We are well-versed about the features, pros & cons, capabilities, and many other things of QlikView, but are still unaware of the achievements of QlikView in the industry sector. The power and strength of QlikView make it different from other available BI tools. With these Best QlikView Case Studies, we are going to measure QlikView’s efficiency and success by looking at some real-time issues of renowned companies. Here, we will discuss how QlikView plays an essential role in solving the issues of CISCO, Mercedes Benz, Sony, and FILA.

Top QlikView Case Studies

In each of the following QlikView case studies, we’ll learn how the company has used QlikView to their benefit and have grown in the competitive market space. Let’s start with CISCO –

1. QlikView Case Study – CISCO

Cisco Systems, Inc is a multinational company based in the USA. The company develops and manufactures networking hardware, telecommunication hardware and provides high-tech services like network and technology architectures. It is spread worldwide having offices in more than 165 countries. It is a leading technology committed to providing people with efficient ways of communicating, connecting and collaborating.

The challenge

To grow as a company and fulfill its purpose, the most important factor is customer relations and customer satisfaction. What Cisco needed was a means to establish a strong customer relationship by knowing the needs and behavior of its customers. For this, they needed an effective BI solution which enables people at Cisco to access sales and customer data from different data sources, transform that data into meaningful and actionable insights. The database of the company was as gigantic as nearly 500 million lines of complex data and installed base records. After researching for a few potential BI technologies, Cisco finalized QlikView as the perfect fit for their requirements.

QlikView’s role

With its sheer flexibility and user-friendly nature, QlikView is empowered in Cisco in more than one way. QlikView has enabled people at Cisco possessing any level of skill to access data and draw insights from it. It serves as a self-service BI tool used for innovative decision making. With the virtue of QlikView, Cisco sealed two major service deals with telecom giants, recorded as the biggest deals in the history of Cisco.

The change

• Business users at Cisco created a QlikView dashboard that acted as an interface for employees at Cisco to access data from its large installed bases.
• QlikView enabled Cisco to consolidate data from Oracle, Hadoop, and Teradata and put it together on a QlikView server.
• Every user at Cisco was able to access and filter out the sales and customer data. It was also able to perform transformative and analytical operations on it by creating graphs, visuals, and reports.
• Managers were able to gain better insights and precise information on sales opportunities, thus, improve sales and revenue.
• Quicker detection and problem-solving in issues related to network operations.
• Helped the marketing department to keep a track on customer’s current services and recommended them of the latest upgrades and available products to keep them up to date.
• It is used for financial planning by executives.
• Incredible business gains with ROI of about 4 million dollars and $100 million-dollar worth of additional revenue by support and service contracts renewals.

2. QlikView Case Study – FILA

FILA is a multinational sporting goods company. It was founded in 1011 in Biella, Italy. It is currently headquartered in South Korea due to the change of ownership and is spread in about 11 countries.

The challenge

The main challenge for Fila sales group was to access information lying in various systems and sites of operations. Another challenge was to circulate this information (data) to business users at different sites.

In addition to that, the company wanted to improve the data quality, data availability and provide easy-to-use analytic solutions to end users. Also, the focus was at providing system users with data about corporate processes so that they can understand the functioning and monitor activities, optimize decision making for the company.

QlikView’s role

Within no time after the requirements were surfaced, QlikView’s solution was deployed to 250 users. QlikView Server enabled the company to consolidate all the data residing at different sites and systems in one place. Also, QlikView offered FILA Europe with one common dashboard which was to be used from any Fila establishment across the globe and its suppliers. It helped to ensure better communication and maintained a solid network.

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The change

• Using the QlikView dashboard, FILA can analyze aspects like production planning, pricing, invoicing, order management, and customer service support, etc.
• The solution has helped FILA in terms of coordination and collaboration improvements; formalization, consolidation, and dissemination of FILA’s knowledge base to every employee for better insights and decision making.
• Users at FILA were able to access and drill through the available data using user-friendly and interactive QlikView dashboards. Even non-technical users were able to surf and work smoothly in QlikView by using the data to filter important information, create visualizations and reports.
• Ability to create in-depth reports and run queries on multi-dimensional data.
• The associative and interactive nature of QlikView engine is best suited for the company’s requirements as it functions as per the natural way of thinking and decision making to bolster the company’s business.

3. QlikView Case Study – Mercedes Benz

Mercedes-Benz India was founded in 1994 and have grown in leaps and bounds since then. Mercedes-Benz is India’s one of the top luxury car manufacturers with a dense network spread across the country. It is currently present in about 31 cities of India having 72 touch points. Mercedes-Benz India has a plan of expanding its operations and business in the top-end luxury segment by 2022.

The challenge

Like every successful corporation, building customer trust and solid customer relations are also the main focus of Mercedes-Benz India. The company wanted a solution that was easily able to understand customer requirements better and keep track of services provided by the various dealerships to the customers. In addition to this, a fast reporting system, improved decision-making and a user-friendly BI tool to gain valuable insights in almost real-time were vital concerns. To ensure, the company needed a robust CRM/DMS system to organize and manage data and an effective business intelligence solution to enable prompt and precise reporting.

After reviewing several potential BI solutions, Mercedes-Benz finalized on QlikView business discovery platform. QlikView’s speed to market, time to value, data analysis capabilities, and convincing proof of concepts impressed them.

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QlikView’s role

Initially, Mercedes-Benz deployed QlikView just to the after sales department to analyze throughout, warranty, and revenue figures. After a successful trial on the Aftersales operations, QlikView was deployed across the company network for Sales, HR, and Plant operations in India has over 300 users.

The change

• QlikView was deployed across Mercedes-Benz in less than four weeks. The information to users was made available from the back-end ERP/DMS systems with fixed update frequencies. After a successful testing phase of centrally deploying the solution, it was rolled out for the whole dealership.
• User adoption was at high rates and easy due to the user-friendly nature of QlikView. Also, QlikView easily integrated data from MB’s existing data sources; SAP and Siebel CRM tools.
• Improved reporting by a centralized dashboard and reports created by QlikView. Analytical teams could easily work with the available data and draw insights important for the company. Every user was able to analyze data reports that helped them in understanding the processes and workflows ensuring better problem-solving.
• Improved After-Sales operations by prompt reporting and close near real-time monitoring of customer interactions and related data. It helped in increasing the vehicle throughput of more than 60%.
• Improved customer attention and problem-solving services.
• Mercedes-Benz is planning on growing its QlikView application by deploying QlikView on mobile so that high management people have data and insights on their fingertips. In addition to a successful run in India, Mercedes-Benz will roll-out QlikView solutions for the APAC region and Europe as well.

4. QlikView Case Study – Sony Europe

SONY is a multinational manufacturer of electronic consumer products. It is a leading Japanese company. Sony Europe aims at utilizing valuable business information available as raw data and transforms it into meaningful insights.

The challenge

Sony Europe’s Spain division, having a turnover of 1.166 billion euros in 2009 felt the need for a BI system that can analyze multiple scenarios and analytical processes. Impressed by QlikView’s ease of deployment and adaptability, the company finalized QlikView as their BI solution.

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QlikView’s role

By deploying QlikView, Sony instantly realized the potential of the tool and acknowledged the enhancements made by it in terms of visibility provided by QlikView for business information and dynamics. In addition to this, QlikView solutions were created to offer customer insights and for Sony Style Store Shops which benefited the company a great deal.

The change

•  Integration of data relevant to Sony from various data sources such as Oracle, SAP NetWeaver BW, Microsoft Sharepoint, Microsoft Excel, MS Access, Sony’s planning files, etc., into a single QlikView BI environment.
• Rapid application development and deployment followed by prompt assists in decision-making and analysis.
• QlikView Desktop and Publisher deployed in Sony Spain for about 80 users.
• Improved graphical analysis of key performance indicators like sales, visits, number of references, innovations, average amount, rate conversion, budget variations, stock rotation, indices, deviations, market share, expenditure, discounts and margins, innovations online presence, etc.
• Creation of QlikView scorecards for internal departments in Sony.
• The areas of business benefited from QlikView solution in Sony are marketing, management, finance, STIC, Sony Style Stores, customer insight, commercial sector, etc.
• Increased visibility into business processes and consumer trends. It also improved resource management, risk analysis and threat detection for the company.

