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How to Create Power BI Time Series Chart
Business Intelligence
Power BI Time Series Graph

How to Create Power BI Time Series Chart?

2. Power BI Time Series Graph

Today we’ll coordinate the information representation control in Power BI to the ARR in R Programming. Each time I see one of these posts about information representation in R, I get this tingle to test the breaking points of Power BI.
Today around evening time I read a post about plotting time series in R utilizing Yahoo Finance information by Joseph Rickert on the Revolution Analytics blog. In his blog, he depicts, in its most straightforward shape, how he gets stock information from the Yahoo Finance API and plots it on a diagram.
Do you know about Power BI Data Category?
Sounds like something Power BI can do!

Power BI Time Series Graph

Power BI Time Series Graph

He at that point goes ahead to depict making the graph intuitive utilizing extravagant R enchantment.

Power BI Time Series Graph

The sample of Power BI Time Series Graph

We should separate what we’re seeing here.

  • Information for IBM and LNKD stock.
  • Line chart.
  • Mouseover legend.
  • Date extend selector.
  • Intuitive HTML introduction.

3. How to Create Time Series Line Chart in Power BI?

Following are the seven steps to make Power BI Time Series Charts:

a. Bring the Information

With anything Power BI, the initial step is getting the information.
In his blog, Joseph posts the accompanying connections as his sources
IBM Stock information: http://genuine
Linkedin stock information: http://genuine
Opening these in a program downloads a CSV document. Be that as it may, we need to have the capacity to open the information in the favour R path with the factors in the URL. This additionally empowers us to effectively change the time frame later on.
Bringing in this information in Power BI is done by means of the “Internet” information source.

Power BI Time Series Graph

Bring the Data

In the following, excessively expansive exchange box, with a little information box we enter our first URL.

Power BI Time Series Graph

Step.1 Power BI Time Series Graph – Bring the Information

Squeezing “alright” gives us the accompanying discourse box.

Power BI Time Series Graph

Power BI Time Series Chart – Bring the Data

The “Alter” catch will give us the Power Query screen which gives us a ton of alternatives to alter our current information or even make new highlights in our dataset. To rival the capacities of a particular instrument like R we’ll have to utilize the maximum capacity of Power BI.
So squeeze that “Alter” catch and after that import the following dataset too utilizing a similar technique.
You should wind up having 2 datasets stacked, seeing the underneath screen.

Power BI Time Series Graph

Power BI Time Series Graph – Bring the Data

b. Clean the Information

As you may have seen, the qualities were foreign made as though the stock was worth millions to billions. I’m certain IBM and LinkedIn will be upbeat to hear this. Nonetheless, you may have seen that stock is normally justified regardless of a few dollars for little organizations to just several dollars for the best organizations.
I’m feeling that the information may show up effectively for you, contingent upon your region. The period versus comma decimal problem is something average for Belgium.
To work around this issue in our information import we’ll make the accompanying strides.
Change over the numerical segments to content

Power BI Time Series Graph

Step.2 Power BI Time Series Chart – Clean the Information

  • Supplant the period by commas.
Power BI Time Series Graph

Power BI Time Series Graph – Clean the Information

  • Change over the decimal segments to a decimal information write.
  • Change over the entire number segment (Volume) to an entire number datatype.

c. Join the Information

To demonstrate both datasets in one outline we have to join the information first.
In any case, to distinguish the joined information in one graph, we’ll have to include a section in both datasets before we go along with them.

Power BI Time Series Graph

Step. 3 Power BI Time Series Graph –  Join the Information

Including a segment is done by means of the suitably called menu thing “Include Column”.
There’s a plenty of decisions here, however, we’ll simply run with “Include Custom Column”.
For each dataset, including a segment called “Organization” and check it as having information for the particular inquiry utilizing an equation as found in this screen capture.

Power BI Time Series Graph

Step. 3 Join the Information

Next, we’ll have to join the 2 datasets.
This should be possible from the home menu utilizing the “Add Queries” thing.

Power BI Time Series Graph

Step. 3 Join the Information

In the wake of squeezing the “Affix Queries” thing, you’ll get the accompanying discourse box.

Power BI Time Series Graph

Step. 3 Join the Information

It advantageously demonstrates to you which dataset you’ve as of now got chose. That way you can astutely pick the dataset that you need to attach to the present one.

Next, you can tap the “Nearby and Apply” catch.