Summary

It is not the end; today many industries are using QlikView and, amongst all, these are the renowned QlikView Case Studies. With these four companies FILA, Mercedes-Benz, Sony, and Cisco we talked about the major role of QlikView in the betterment of the company’s business. However, Applications of QlikView are not just restricted to these companies but are also used in different sectors such as finance, insurance, etc.

This article is dedicated to the Qlik Advanced Analytics integration in QlikView and Qlik Sense. Here, we will start by understanding the basics of advanced analytics. Then we will proceed with learning how Qlik has added advanced analytics features in QlikView and how does it work.

Qlik Advanced Analytics Integration – Analytic Connections in QlikView

1. What is Advanced Analytics?

Advanced analytics is a set of advanced operations or calculation performed on data by third-party engines. These advances techniques and operations can be anything like predictive analytics, location analytics, machine learning, big data analytics, data mining and visualizations.

Advanced analytics capabilities are needed by any BI tool as they offer a limited analytical capability to the users which in some scenarios prove to be insufficient to make the most meaning out of the data that exists. Thus, such capabilities enable a user to perform advanced and complex analytical operations on massive data sets and return correct results. The user can thus dive deeper into the data and gain unique insights and make predictions based on them.

Do you know What s Big Data & Its importance in IT Industry?

2. Qlik Advanced Analytics Integration

Qlik has always focused on improving their BI tools with the latest technology and trend. The integration of advanced analytics in Qlik Sense and QlikView is an effort made in the same direction. The capability of data integration and advanced analytics serves an enterprise by providing important insights like fraud detection, inventory optimization, sales forecasting and prediction, market analysis, pricing optimization and so on.

Qlik advanced analytics integration important for the two main reasons. Firstly, if we look at the traditional way of developing and designing the BI tools. Developers used to design a general analytical model based on some commonly asked queries for the available data. However, this makes a tool rigid and its analytical pathways static. That is, a user is restricted to analyse a given set of data in one or two ways. With the integration of advanced analytics, users have the flexibility to apply advanced analytical algorithms on the data rather than using the precomputed and pre-modelled ways.Secondly, the batch processing methods were used in query-based designs, resulting in the sending of big data sets to third-party engines as developers were unaware of the usefulness of the entire set

Most of the data loaded into such batches went unused. Thus, making it highly inefficient and slow.

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But, with Qlik’s associative indexing engine technology, data updates itself quickly according to the context and selections. As soon as you make a selection on the app, the associative engine quickly forms new associations between relevant data units and analyses. It is the current context. Here, only a small set of relevant rows and columns send to the third-party engine. Which performs advanced analytics on it and sends it back to the client app in real-time.

3. How Qlik Advanced Analytics Integration Works?

Advanced analytics provides a set of new analytical capabilities. Which enables users of QlikView and Qlik Sense to explore and analyse their data even better. This facility is leveraged by connecting QlikView with third-party engines such as R, Python, MATLAB, Spark, Regex etc. All of the analytical engines contain a unique set of functions, expressions and algorithms, can apply on the data sets within QlikView. We can do this by using connectors specific to analytical engines. However, Qlik also provides open-source APIs for the users to create connectors of their choice and use case.

Now, let us see on a technical front, what happens when a BI tool like QlikView integrates with third-party advanced analytics engines.

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1. When a user interacts with the QlikView desktop, they generally make selections or search data. This triggers the associative engine into making relevant data association according to the selections made.
2. Due to the selections made, the associative engines refines the data contextually and updates it for further advanced analytics. We can store the set of data, which is select in the in-memory.
3. Here, we can send the in-context or relevant data to the third-party analytic engine connect via a connector or plug-in.
4. The analytics engine processes the data and applies advanced calculations and algorithms on the received data and send it back to the Qlik engine.
5. Resultant data will combine with the data residing in-memory of QlikView.
6. The transformed data will receive after advance analysis instantly use for the visualization tools and represented on the dashboard.

5. Analytic Connections in QlikView

In QlikView Jargon, the advanced analytics capabilities referring to as server-side extended analytic connections. It offers a built-in library of expressions and functions of different language like R, Python etc. If the user needs algorithms and functions for statistical analysis, then the R engine is suitable. For example, you might need a specific forecasting function from R which can be called within the QlikView script and computed on the go, instantly producing results. Whereas, Python and MATLAB are more general purpose and machine learning oriented languages. The analytical engines for different languages are called Server-side Extensions (SSE) and can be configured into QlikView Desktop and QlikView Server using the Settings.ini file.

So, this was all about Qlik Advanced Analytics Integration. Hope you liked our explanation.

6. Summary of Qlik Advanced Analytics Integration

Thus, providing advanced analytics capabilities, users are able to process their data in different ways. This gives them the flexibility and unique insights, which may be miss when we use Qlik tools for query-based and batch approaches.

Feel free to drop your queries and suggestions in the comment box below.

Let us make an effort and shift our focus from the specific BI tools like QlikView and QlikSense to Qlik as a technology to Big data. Also, in this article, we are going to keep our discussion focused on Qlik approach to big data. Here we will discuss different methods of utilizing Big Data in Qlik and several benefits of Qlik for Big Data.

So, let’s start with understanding how Qlik approach to big data and what it has to offer its users.

Qlik Approach to Big Data

Qlik is known to be a pioneer in data analytics and management. As it has reached a point where its user base has grown to be of 48,000 customers spread across 100 countries. Qlik provides efficient BI solutions for both tech and non-tech users. Who use it to explore data and comprehend the story behind it. Qlik solutions offer data exploration, visualization, discovering insights. Also, lets users make informed decisions based on their analysis to foster their businesses.

As we know, billions of terabytes of data are being generated by all sorts of businesses worldwide which is referred to as big data in common terms. Businesses see big data as a potential source of information regarding the requirements and behavior of their customers, suppliers, products, partners, and markets. This makes big data a strategic and economic asset for organizations. Thus, organizations are always in search of efficient business intelligence technologies. Which lets everyone in the enterprise work with data and give them user-friendly tools to transform and visualize data to provide it relevance and context. And for the same reason, enterprises have turned to Qlik and the solutions offered by it. Qlik has ties with over 1700 partners, many of which are big data-centric tools such as Cloudera, Hadoop, Google BigQuery, and AMS.

Do you know What is Big data and its Importance in the IT Industry?

What are the Methods of Utilizing Big Data in Qlik?

When it comes to dealing with big data, a common concern is that not all the employees in an organization are adept data scientists or even close to knowing anything about it. So, there must be such big data analytics and techniques which enables as well as empowers every user to conduct proper operations on data and generate informative reports from using it. In other words, they need a simple, user-friendly guided analytics environment to help them manage and understand the big data.

Another challenge faced by users while working with big data is they were expected to know which part or segment of the entire big data repository they want to work with, which is not an easy task for non-technical users. To overcome such issues, Qlik has come up with certain methods which can be used individually or in combination to work with big data.

1. In-memory (QIX Engine)

Qlik’s Indexing Engine (QIX) has the capability of compressing big data to ten percent of its original size which is enough for some customer’s use. Qlik solutions work by accommodating the compressed data into the in-memory and load it from there.

2. Segmentation

Big data get easy to handle and visualize by dividing a large application into small segments based on categories. For instance, if an application is showing the geographic data of the entire world, you can break it down into small segments per country. Thus, this process is called segmentation.

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3. Chaining

Chaining is contrary to segmenting. Chaining is linking different segments or subject-specific views to one another. It forms a logical association between application segments. Big data analysis and handling become easy by first segmenting larger applications into subject-specific views and then linking them with each other through chaining.

4. Direct Discovery

Another way to handle big data is through direct discovery. Here, some data (small tables) still resides in the in-memory but a large chunk (large tables) resides in the database. A user gets to directly access the external database when in need of the large tables. It is known as a hybrid approach as it brings together the in-memory system with the external database storage system.

5. On Demand App Generation (ODAG)

A unique method, where an on-purpose application generates having only the section or data set that you require to work with. There are two divisions of this process:

First, you have a Selection app, which is a portal where data is been sorted into categories and sections such as customers, product, vendor, time period, geography etc. You can select the data set of your choice.

Then, in the second part, a new application is launched having only the section of data that you selected from the database through the selection app. You can work with the data set as you like and create reports and dashboards. You can always go back to the selection app and work with new sets of data.

Advantages of Qlik for Big Data

Qlik Approach to Big Data is incomplete without discussing its benefits for it. One can think of many advantages of using Qlik solutions for big data. We have tried to list out a few for you.

1. Qlik gives an associative and augmented experience to the user by assimilating data from various data sources and associating it logically. The associative engine efficiently gathers data from different data sources and indexes it for a better understanding of the data structure.
2. Qlik supports a wide range of user base and offers a lot of services such as guided analytics, self-service visualization, and exploration, collaboration and reporting, geographic and advanced analytics, AI capabilities (Qlik Cognitive Engine), data integration etc.
3. It helps in making sense of big data by empowering the users with capabilities to fetch data from varies sources and use it to extract meaning from it.
4. Big data is a reservoir of important information and insights in business. Technologies like Qlik helps the business users to access that data, model and structure it, then finally represent it visually and explore it better.
5. Qlik tools empower every user in the enterprise, regardless of their skill set, explore and analyze big data efficiently.
6. It can connect to different types of data sources like Excel, XML. Or, big data sources such as Cloudera, Hadoop, Teradata. App-specific sources such as SAP, Salesforce etc.
7. Qlik’s associative engine enables associations between data tables which makes navigating within large data sets very easy. The user doesn’t have to drill-down in complex rows and columns of large data tables. Thus, it makes big data much more manageable.

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Solutions Offered by Qlik for Big Data

Qlik currently offers many platform-based solutions aimed at aiding developers or purposes like data management, data visualization, etc. Some latest tools offer by Qlik are-

1. QlikView: A highly interactive tool for data discovery and guided analytics.
2. QlikSense: A self-service, user-friendly data analytics and, visualization platform.
3. QlikCore: Development platform for customizable and embedded applications.
4. Qlik Data Catalyst: An enterprise data management solution. There are some value-added products provide, to enhance the capabilities of existing tools.
5. Qlik NPrinting: Report generation and distribution tool for Qlik Sense and QlikView.
6. Qlik GeoAnalytics: An advanced mapping and location-based analytics platform for Qlik Sense and QlikView.
7. Qlik Associative Big Data Index: Enables binary indexing on data stored in Hadoop clusters or data lakes for fast data discovery.
8. Qlik DataMarket: Provides Data as-a-service (DaaS) from comprehensive data libraries from different data sources on a subscription basis.
9. Qlik Connectors: Provides connectivity to internal and external data sources. It enables connection with web-based, app-based (Salesforce, SAP), file-based, cloud-based data sources.

Summary

Qlik is a robust technology aiming at providing as many customers a hassle-free data analytics, management, and visualization experience. One major advantage of using Qlik solutions amidst various other BI platforms is Qlik’s scalability and flexibility to adapt to changing big data landscape.

We hope this explanation of “Qlik Approach to Big Data” was helpful to you and answered all your questions. If you have any query, tell us through comments.

Qlik provides its customers with a wide range of products. Two such popular BI tools are QlikView and Qlik Sense. Some of you might be familiar with either or both tools. Here, we are going to discuss QlikView Vs Qlik Sense. Although, both the tools are business intelligence platforms and more or less serve the same purpose, there are certain things that make them distinctly different from each other.

Let us start out discussion on how QlikView is different from Qlik Sense and perhaps find which one is better Business Intelligence tool.

QlikView Vs Qlik Sense: Overview

Before we start the difference between QliView Vs QlikSense, we will discuss the introduction of these two terms.

i. What is Qlik View?

QlikView is a data analysis and visualization tool which enables users to fetch, integrate, process and analyze data from varied sources. We can use it for developing data models, analytical applications, dashboards, visualizations to create analytical reports and deliver it to end-users via Access point.

Through the access point, end-users can access data, carry out searches, create data models, associations, visualizations etc. to analyze data and discover data trends.

Features of QlikView

• Dynamic BI ecosystem (Interaction with dynamic apps and dashboards).
• Default and custom connectors
• Data visualizations
• Capable of building guided analytics applications and dashboards.
• Guided and advanced analytics

ii. What is Qlik Sense?

Qlik Sense is a self-service data discovery and analysis tool which focuses on ease of use for the user. It provides a modern and interactive user interface where you can use the tools for modeling and managing data, creating visualizations, layouts, and stories. It is not very technical in its approach and thus very user-friendly.

Features of Qlik Sense:

• Smart search options like Google and associative functions.
• Fast and reliable connections to multiple data sources.
• Drag and drop visualizations
• Generate personalized reports and detailed, interactive dashboards.
• Self-service data discovery

Difference Between QlikView and Qlik Sense

Let us start QlikView Vs Qlik Sense based on what features they do or do not provide.

i. OLAP functionality

QlikView provides Online Analytical Processing capabilities to perform analytical operations on the data whereas, Qlik Sense does not have OLAP functionality.

ii. ETL capabilities

Both Qlik Sense and QlikView provides Extract, Transform and Load (ELT) capabilities.

iii. Self-service visualizations

QlikView does not offer self-service visualization capabilities whereas Qlik Sense does.

iv. Guided analytics

QlikView provides guided analytics functionalities whereas Qlik Sense does not.

v. Filter requirements

Data filters are required in QlikView whereas, they are not needed in Qlik Sense.

vi. Data storytelling

Data storytelling is a feature unique to Qlik Sense and is not available in QlikView.

vii. Data mining & analytics

Data mining & analytics capabilities are provided in Qlik Sense only.

viii. Modern visualizations

Qlik Sense is known for its attractive as well as interactive user interface. Thus, Qlik Sense provides modern visualizations to represent data with an easy to use drag-and-drop functionality. Whereas, QlikView offers basic visualizations.

ix. Associative indexing engine

Both Qlik Sense and QlikView have a robust associative indexing engine (QIX Engine) at its core.

x. Mobile support

Both Qlik Sense and QlikView offers mobile compatibility. Qlik Sense has a mobile app and is supported by iOS 11.0 or later. Whereas, QlikView supports Apple Mobile Safari (iOS 10 or later) which is a browser support.

xii. Advanced analytics and integration

Qlik is working to provide efficient features and capabilities on advanced analytics and integration. However, better advanced analytics integration capabilities are offered in Qlik Sense than in QlikView.

xiii. Integrated app development environment

QlikView is a development-based tool as provides an integrated app development environment which is not so in Qlik Sense as it a visualization centric tool.

QlikView Vs Qlik Sense – Verdict

QlikView is more of a traditional, technical tool for shared business intelligence, data analytics and reporting. Whereas, Qlik Sense can be regarded as a modern data exploration platform. Although, both the tools are created on the same ground, which is to serve as a BI tool. They are distinct from each other in many ways.

So, instead of declaring a clear winner as to which tool is better, it is only fair to say that both the tools are useful for respective purposes. On one hand, where Qlik Sense might be more popular in the market for its sheer ease of use and simplicity as it is a self-service and data exploration (drag-and-drop functionality) tool which can be used by users of any caliber and skillset. While on the other hand, QlikView focuses more on application development and guided analytics and less on user interaction and responsiveness.