Power BI Time Series Graph

Step. 3 Join the Information

d. Make the Report

Tap the “Report” tab and how about we get the opportunity to work!
5 stages will get you the essential setup:

  • Tap the 3 fields you need
  • Close
  • Organization
  • Date
  • Tap the line graph perception
Power BI Time Series Graph

Step. 4 Make the Report

You’ll see this delightful diagram that you’ll perceive from the first article.

Power BI Time Series Graph

Step. 4 Power BI Time Series Graph – Make the Report

We got our information, we got a line graph and we got our mouse over data. Presently we have to make our date extend selector.
There are a few different ways to actualize this.
Tragically, the cool slider doohickey that R has isn’t one of them.
So what would we be able to do to make a cool date run selector in Power BI?
Power BI empowers us to utilize slicers or even utilize an information perception, similar to a treemap, as a kind of slicer.

e. Adding Highlights to Our Information

We’ll likely need to cut on a year, quarter and month. How about we add the pertinent information to our dataset.
For this, we have to alter our dataset, so we should press the “Alter Query” catch once more.
Including these fields is a breeze, we select a date field and go to the Add Column menu.
From that point we see a standout amongst the most extraordinary choices. We can include distinctive time segments with the snap of a catch.

Power BI Time Series Graph

Step. 5 Power BI Time Series Graph – Adding Highlights to Our Information

f. Adding Custom Highlights to Our Dataset

Adding custom highlights to your dataset should be possible utilizing DAX.
DAX can be the subject for a considerable measure of other blog entries however for a simple begin look at Dustin Ryan’s blog entry on some regularly utilized DAX recipes.
For our little analysis, we don’t have to go this far in any case. So don’t hesitate to investigate or give your recommendations in the remarks or through twitter.

g. Including Slicers

In Power BI you can channel a view, that is one page in a report. There are a few conceivable outcomes to make channels, a slicer is one of them. A slicer is a channel that is available on the report page itself. Like the one in the first R representation. Separating works with information that has a place with a similar question or with inquiries that have a relationship characterized between them.
One of the slicers we’ll make is by utilizing a treemap.
Make a treemap perception and put the quarter name in there like in the screen capture.

Power BI Time Series Graph

Step. 7 Including Slicers

This gives us a very revolting slicer with various hues. We can change these hues by means of the arrangement menu.

Power BI Time Series Graph

Step. 7 Including Slicers

Power BI Time Series Graph

Step. 7 Including Slicers

4. The Result

In the event that you’ve been following the procedure yourself, you most likely saw how quick and simple it is to toy around in Power BI.
Leave a remark in the event that you have an inquiry or experienced an issue. The following is the outcome I got.

Power BI Time Series Graph

Power BI Time Series Graph – Result

On the off chance that you haven’t played around in Power BI yet, simply download the free Power BI Desktop application today and begin with the Power BI Zero to Hero series.
It’s significantly more easy to understand that keeping in touch with a few lines of R enchantment. I’d even contend that it’s a better time!
So, this was all about Power BI Time Series Charts. Hope you like our explanation.

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Introduction to Power BI
Business Intelligence

Welcome to the Power BI tutorial . Before we begin this journey of learning a new BI technology called Microsoft Power BI, we must learn some basics about it. In this introductory tutorial of Microsoft Power BI, we will give you some interesting information and insights on this BI technology. We request you to take some time out and explore this thoroughly as it will act as a building block for learning Power BI technology.

We can confidently presume that not many of you here are not aware of business intelligence and data visualization. Especially in today’s world, where data is the Robin of every business and organization. And, without this Robin, there is no Batman! Data is a treasure of knowledge and valuable information which is used by the ones helming a business to make lucrative and effective decisions at the right time.

“BI is about providing the right data at the right time to the right people so that they can take the right decisions”

Power BI Tutorial

Before diving into the Power BI introduction, let’s have a quick look at Business intelligence (BI). It refers to taking raw data from a data source, transforming it into usable data and utilizing it to make reports and informative graphics for data analysis.

Graphically representing tabular data is known as data visualization. It enables a user to visualize important information through charts, graphs, KPIs, maps, etc. to attain valuable insights just by looking at them. Well Microsoft Power BI is a tool having business intelligence and data visualization capabilities.

Before we begin with this journey of learning a new BI technology called Microsoft Power BI, we must learn some basics about it. We request you to take some time out and explore this Power BI tutorial thoroughly as it will act as a building block for learning Power BI technology.