So, this makes the users or the need of the organization entirely responsible for which tool amongst the two (QlikView Vs Qlik Sense) is the best choice for them. If they want to perform technical operations and work with data on the ground level, then QlikView is the choice for you. And, if you wish to just design and create visually appealing data reports and dashboards, then Qlik Sense is the answer. Both of them can also be used simultaneously for the respective services they are good in providing at.

Also, See – Latest Job Trends and Salaries in QlikView

QlikView and Qlik Sense – Extra Points

Next, we take an elaborative dig at the matter and provide a detailed pointwise comparison.

• Data loading is slower in QlikView as compared to that in Qlik Sense.
• If using QlikView, organizations need to make an investment in recruiting specially trained QlikView developers. Whereas, in the case of Qlik Sense, there is no condition of being technically trained and skilled as Qlik Sense is more user-friendly in embedded analytics.
• Licensing and purchasing process is a little more complex for QlikView than for Qlik Sense.
• QlikView supports only English as a language whereas Qlik Sense supports English, Chinese, Japanese and German.
• The target customer size for QlikView is small, moderate and large industries whereas, for Qlik Sense it is small and moderate industries.
• QlikView offers greater and better control to developers over the design and control of applications thus, objects are more customizable. Whereas, Qlik Sense does not give users much customization and development options. Rather it is user-friendly and easy to use.

Must refer – Latest Job Trends and Salaries in Qlik Sense

Summary

Qlik has kept its focus on developing and improving Qlik Sense as a tool, investing a large chunk of their time and resources on it. However, they are also dedicated to make QlikView a better product for the user base that still exist and serve them to their best of capabilities. Also, as the purpose behind both these BI tools was to give users a good and complete data visualization and analytic software, efforts are made by Qlik to decrease the seeming differences between the two and make them the best versions of them.

Still, have a doubt in QlikView Vs Qlik Sense? Feel to write us!

Now let us do some more weighing of Qlik Sense against another giant in the BI industry, Tableau. Here, we will compare Qlik Sense with Tableau based on different factors in our attempt to find a better tool amongst the two. Firstly, we will learn the features of Qlik Sense and Tableau and then compare both BI tools in various aspects.

Difference between Qlik Sense & Tableau

1. Qlik Sense Vs Tableau

Both Qlik Sense and Tableau are top-ranked self-service BI solutions. Although both the tools aim at serving the same purpose which is being a self-service data visualization and analysis tool, there are some differences between the two. Initially, Qlik Sense was more of an enterprise-ready tool with a robust indexing engine. Whereas, Tableau focused on data visualizations and ad hoc queries.

Moreover, both the tools have evolved with time and have more or less the same capabilities and the goal to serve. However, there are some distinctions.

Qlik Sense is known for its enterprise capabilities such as data access, management, repeatable reports, and scalability (due to the QIX data engine).

• Qlik Sense is improving in visualization and dashboarding.
• Tableau is good in data drills, insights and data discovery.
• Tableau has also introduced various enterprise capabilities and a data engine named Hyper.
• The new data engine Hyper is believed to integrate IoT analytics.
• Tableau offers good data connection options such as connecting to live data sources (SAP HANA, Teradata).

2. Qlik Sense Vs Tableau: Features of BI Tools

Now, we will learn different features of Qlik Sense and Tableau.

Features of Qlik Sense are:

• Drag-and-drop visualizations
• Smart search
• Quick and reliable connections to multiple data sources
• Access to real-time analytics anytime, anywhere
• Data storytelling functionality
• Self-service simplicity
• Shared object library
• Progressive creation
• Managed data connections
• Rapid development environment
• Powerful open and standard APIs
• Multi-source data integration including big data
• Manageability
• Enterprise-level security
• Scalability

Features of Tableau are:

• Patented technology from Stanford University
• Toggle view and drag-and-drop
• List of native data connectors
• Highlight and filter data
• Share dashboards
• Embed dashboards within
• Mobile-ready dashboards
• Data notifications
• Tableau Reader for data viewing
• Dashboard commenting
• Create “no-code” data queries
• Translate queries to visualizations
• Import all ranges and sizes of data
• Create interactive dashboards
• Server reset API
• String insights into guided stories
• Automatic updates
• Metadata management
• Security permission feature
• Tableau public for data sharing

3. Qlik Sense Vs Tableau: Comparison Between BI Tools

i. Usability

Tableau has got better usability than Qlik Sense as per the users’ reviews. Tableau is faster in setup, data connections, creating dashboards, file sharing etc. However, Qlik Sense is expected to get better with time with the new versions to come.

ii. Dashboards

Tableau has better and quick in response dashboards than Qlik Sense. Although, Qlik Sense also has a very attractive and easy-to-use user-interface. But the overall dashboards along with the quality and detail of graphs and charts are slightly better in Tableau. However, Tableau is better in scorecards.

iii. Reporting

Both Qlik Sense and Tableau stand neck-to-neck in the case of standard BI reporting functionality. However, Qlik Sense is believed to be better in Ad hoc reporting, report output, data transformation, WYSIWYG report design, and scheduling than Tableau. Tableau is good in predefined reports.

iv. Pricing

Qlik Sense has a quote-based pricing model where the user has to pay a certain amount as a perpetual license fee to get the token or license for Qlik Sense access. The price quoted is based on the number of Qlik Sense desktop users. It offers on-premise and cloud-based deployments. It also offers free versions of Qlik Sense Cloud and Desktop.

Tableau offers monthly, annual or quote-based payment choices. It has a free trial version for Tableau Desktop. The paid scheme ranges from $35 to $70 per month. However, the annual subscription fee for the personal edition is $999 per user and for professional/enterprise edition is $1,999 per user.

v. Access Control and Security

The access control and overall security capabilities are better in Qlik Sense as compared to that of Tableau.

vi. Implementation

For implementing or deploying Qlik Sense, it is better to seek help and hire Qlik consultants. Whereas, in Tableau, you need to be specific about the services you require under a Tableau version as the corresponding Tableau server needs to be configured for appropriate functions.

vii. Clients

Some famous clients of Qlik Sense are Canon, Fila, Cisco, McAfee, Qualcomm etc.

Whereas, some popular clients of Tableau are Pandora, Deloitte, Citrix.

viii. Device Supported

Both Tableau and Qlik Sense provide a broad range of device support such as Windows, Android, Mac, iPad/iPhone, web-based platforms.

ix. Self-Service

Qlik Sense is good in self-service functionalities like data discovery and searching. Whereas, Tableau performs better in auto modeling, collaboration and workflow, calculated fields, and data column filtering which are also self-service capabilities.

x. Advanced Analytics

Tableau is better than Qlik Sense in advanced analytics capabilities like predictive analysis, data visualization, and big data services.

xi. Platform

The overall platform performance of Qlik Sense in terms of customization, mobile user support, user roles, access management, sandbox/test environments, and reliability is better than Tableau. While Tableau is better in internalization.

xii. APIs and Embedding

Qlik Sense provides a better environment for API integration and embedding than that in Tableau.

xiii. Customer Support

Qlik Sense provides customer support through e-mail, phone, training, live support and ticket system. Whereas, in Tableau, customer support options are e-mail, phone, and training.

xiv. Scalability

Qlik Sense is a lot more scalable than Tableau. The Qlik Sense applications can be easily scaled especially while dealing with big data.

xv. Company Size

Both Qlik Sense and Tableau operate primarily in medium (51-1000 employees and $50-1000 million in revenue) and large-scale (over 1000 employees and $101 million in revenue) companies. However, in some cases, they are also used in small-scale (up to 50 employees and $50 million in revenue) companies.

4. Summary

At last, it is only fair to say that both the tools (Qlik Sense and Tableau) give competition to each other but hold a lot of potential as effective self-service BI tools. However, both the tools differ by some capabilities and features making one better than the other in respective cases. However, as per the customer review, Tableau has got a little more edge over Qlik Sense for its sheer ease-of-use and attractive graphics (UI).

Big data is the gold mine for businesses of all kinds. Every organization wants the best data analysis and visualization tool for their Big Data. In this article, we will try to give you all the information about the best BI tool for Big Data Visualization. Here, we will learn the difference between Tableau vs Qlik Sense vs Power BI.

So, are you ready to explore Top BI Tool for Big Data Visualization?

1. BI Tools for Big Data Visualization

In today’s time, business relies greatly on big data and the information encrypted in it to be able to comprehend current trends and business scenarios in order to make wise and informed decisions in the future. Hence, this makes having a good business intelligence tool to analyze and visualize big data imperative.

It is without a doubt that we have quite a few BI tools which aim at big data visualization in the market presently. Most of them serve a particular purpose and it really comes down to your requirements and use-case that which of such tools are going to suit you the best. However, we are here in our quest to find the best general-purpose BI tool for big data visualization and analysis.

Do you know the current trend of Big data in the IT Industry?

2. What is needed in a good tool?

Before we get into the dichotomy of individual BI tools, we must understand what are the basic needs for any big data visualization tool to be good.

• Every data visualization tool is expected to transform unfathomable data into eye-pleasing charts and graphs and let them convey the hidden message in the data to the business users and analysts.
• Rather, a tool must also have the capability to analyze, process and present the data in a digestible manner.
• The tool must be efficient in creating understandable data reports and dashboards by assimilating and aggregating massive and complex data from different sources.
• The tool must be so designed that every user, regardless of their background and skill set can learn to use it like any other software or application used daily.
• A tool must focus on being an interactive self-service analytics, development, and visualization tool. This is unlike the traditional enterprise-wide, IT-developed software which can only be used by a small group of technical users. A tool should give entry-level users the capability to use it efficiently and gain insights into big data.
• Filtering, processing, and slicing-dicing of big data should be easy.
• A tool must provide enough features for collaboration and insight sharing within and outside the organization.
• The visualizations must be plenty and intuitive for any technical or non-technical user to understand it and draw meaningful insights from it.

Recommended reading – Why should you learn Big Data? 

3. Top BI Tools for Big Data Visualization

Top three Business Intelligence tools for big data visualizations are Tableau, Qlik Sense and Microsoft Power BI. Let us understand what role each play in big data visualization and how good is it with big data. Also, all the three tools are declared to be the leading BI tools according to the Gartner’s Magic Quadrant for Business Intelligence and Analytics Platform (2018).

Gartner’s Magic Quadrant for Business Intelligence and Analytics Platform (2018)

i. What is Tableau?

Tableau is the most popular and leading BI tool presently. It has the best visualization capabilities with a perfect front-end graphical UI. It also has some built-in analytics modules which can be used directly by the user on their data. Also, it gives its users the ability to develop app objects, customize dynamic visuals, and distribute reports and documents to other users via the web.

ii. What is Qlik Sense?

Qlik Sense is a simple and interactive data visualization tool which enables users to import and aggregate data from varied big data sources. They can further use the data visualization tools of the software to shape raw data into meaningful information. Qlik also claims QlikView as a potential contender as an efficient big data tool as it can also capable of integrating with multiple data sources at a time.

iii. What is Microsoft Power BI?

Microsoft Power BI is Microsoft’s very own data visualization tool. It becomes better than the rest in some ways as it is compatible best with Microsoft Azure and Microsoft cloud environment. Also, users can connect to Excel to import data and create personalized data dashboards.

4. Tableau vs Qlik Sense vs Power BI

In the fight of best BI tools for Big data Visualization, we will discuss the difference between Power BI and Tableau and Qlik Sense:

Tableau vs Qlik Sense vs Power BI

i. Visualization Capabilities

Power BI: It is an easy-to-use platform which enables users to import data from varied sources and use it with charts, graphs, tables to visualize it. It has been regarded as “the simplest to use tool among the leading BI vendors” by Gartner’s Magic Quadrant for Business Intelligence and Analytics Platform (2018). It supports data integration from various sources like Hadoop, on-premise files, or cloud-based sources.

Qlik Sense: It is a self-service analytics tool with an in-memory data storage engine. It provides good visualizations which are dynamic due to the in-memory engine. Data is linked to creating associations which updates the visualizations as soon as data behind them is updated at the source. Meanwhile, users can keep on exploring and working on the dashboard.

Tableau: Tableau is known for its perfect graphics and visualization capabilities. Along with this, it is easy-to-use software. It enables data integration from varied sources. Also, it can take data in-memory or access it directly from the source if files are large to accommodate in-memory. It was regarded as “Most attractive and intuitive visualization tool” by Gartner’s Magic Quadrant for Business Intelligence and Analytics Platform (2018).

ii. Advances Analytics Capabilities

Power BI: It supports R language-based visualizations. Also, it provides advanced features such as forecasting, clustering and decision trees.

Qlik Sense: It does not support R or Python-based objects. However, Qlik promises to provide language support in the coming versions. You can use features such as regressions, clustering, and predictive analytics via API connections to third-party apps.

Tableau: It provides fully integrated support for R and Python. Also, it has in-built tools for clustering and forecasting.

iii. Cloud Capability

Power BI: It is compatible with Microsoft Azure which offers cloud-software called “Cloud-first”. If you wish to leverage the cloud capabilities on a desktop, you need to have a cloud account in order to share insights and visualizations on the cloud.

Qlik Sense: It offers a SaaS cloud product. Although, users prefer the server version.

Tableau: Tableau is compatible with robust cloud platforms such as Microsoft Azure, Amazon Web Services etc. You can use Tableau’s cloud capabilities either through a Tableau managed cloud system or through a third-party cloud platform.

iv. Pricing

Power BI: Microsoft Power BI services cost about $9.99 per user per month.

Qlik Sense: For the enterprise version, the price is $15,000 for one token. It grants 10 timed login passes and unlimited use for one user. For the cloud version, the prices are $20 for a single user and then $25 per user for multiple users.

Tableau: Tableau charges for different services are,

• For Tableau Desktop Personal $35 user/month.
• For Tableau Desktop Professional $70user/month.
• Tableau Server $35 user/month.
• Tableau Online $42 user/month.

v. Storage Limits

Power BI: The subscription limits allow total storage of 10GB cloud storage for data. Additional charges are applied if you want to expand the data storage capacity.

Qlik Sense: The Qlik Sense Cloud Business subscription limits allow 500GB of cloud storage of data per workgroup.

Tableau: The online subscription offers a total of 100GB data storage on the cloud.

5. Other BI tools for Big Data Visualization

Along with the three big players that we just discussed, there is a lot of other good big software in the market. We have provided some names of highly-rated big data software in the list below (2019).

• SAP HANA
• Sisense
• Google Charts
• Domo
• Cluvio
• SPSS by IBM
• Phocas
• Statistica by DELL
• Datorama

So, this was all about BI Tool for Big Data Visualization. Hope, you liked our explanation.

Power BI vs SSRS

Power BI is a popular new age technology, it is often subjected to comparisons with other similar technologies. Comparisons are important as they allow us to see two potential technologies in an analytical light. We get to understand the real differences between them and choose the better one. Comparisons also help the creators to better their products.

Moving further in our Power BI Dataflair tutorial series, now, we are going to learn about the top differences in this Power BI vs SSRS article.

But before that let us take a quick glance of Power BI and SSRS.

What is Power BI?

Power BI is a data analysis and reporting software created by Microsoft. It is a modern-day business intelligence tool which is loaded with smart and user-friendly features. Power BI extends its services in the areas like data connectivity, data transformation, data preparation, data modeling, reporting and dashboarding. In addition to this, one can utilize Power BI’s advanced capabilities such as using DAX formulas, custom visuals, etc.

Before proceeding ahead, please complete the DAX in Power BI

What is SQL Server Reporting Service (SSRS)?