Power BI tutorial - Introduction to Power BI

Wait! Do you know about Power BI KPI 

What is Power BI?

Power BI is a cloud-based business analysis and intelligence service by Microsoft. It is a collection of business intelligence and data visualization tools such as software services, apps and data connectors.

We can use the datasets imported in Power BI for data visualization and analysis by making sharable reports, dashboards, and apps. Power BI is a user-friendly tool offering impressive drag-and-drop features and self-service capabilities.

Microsoft offers three types of Power BI platforms:

  • Power BI Desktop (A desktop application)
  • Power BI Service (SaaS i.e., Software as a Service)
  • Power BI Mobile (For iOS and Android devices)

Also, we can deploy Power BI on both on-premise and on-cloud platforms.

In the image given below, have a look at the process flow in Power BI.

Process Flow of Power BI - Power BI Tutorial

Why Power BI?

As we learned in the previous section of Power BI tutorial that, Power BI is an umbrella term having several different kinds of services under its tutelage.

  1. There is a cloud-based BI service called Power BI Services used to view and share dashboards.
  2. A desktop-based reporting interface known as Power BI Desktop.
  3. Another useful service is Power BI Embedded that runs on an Azure cloud platform and we can use it for report creation, ETL and data analysis.

Further, let us discuss a few points regarding why Power BI is an important tool in today’s time and why do we need it.

  • Real-time analysis in Power BI can be done by establishing direct connections to the data sources. Also, it keeps data updated to the latest second by data refreshing.
  • You can use custom visualizations from a custom visuals gallery. Custom visuals are divided into many options and categories.
  • You can quickly search for important insights and datasets within your data by using the Quick Insights option.
  • Establish a live or non-live connection to on-premises data sources like SQL Server, and use a secure channel to access data through data gateways. This makes Power BI enterprise-ready as on-premises connections make data transfer secure and the technology scalable and reliable.
  • You can connect to other services through Power BI such as SQL Server Analysis Services (SSAS), Microsoft Excel, etc.
  • Power BI is a new age software using the latest technologies such as HTML 5.0, column store databasescloud computing, mobile apps, etc. This helps in keeping Power BI on the top and popular as it is constantly getting updated with the latest features.

Take a deep insight into Custom Visuals in Power BI

History of Power BI

Power BI is a Microsoft’s product initially released on 11th July 2011. It was originally designed and created by Ron George in 2010, who released it with the name “Project Crescent”. Later in September of 2013, Microsoft changed the name to Power BI and launched it for the public.

This release was a Power BI for Office 365 and had Microsoft Excel add-ins, Power Pivot, Power View, Power Query in it. In later versions, Microsoft added advanced features like natural language Q&A, enterprise-level data security and connectivity, Power data gateways, etc.

Power BI’s first general public release was on July 24th, 2015. As of 2019, Power BI has been officially declared as one of the leading BI tools by 2019 Gartner Magic Quadrant for Analytics and Business Intelligence Platform.

Power BI Features

There are some of the most important and interesting features of Power BI:

  • Visualizations/ custom visualizations
  • GetData (Data sources)/data connections
  • Datasets
  • Dashboards
  • Filters
  • Ad hoc analysis
  • Reports/ ad hoc reporting
  • Trend indicators
  • Online Analytical Processing (OLAP)
  • Navigation pane
  • Natural language Q & A box
  • DAX functions and formula
  • Office 365 app launcher
  • Content packs
  • Authoring interactive reports

You must learn about these features in detail from our separate tutorial on features of Power BI

Power BI Components

Power BI is a business intelligence and data mining software suite which is a collection of different kinds of services by Microsoft. These services play a specific role and work in coordination with each other, to make Power BI function as a whole. In this section of the Power BI tutorial, we will learn about each of these Power BI services or components and their roles.