SQL Service Reporting Service (SSRS) is a server-based report generating platform. Much like Power BI but a little conventional in its use, SSRS is mainly used for enterprise visualization of data. It is used for generating, viewing and sharing reports. SSRS has a programming interface and an integrated set of processing components. SSRS demands greater manual effort because of its less graphical, drag and drop features and more programming-based tools for the report making. It is also a product by Microsoft and is a part of Microsoft’s SQL Server suite. It works in close association with tools like Visual Studio and SQL formatting tools.

Basic Differences between SSRS and Power BI

Here are some basic differences between Power BI and SSRS, listed below:

• Power BI is free, SSRS requires SQL Server license. However, you require purchasing Power BI Premium license for PBIRS.
• Power BI is cloud-based, SSRS is server-based.
• Power BI is more modern and graphical. SSRS is conventional and involves manual effort and time to create reports and analysis.
• Can use data from the cloud in Power BI. SSRS can only use on-premise data.
• Power BI Report Server (PBIRS) is the successor of SSRS and has more features than SSRS. For one, it can use and render both interactive PBIX and analytical XLSX reports which SSRS cannot.
• PBI now has Cortana integrated for AI-based natural language, Q&A about your data and reports in Power BI. SSRS does not have this feature.
• In SSRS, you need to purchase a license, define requirements and scope, customize/develop your software according to the requirements, deploy, develop reports in a coding interface, schedule data refreshes, etc.
• Power BI has a graphical interface with the drag-and-drop capability to create reports. You can work with unstructured data, use modern rendering, publish, integrate and collaborate easily across platforms.

Power BI vs SSRS

After the general comparison that we just had, let us dive deep and have a pointwise comparison between Power BI vs SSRS based on some important factors.

1. Technology

Power BI: Microsoft Power BI is a new age business intelligence technology used for dealing with data and creating reports. It is user-friendly software with easy to use features for creating, publishing and sharing reports.

SSRS: SSRS is SQL Server Reporting Service which is also a Microsoft’s product. It is a conventional, server-based report generating and data analysis software.

You should definitely learn to apply Filter in Power BI Desktop

2. History

Power BI: It is a newer technology as compared to SSRS as the report server of Power BI known as Power BI Report Server was launched in 2017.

SSRS: The SQL Server Reporting Service was launched commercially in the year 2004.

3. Benefits

Power BI: User-friendly and easy-to-use tool for report creation and data analysis. It is rich in graphical capabilities.

SSRS: SSRS does not have much to offer in the area of graphics. Rather, it has a good drill-down capacity.

4. Implementation

Power BI: Power BI Report Server (PBIRS) is capable of generating, publishing and sharing reports and dashboards for cloud-based as well as server-based platforms.

SSRS: SSRS only generates and share only server-based reports.

5. Accessibility

Power BI: You can access Power BI software on three different kinds of platforms; web, mobile devices (apps) and desktop.

SSRS: You can use SSRS on the web and on the desktop.

6. Licensing

Power BI: The initial version of Power BI and Power BI Report Server is free of cost. Although, if you wish to go premium, you will have to purchase a license. The premium includes features like a gateway, security, collaboration, etc.

SSRS: To use SSRS, it is necessary for you to buy a SQL Server license.

Don’t forget to explore the Power BI Gateway Tutorial

7. Components

Power BI: Microsoft Power BI is a cloud-enabled SaaS. Also, it is an open-source HTML 5 enabled platform for data analysis.

SSRS: SSRS is a server-based enterprise report generation and visualization tool.

8. Usage

Power BI: More user-friendly due to its rich graphical user interface and drag-and-drop capabilities.

SSRS: Less user-friendly as it focuses more on a coding/programming interface.

9. Data dependency

Power BI: In Power BI, you can work with both structured and unstructured data.

SSRS: With SSRS, you can work with structured and semi-structured data but not unstructured data.

10. Occurrence

Power BI: Power BI is single-handedly dominating the BI market as of 2019. Microsoft’s Power BI Report Server is also preferred as the reporting server over SSRS.

SSRS: SSRS is a conventional tool using old technology. Although, it is still in use more than Power BI.

11. Training

Power BI: Power BI is easy to learn as it uses a graphically rich user interface with drag-and-drop features to create a report. You don’t really have to engage with the technical and coding part of the process which makes it a user-friendly tool that can be learned by a user of any skillset.

SSRS: You need to come from a technical background to learn SSRS. In SSRS, a developer generates reports through coding and designing them manually. This may not be as easy to learn and do as Power BI, but it gives you a better understanding of the process and things going on under the hood.

Summary

Here we come to the end of our tutorial on Power BI vs SSRS. Now that we have done a thorough analysis of both the software in question; Power BI Report Server and SQL Server Reporting Service. Deciding on which one is better is a little tough as it depends on the user’s requirement. If you require generating and using only simple, paginated reports on-premise in an enterprise, you must go for SSRS. SSRS is also cost-effective for that matter.

On the other hand, if you require creating and using interactive and analytical reports with rich graphics, Power BI Report Server should be your choice. Although, if your requirements fall somewhere between these two, the Power BI Report Server is a good choice as it has all the features that SSRS has.

Power BI Free vs Pro (Paid) – 60 Days & Membership Preliminary

2. Power BI Free and Pro (Paid)

This will take a gander at how the Power BI (free) offering can utilize inside your association. An association implies that you have an occupant and can oversee clients and administrations inside that inhabitant. As a director, you can control permit task, or you can enable clients to join as a person. We will take a gander at the Power BI (free) permit and how you can control singular join.
Do you know How to Create Power BI Combo Chart?

3. Power BI Free Vs Pro

Here, we discuss a clear difference between Power BI Free Vs Pro (paid). So, let’s start:

a. Power BI Free

We will start Power BI Free subscription, in this Power BI Free Vs Pro Tutorial:

Power BI Free Vs Pro Tutorial – Power BI Free Subscription

i. Singular join Vs Permit task

Clients inside your association can access Power BI in two diverse ways. They can separately agree to accept Power BI, or you can relegate a Power BI permit to them inside the Office 365 administrator entrance.
Permitting singular join decreases the weight, from the association managers, by permitting the clients that are occupied with Power BI to agree to accept free.
For more control, you can obstruct sign and relegate Power BI licenses yourself inside the Office 365 administrator focus. This enables you to be particular of who can get to what benefits inside your association. This is additionally an extraordinary choice on the off chance that you need to manage to evaluate and need to know precisely who can utilize what.
Read about the Power BI Funnel Charts (Custom Visuals)

ii. Method to get Boundless Permit Square

Inside the Office 365 administrator focus, under Billing > Licenses, you could possibly observe Power BI (free) with boundless licenses.
This square of licenses will appear after the first occasion when somebody agrees to accept Power BI as a person. Amid that procedure, this permit square gets appended to your association and a permit is allowed to the client that is joining.
On the off chance that you are obstructing client sign, and nobody has joined, you won’t see this permit square. You can either permit singular client recruits and have one client join, or you can get free licenses through the include membership Office 365 stream which will be discussed straightaway.
Once the Power BI (free) permit square is accessible, you can appoint those licenses to your clients. For more data about how to relegate licenses, see Assign licenses to clients in Office 365.

iii. Getting Power BI Free Licenses

Here, we will discuss how to get free licenses by means of include membership inside Office 365.

1. Explore to the Office 365 administrator focus.
2. On the left route sheet, select Billing > Subscriptions.
3. Select Add memberships + on the correct side.
4. Under Other Plans, drift over the circle (… ) for Power BI (free) and select Buy now.
5. Enter the number of licenses you might want to include and select Check out now or Add to a truck.

Let’s revise How to Add Power BI Filter in Report?
Note – You can include more at a later date if necessary.