  • Power Query: We use this service to access, search and transform data from public or local/internal data sources.
  • Power Pivot: This service provides tools to model data taken from the in-memory data source to use it for analytics.
  • Power View: This service has many tools to graphically represent data using visuals and use them for analysis.
  • Power Map: It comes with tools and capabilities to visualize Geo-spatial data or information in the 3D model in a map. You can use these maps in a Power BI report.
  • Power BI Desktop: It is a companion development tool for Power View, Power Query, and Power Pivot. You can import data from a data source, prepare and transform it and use it in visualizations to create reports in Power BI Desktop.
  • Power BI Website: It is a web platform to view and share Power BI apps or solutions. Using Power BI Website, you can create dashboards from reports, share the dashboards with other Power BI users and slice and dice data within a report.
  • Power Service: The Power Service enables the sharing of workbooks and data views with other users. The data gets refreshed at regular intervals from the on-premises or/and cloud-based data sources.
  • Power Q&A: Using the Power Q&A option, you can search for your data or discover insights by entering queries in natural language. It instantly understands your query and returns relevant results.
  • Power BI Mobile apps: Business users view and interact with the reports and dashboards published on a cloud service through mobile hosted Power BI instances. Android, Windows and iOS mobile devices support the Power BI mobile apps.
  • Data Catalog: The Data Catalog option offers the capability to search and reuse queries.
  • Data Management Gateway: This component manages the periodic data refreshes, data feed viewing and table exposing.

Power BI Architecture

To have a better understanding of Power BI, we can divide the architecture into three parts or phases:

Power BI Architecture - Power BI Tutorial

1. Data Integration

In Power BI, we can import data from different kinds of data sources in different formats. In the data integration step, Power BI brings data together (extracted) from different data sources and converts it into a standard format. After data is integrated into Power BI, it is stored in a common storage area known as the staging area.

2. Data Processing

Once Power BI integrates and stores data at a secure place, the raw data requires some processing. Several processing or cleansing operations transform the raw data such as removing redundant values, etc. Later, we apply relevant business rules on the processed data that transforms it according to our business needs. This transformed data is loaded into the data warehouses. This completes a full process of ETL.

3. Data Presentation

In this final phase, the processed data moves from the warehouse and goes into the Power BI platforms like Power BI Desktop to create reports, dashboards, and scorecards. Power BI offers a wide range of visualizations. We can also import custom visualization from the marketplace. From the report development platforms, we can publish the reports on the web or mobile apps to share it with other business users.

Get a thorough understanding of Power BI Architecture

Users of Power BI

Power BI users are categorized into four sections according to the purpose of the usage of Power BI. These four types of users are Analysts, Business users, IT professionals and Developers. Let’s learn some more about them.

1. Analysts

Analysts use Power BI to develop reports, dashboards, data models and study them to discover valuable insights in the data. Power BI offers a wide range of data sources from which an analyst can extract data, make a common dataset, cleanse and prepare that data to make reports and conduct analysis.

2. Business Users

The business users are the common users who study the reports and dashboards available to share with them on the Power BI website or mobile app. Business users remain updated with the latest information which helps in taking important decisions in time. They can also set an alert notification for any change or abnormality in data (if occurs).

3. IT professionals

The IT professionals are mainly concerned with the scalability, availability, and security of data. They also centrally manage all the Power BI services and users.

4. Developers

Developers are responsible for all the technical work. Their key roles are to create custom visuals to be used in Power BI, embedding Power BI into other applications, creating reports, etc.

You must definitely learn to apply Filters in Power BI Reports

Data Connections in Power BI

There is a plethora of data sources from which you can extract data into Power BI. You can connect to data files on your local system, Excel files, Azure SQL Database, Facebook, Google Analytics, Power BI datasets, etc.

You can connect to cloud-based sources, on-premises data sources using gateways, online services, direct connects, etc. We have listed some commonly used data sources below.

  • File: Excel, Text/CSV, XML, PDF, JSON, Folder, SharePoint.
  • Database: SQL Server database, Access database, Oracle database, SAP HANA database, IBM, MySQL, Teradata, Impala, Amazon Redshift, Google BigQuery, etc.
  • Power BI: Power BI datasets and Power BI dataflows.
  • Azure: Azure SQL, Azure SQL Data Warehouse, Azure Analysis Services, Azure Data Lake, Azure Cosmos DB, etc.
  • Online Services: Salesforce, Azure DevOps, Google Analytics, Adobe Analytics, Dynamics 365, Facebook, GitHub, etc.
  • Others: Python script, R script, Web, Spark, Hadoop File (HDFS), ODBC, OLE DB, Active Directory, etc.

Deep dive into 100+ Spark Tutorials to master the cluster computing platform

Power BI Pricing

Now, we are sure you must have started liking Power BI after learning what all it has to offer. And so, you would also want to know its pricing and licensing costs. We will let you know about the prices of different versions with their features in this Power BI tutorial. Microsoft has put out three pricing plans for Power BI:

  • The basic version, Power BI Desktop is free of cost and includes tools for data visualization, data preparation, data modeling, data cleansing and publishing reports to Power BI Service.
  • Power BI Pro is available at a subscription price of $9.99 per user per month. You can try a 60 days free trial before purchasing the subscription. This plan for Power BI Pro includes tools for data collaboration, a 360 real-time view for dashboards, data governance, and the freedom to publish reports anywhere.
  • The Power BI Premium is available at a price of $4,995 per month for one dedicated storage resource and cloud computing facility.

Must Learn – How to Create Dashboard in Power BI

Companies using Power BI

Power BI is a relatively new business analytics software in the market and is gaining popularity very fast. It has gathered a huge customer base worldwide already and is rapidly expanding. Here is a list of a few big names that use Power BI as their business analysis software:

  • DELL
  • Capgemini
  • Nuevora
  • Accenture
  • Agile BI
  • Data Bear

Power BI Case Study on Rolls-Royce

In this section, we will briefly walk through a case study of Power BI. This will help us understand the role of Power BI in a real-life scenario. The case in the spotlight here is Rolls-Royce. This 20-year-old company needs no introduction.

As of this year, it is making more than 13,000 engines for commercial aircraft used around the world. This speaks for its massive and ever-increasing customer base. Now let us move further and see the challenges the company faced and how Power BI proved to be useful.

The problem

The most basic challenge of the company was to optimize maintenance costs, operational costs, fuel expenses, etc. This is only possible when the company is able to record, access and analyze the data produced by all the systems and equipment of the aircraft. With the advancing technology, the systems can record more and more signals which are the data from different aircraft sensors. This has resulted in a constant increase in data volumes. So, the company needed a good data management and analysis system that filter important signals or data and use them to generate insights.

In addition to this, Rolls-Royce launched a customer service and maintenance model known as “TotalCare Services”. It was a very successful initiative that involved engine maintenance services for the customer. For this also, the company needed proper insights into data so that they can establish a bond with their customers.

The change

Rolls-Royce chose the Microsoft Azure platform and Power BI to manage and analyze terabytes of data coming from the engines and maintenance systems. With the help of Microsoft Azure, the company was able to aggregate data from varied locations and sources. And with the help of Microsoft Power BI, they were able to carry out analysis on the extracted data.

With Power BI, they designed and created dashboards and reports having informative visuals and charts. Earlier, creating informative reports to gain insights into data was time-consuming. But with Power BI, it is the easiest step in the entire process. Thus, Power BI plays a crucial role in providing valuable insights into data so that the company can focus on improving operational efficiencies and establish long-lasting relationships with their customers.


This brings our introductory tutorial on Microsoft Power BI to an end. We hope it helped you lay a solid foundation about the technology. In the tutorials to come, we will expand on more interesting topics and tools of Power BI.

Next article lined up for you – Pros and Cons of Power BI

Any questions regarding the Power BI tutorial? Share your queries in the comment section.

Stay tuned and happy learning!

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What are the Steps to BI Success
Business Intelligence
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Power BI Desktop April 2019 Feature Summary
Business Intelligence

April is an exciting month for Power BI Desktop! Our April update has major updates across the entire product.  This release adds the ability to define the titles of your visuals and the URLs of your buttons based on DAX expressions, which is only our first step towards making every property of a visual expression-based. You can also now easily link reports within a workspace together with across-report drillthrough support. We have a lot of new connectors this month and several  of our preview connectors are now generally available, including the Power BI dataflows and PDF connectors. Data prep gets some major updates as well with the GA of data profiling and M intellisense.

Here’s the complete list of April updates:





Data connectivity

Data preparation


For a summary of the major updates, you can watch the following video:


Filter pane improvements

Support for full filter pane editing

We’ve now added support for full editing of the new filter pane. You can add and remove fields to filter on, change the filter state, control the visibility of the pane and filter cards, and lock filter cards all within the new filter pane.

Since the new filter pane now has full editing ability, when you are using the preview, you no longer see the old filter pane at all in the visualization pane.

Ability to rename filters

When you’re editing the filter pane, you can now double click the title to edit it. This is a good way to make the filter card names more understandable for your end users.

Filter pane scales with the report page

To maintain proportion between the report page and the filter pane, the new filter pane will now scale with the report page and visuals.

Restrict ability to change filter type

Under the Filtering experience section of the report settings you now have an option to control if consumers of your report can change the filter type. With this setting off, your report consumers won’t have access to the dropdown to switch between the basic and advanced types of filters.