1. Enter the required data in the look at a stream.

There is no buy when utilizing this approach, in spite of the fact that you should either enter your charge card data for charging or be invoiced.
On the off chance that you choose later that you need to include more licenses, you can return to Add memberships, and select Change permit amount for Power BI (free).
You would now be able to dole out those licenses to your clients. For more data about how to relegate licenses, see Assign licenses to clients in Office 365.

iv. Empower, or incapacitate, singular client, join in Azure Active Directory

As an executive, you can empower, or debilitate, singular client recruits as a component of the Azure Active Directory (AAD). In the event that you know how to use the AAD PowerShell summons, you can empower, or handicap, specially appointed memberships yourself. Take in more
The AAD setting that controls this is AllowAdHocSubscriptions. Most occupants will have this setting set to genuine, which implies it is empowered. On the off chance that you gained Power BI through an accomplice, this might be set to false as a matter of course, which implies it is handicapped.

1. You have to first sign into Azure Active Directory utilizing your Office 365 certification. The main line will incite you for your accreditations. The second line interfaces with Azure Active Directory.

$msolcred = get-qualification associate msolservice – certification $msolcred

1. When you are marked in, you can issue the accompanying charge to perceive what your occupant is as of now arranged for.

Get-MsolCompanyInformation | fl AllowAdHocSubscriptions

1. You would this be able to charge to empower ($true) or debilitate ($false) AllowAdHocSubscriptions.

Set-MsolCompanySettings – AllowAdHocSubscriptions $true
Follow this link to know How to Install Power BI Apps?

b. Power BI Pro

Power BI Pro is a paid license that empowers more highlights. Pro licenses are for a group that needs to share and team up with others to settle on information-driven choices. Each colleague making or review shared Power BI content needs a Pro to permit except if the substance is related with a committed limit utilizing Power BI Premium.

Power BI Free Vs Pro Tutorial –  Power BI Pro Preliminary Plans

These highlights require a Power BI Pro permit:

• Break down information in Excel or Power BI Desktop – Use Excel or Power BI Desktop to see and connect with a dataset distributed in Power BI.
• Offer dashboards and team up with workspaces – Power BI workspaces encourage cooperation with associates on dashboards, reports, and datasets.
• View shared substance – Pro clients can see dashboards and reports that are imparted to them, cooperate with dashboards and reports that are shared with them, and re-share dashboards and reports that are shared with them (if permitted). Be that as it may, a Pro client can’t alter these dashboards or reports.
• Incorporate substance with Microsoft Teams – You can include a Power BI tab in a Microsoft (MS) Teams channel. MS Teams naturally identifies every one of the reports in the workspace. For more data, see Power BI collaborates with Microsoft Teams.

Let’s revise Power BI Gateway – Types, Working, How to Utilize

i. Power BI Pro 60-day Preliminary

After you have agreed to accept your free record, you can alternatively attempt Pro free for 60 days. You will approach the majority of the Pro highlights for the span of the preliminary. Pro has every one of the highlights of the free form of Power BI, and extra sharing and joint effort highlights. For more data, see Power BI Pricing. To attempt a 60-day free preliminary of Power BI Pro, sign into Power BI, and attempt one of these Power BI Pro highlights.

• Make a workspace
• Offer a dashboard

When you attempt any of these highlights, you will be provoked to begin your free preliminary. You can likewise make utilization of it by setting off to the apparatus symbol and choosing Manage individual stockpiling. At that point, select Try Pro for nothing on the right.
At that point, you can choose to Start preliminary.
Note – Clients exploiting this in-item Power BI Pro preliminary don’t show up in the Office 365 administrator entry as Pro Trial clients (they show up as Power BI free clients). They will, in any case, appear as Pro Trial clients in the oversee stockpiling page in Power BI.
Note – On the off chance that you are an IT Administrator wishing to secure and convey Power BI preliminary licenses to numerous clients in your association without having singular clients acknowledge preliminary terms exclusively, you can agree to accept a Pro membership preliminary. You should be an Office 365 Global or Billing Admin or make another inhabitant agree to accept an administrator preliminary. For more data, see Purchasing Power BI Pro.
When you are in the administration, you would then be able to check that you have a Pro preliminary record by setting off to the apparatus symbol and choosing Manage individual stockpiling.
Let’s read about Power BI Query

ii. Membership Preliminary in Office 365

You can get Power BI Pro as a preliminary for your association. When you have the membership, you can dole out Pro licenses to your clients. For more data about how to allocate licenses, see Assign licenses to clients in Office 365.
Note – There is a point of confinement of one hierarchical preliminary for each inhabitant. This implies on the off chance that somebody has effectively connected the Pro Trial to your inhabitant, you can’t do it once more. On the off chance that you require help with this, you can contact Office 365 billing support.
Take after these means to get a preliminary membership in Office 365:

1. Explore to the Office 365 administrator focus.
2. On the left route sheet, select Billing and after that tap on subscriptions.
3. Select Add memberships on the correct side.
4. Under Other Plans, drift over the oval (… ) for Pro and select Start free preliminary.
5. Select Try now on the affirm your request screen.
6. Select Continue on the request receipt.

So, this was all about Power BI Free vs Pro (Paid) Tutorial. Hope you like our explanation.

In this article, we will shed some light on the roles and responsibilities of a Power BI Developer. Skilled professionals as Power BI developers are highly in demand by the companies worldwide. Here, we will explore this job title further and learn about the basic requirements for this job and the roles and responsibilities of a Power BI developer.

Basic Requirements for a Power BI Developer

Here are some general background requirements for the position of a Power BI developer:

• BS/MS in Computer Science or Information System. Besides that, one needs to have considerable work experience in similar fields.
• Experience of 5+ years in data preparation, data gateway and data warehousing projects.
• Experience of 5+ years and familiarity with Microsoft Business Intelligence Stack having Power BI, SSAS, SSRS, SSIS.
• 3 to 4 years of experience working with a self-service tool, preferably Power BI or Tableau.
• Familiarity with JavaScript, CSS, and other JavaScript libraries.
• Should be familiar and experienced in SQL.

Gain Expertise in the database query language with 40+ Free Tutorials on SQL

Roles and Responsibilities of a Power BI Developer

The main roles and responsibilities of a Power BI developer are discussed below:

• Power BI development and administration.
• Building Analysis Services reporting models.
• Developing visual reports, dashboards and KPI scorecards using Power BI desktop.
• Connecting to data sources, importing data and transforming data for Business Intelligence.
• Excellent in analytical thinking for translating data into informative visuals and reports.
• Able to implement row level security on data and have an understanding of application security layer models in Power BI.
• Proficient in making DAX queries in Power BI desktop.
• Expertise in using advance level calculations on the data set.
• Responsible for design methodology and project documentation.
• Able to develop tabular and multidimensional models that are compatible with warehouse standards.
• Adept in developing, publishing and scheduling Power BI reports as per the business requirements.
• Able to properly understand the business requirements and develop data models accordingly by taking care of the resources.
• Should have knowledge and experience in prototyping, designing, and requirement analysis.
• Should have knowledge and skills for secondary tools such as Microsoft Azure, SQL data warehouse, PolyBase, Visual Studio, etc.
• Able to integrate Power BI reports into other applications using embedded analytics like Power BI service (SaaS), or by API automation. Also, one must be experienced in developing custom visuals for Power BI.

One probable reason why you are keen on learning Power BI is that you want to make a career in Power BI. You might be having a lot of questions to be sure whether you are thinking in the right direction or not? Well, worry no more, we will provide you complete information on Power BI Career Opportunities, along with their salaries and a complete overview of scope in Power BI.

Before diving into Power BI career prospects, let’s have a quick glance of Microsoft Power BI.

What is Microsoft Power BI?

Microsoft Power BI is a suite, which is a collection of Business Intelligence Tools such as software services, apps and data connectors. It is a cloud-based platform used to consolidate data from varied sources into a single data set.

These data sets are used for data visualization, evaluation, and analysis by making shareable reports, dashboards, and apps.