Improved filter pane accessibility

We’ve improved the keyboard navigation for the new filter pane. You can tab through every part of the filter pane and use the context key on your keyboard or Shift+F10 to open the context menu.

Watch the following video to learn more about the filter pane improvements:

Conditional formatting for visual titles

Since the initial release of Power BI, you’ve been able to customize the titles of your visuals, but they’ve always been static text.

Since Power BI reports are interactive, it makes sense that you may want your titles to be dynamic and reflect the current state of the report. You can now use the conditional formatting dialog to change the text of your report based on a DAX expression in your model.

First, you’ll need to create a field in your model to use for your title. For example, here’s an expression that will change based on the filter context the visual receives for the product Brand name. One thing to note is that this field needs to be formatted as text.

 Then launch the conditional formatting dialog by right-clicking the “Title text” area in the property pane card and picking Conditional formatting.

Then in the dialog, select a text field from your model. This can be a column or a measure.

Now the visual’s title will respond to changes in the report.

Once such a title is set, you can re-launch the dialog by clicking the fx button in the property pane or revert to the default using the context menu.

Watch the following video to learn more about conditionally formatting titles:

Conditional formatting for web URL actions for buttons, shapes, and images

You can also use the same expression-bound formatting to make the URLs of your buttons dynamic! It’s set up the exact same way as titles. This can be very useful if you want users to navigate to other webpages with URL parameters based off their current selection.

Over the coming months we’ll be rolling these conditional formatting options out to more properties on more visuals and give you more ways to set the expression. The goal is that you’ll be able to use rules, a measure or enter an expression directly in the dialog and use the result to format any property.

Watch the following video to learn more about conditionally formatting URLs for buttons:


Drillthrough across reports

We are extending our drillthrough feature, which up until now only worked between pages of a single report, to also reference other reports in a given workspace as well. The power of this feature is that you can no easily link up multiple reports. For example, you could create a summary report connected to a slimmed down dataset and set up drillthrough to deep detailed reports.

To set up this experience you’ll need to:

  • Set up a drillthrough target page to be accessed from other reports within a workspace
  • Allow a report to opt into seeing drillthrough pages outside of the report

To set up a drillthrough page so it can accessed from other reports within a workspace, all you need to do is turn on the Cross-report toggle in the drillthrough section of the visualization pane.

After that, all you need to do is enable the Cross-report drillthrough setting for all reports within a workspace that you want to point that cross-report drillthrough page. You can find this setting in the Report settings for the current file section of the Options dialog.

Once you’ve done that, any report can see the cross-report drillthrough pages within its workspace or app. Right clicking in a visual in a report will show the drillthrough page from another report if the fields in the visual match the drillthrough fields setup on the target page. The matching needs to be identical by both table name and column name,  but doesn’t need to be the same dataset.

Watch the following video to learn more about drillthrough across reports:

Key Influencers visual now supports continuous analysis for numeric targets

You can now add numeric fields to the Analyze bucket of the field well and run a continuous analysis and find key influencers that cause that field to increase or decrease. This will work for numeric columns (including calculated columns) but measures are not yet supported.

In order to enable this analysis, you will need to explicitly turn it on after selecting the field to analyze. You can do this by going to the analysis card of the formatting pane and switching the analysis type to continuous instead of categorical.

Behind the scenes the visualization will run a linear regression and rank all the factors that the user selected as potential influencers. It will give insights about how much an explanatory factor increases or decreases the average of the metric being analyzing. In the example above we can see that when Class is Deluxe, the SalesAmount is on average $1.5K higher than when the Class is Regular or Economy.

To learn more about how to set up the key influencers visual and how it works, you can check out our documentation.

Watch the following video to learn more about continuous analysis for the Key Influencers visual:

Python support is now generally available

Thank you for all the great feedback during the preview period! Python is now generally available and can be used to create your models and visuals without needing to enable it.

Partial synonym matching for terms in Q&A

When using Q&A, you can now complete terms even if you only know part of it. Specifically, if you type a word or phrase that is part of a synonym of a field or table, you’ll see the synonym in the list of suggestions.

Watch the following video to learn more about partial synonym matching for Q&A:



We’ve added another new DAX function this month, ALLCROSSFILTERED. This function can be used to remove filters on a table from other tables across direct or indirect many-to-many relationships.



The rainbowGauge partner-developed visual lets report authors create a 3-state gauge with different colors to represent each stage. You can add a min, max, target, and a value and color for each stage to the visual.

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