Microsoft offers three types of Power BI platforms:

• Power BI Desktop (Desktop Application)
• Power BI Service (SaaS i.e. Software as a Service)
• Power BI Mobile (for iOS and Android devices)

Become a Power BI Expert by completing the Power BI Tutorial Package by DataFlair

Microsoft Power BI Market Share

Power BI is a leader among other BI tools. It proves to be an efficient and user-friendly tool for data analysis. It enables users to consolidate data from multiple sources, make interactive dashboards, evaluate data, create informative reports and share it with other users.

Thus, out of all the existing Business Intelligence Companies in the market, Microsoft Power BI has a share of approximately 6.0%. As of 2019, a total of 17,393 companies are using Microsoft Power BI as their BI software. In the infographic shown below, you can also see the market share of other competitors such as Tableau, Congos, QlikTech, etc.

Source: enlyft

Why use Power BI

Power BI is a leading BI tool in today’s time. It offers a ton of business intelligence and data analysis tools. We have enlisted some reasons for why you should use Power BI for data analysis in your firm.

• Easy-to-use
• Multiple source connectors (more than 70 data connectors)
• Cheapest/ most inexpensive solution
• Interactive visual dashboards
• Easily accessible from anywhere
• Data sharing and collaboration
• Natural language query

Are you aware of the Latest Power BI Features? If not, then you must check the article.

Power BI Career Opportunities

First, we’ll look at the most searched query, that is, the earnings of different job profiles in Power BI:

Average Salaries for Different Job Roles

Here, we have provided the average salaries (per annum) based on different job roles in Power BI. The average salary of a Power BI professional is Rs. 5,82,000.

• Power BI Data Analyst – Rs. 4,42,864
• Power BI Developer – Rs. 4,78,587
• Power BI Software Engineer – Rs. 4,42,373
• Power BI Analyst – Rs. 4,94,000
• Senior Software Engineer – Rs. 7,85,636
• Senior Business Intelligence (BI) Analyst – Rs. 9,28,556
• Power BI Business Analyst (IT) – Rs. 3,93,054

Top Companies using Power BI

Now let’s have a look at some top companies using Microsoft Power BI worldwide are:

• Rolls-Royce Holdings PLC (UK)
• Kraft Heinz Co (USA)
• Conde Nast (USA)
• Dell (USA)
• Meijer (USA)
• Hospital Montfort (Canada)

Top Industries using Power BI

Power BI is used in varied types of companies that belong to different kinds of industries such as computer software, IT, healthcare, etc. In the image given below, we have graphically represented the number of companies using Power BI in different types of industries. As it can be very clearly seen, about 24% of the total number of companies considered belong to computer software and IT sector.

Top Countries using Power BI

In this section, we will provide you with the country-wise statistics of companies using Power BI. The country with the most jobs for Power BI professionals is the USA. The USA serves about 54% of the total number of companies considered. It is followed by the UK having 11% of the total companies using Power BI.

Distribution of Companies using Microsoft Power BI

In this section, we’ll see how the companies using Power BI gets distributed over a range of employee size and revenue bands.

1. Based on Employee Size

The companies using Microsoft Power BI are divided into three main categories based on employee size. Small (<50 employees), Medium (50 to 1000 employees) and Large (>1000 employees).

Most of the companies using Power BI i.e. 43% fall under the medium employee size.

2. Based on Revenue

Another way to study the distribution of companies using Power BI is to base it on the revenues made by a company. Basing our distribution on revenue generated per year, we can broadly classify companies in three categories. Small (<$50 Million), Medium (between $50M and $1000M) and Large (>$1000M). 46% of total companies using Power BI are small, 27% large and the remaining 19% are medium.

Power BI Career Trends in India

India is the third-largest country in providing customers that are using Microsoft Power BI. Have a look at the education, salary, location, and companies using Power BI in India.

1. Education Required

To work as a Power BI professional, you need to have at least one of the degrees given below.

• B.Tech/B.E.
• BCA
• M.Tech
• MCA
• BCA
• MS
• MBA

2. Job Locations

The companies recruiting Power BI professionals are spread across India. In the list given below, you can find the top cities or locations in India where you might land up as a Power BI professional.

• Bengaluru/ Bangalore
• Delhi/ NCR
• Gurgaon
• Hyderabad / Secunderabad
• Chennai
• Pune
• Mumbai
• Noida

3. Salary

Although, the average salary for Power BI professional is approximately Rs. 5, 82,000/year. Different ranges of salary in which companies recruit Power BI professionals based on experience and skill are as follows:

• 0-6 Lakhs (entry-level professional)
• 6-15 Lakhs (mid-level professional)
• 15-50 Lakhs (senior-level professional)

Top Companies using Power BI in India

The companies listed below are few of the top recruiters of Power BI professionals in India.

• Accenture
• WNS
• Hexaware Technologies
• Ernst & Young
• Capgemini
• Dell International
• Wipro BPS
• Deloitte
• Sony
• Syngene International
• Infosys BPO
• HCL Technologies

Power BI Career Trends in USA

The USA is the largest customer base for Microsoft Power BI. It generates the greatest number of jobs for Power BI professionals followed by the UK. Let us gain some insights into the US market for Power BI.

1. Job Locations

As you can tell from the list provided below, the Power BI recruiters are spread evenly across the country. You can find most of the companies looking for skilled Power BI professionals in the eastern states or western such as the Seattle area. All the other regions offer decent opportunities.

• New York, NY
• Chicago, IL
• Seattle, WA
• San Francisco, CA
• Washington, DC
• Houston, TX
• Atlanta, GA
• Boston, MA
• Dallas, TX
• Austin, TX
• Redmond, WA
• Denver, CO
• Los Angeles, CA
• Bellevue, WA

2. Experience Levels

The companies in the USA recruit and pay Power BI professionals on three levels of expertise. The salaries vary as per your experience level.

• Entry Level
• Mid Level
• Senior Level

3. Salary Estimates

These are the salary estimates of a Power BI professional in the USA. The salary range depends on your experience level, expertise, and qualification.

• $35,000 (Rs.24,06,180.00)
• $52,100 (Rs.35,81,770.80)
• $72,000 (Rs.49,49,856.00)
• $80,900 (Rs.55,61,713.20)
• $100,600 (Rs.69,16,048.80)

Top Companies using Power BI in the USA

The companies listed below are few of the top recruiters of Power BI professionals in the USA.

• PosiGen LLC
• Amazon Web Services, Inc.
• Redwood
• VizExplorer
• Wyzant
• Pro Star Service LLC
• Granicius Inc.
• Saxony Partners
• Streamline Recon LLC

Power BI Career Trends in UK

After studying the job trends in the USA and India, let us have a look at the career trends in the UK.

1. Job Vacancy Trend

The graph given below shows the job vacancy trends for Power BI as of May 2019. Looking at this chart, we can be certain of constantly increasing job opportunities in the UK for Power BI professionals.

2. Salary Trend

The graphs given below show a salary trend for jobs citing Power BI in the UK. The average salary falls between the range of £40,000 to £50,000.

UK Salary Histogram

Salary Trend in UK

Source – ITJobsWatch

Future of Power BI

Power BI occupies a place in the “Leader” quadrant of Gartner’s Magic Quadrant 2019 Business Intelligence. With a brand name Microsoft backing it up, Power BI has seen continuous growth in its customer base since its advent in 2015. This is because it proved to be a convincing tool by providing users with lots of different tools such as Power Query, Power Pivot, Power Maps, Power View all in a single solution. Also, users have the advantage of using data transformation and visualization capabilities of Power BI with Microsoft Excel.

As far as the scope in Power BI is concerned for the coming years, it will continue to be a leading BI tool among its competitors like Tableau, Qlik Sense, etc. If you like to work with data, create graphs/charts/visualizations, analyzing reports, discovering insights, etc, you can always have Power BI as your career path.

With a current customer base of about a million people worldwide, Power BI is a promising tool if you plan on making it your career working on positions like Power BI Developer, Power BI Admin, Power BI Analyst, Power BI Consultant, etc.