A definitive guide to turn CSV files into Power BI visuals using Azure

Cloud, Big Data, and Business Intelligence are the three buzz words of the decade. Everyone is talking about them. Everyone wants to do it. But no one tells you how to do it. How do you use the cloud to process your big data and build _intelligence _around it to make _business _decisions? There are multiple answers to that question, and in this guide, we tried to answer that question using Microsoft’s cloud solution (Azure) and Microsoft’s BI tool (Power BI) to get you started in the right direction.

Microsoft Azure is one of the leading providers of cloud solutions, offering an end-to-end set of tools and techniques to ingest, analyze, and consume vast sources and formats of data.

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Caution

Microsoft Azure is a paid service, and following this article can cause financial liability to you or your organization.

Prerequisites

An active Microsoft Azure subscription

How to get an Azure subscription?

The very first step in the journey towards representing data in an easy, digestive, and usable form is recognizing the source and format of the data. Traditionally data professionals used to focus on Extract, Transform & Load (ETL) to load and transform data. The advent of Azure has opened the doorway to process structure-less data on an unlimited and unprecedented scale. This change has shifted the transformation and loading data to Extract, Load & Transform (ELT). The basic principles and steps remain the same; they just follow a different order. A data project in Azure typically involves the following steps:

  1. Ingest: Identify the tools, technologies, and method to load the data
  2. Prep and train: Identify the tools, technologies, and method to transform the data

Followed by two additional steps to analyze and consume the cleansed data

  • Model and serve: Identify the tools and methods to model and analyze the data
  • Consume: Identify the tools and techniques to consume or present the data

In this article, we look at a holistic approach of transforming and loading data in Azure as we move through different phases of ELT until consumption with the aid of an example. To begin our journey, we will:

  • Take publicly available COVID-19 data from GitHub (source)
  • Store the CSV files to Azure Data Lake Storage Gen2 with the help of Azure Data Factory (ingest)
  • Transform and cleanse the CSV files to relational data in Azure Databricks (prep and train)
  • Store the cleansed data in Azure Synapse Analytics data warehouse (model and serve)
  • And finally, present the prepared data in the form of Power BI visuals (consume)

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A definitive guide to turn CSV files into Power BI visuals using Azure
sophia tondon

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Is Power BI Actually Useful?

The short answer, for most of you, is no. However, the complexity and capability of the products could be beneficial depending on what type of position or organization you work in.
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In my effort to answer this common question about Power BI I researched the following:
– Power BI Desktop Gateway
– Syncing on-prem SQL server data
– Syncing SharePoint Online list data
– Syncing data from an Excel workbook
– Building, and sharing a dashboard
– Inserting a Power BI visualization into PowerPoint

To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training

The feature spread above gave me the opportunity to explore the main features of Power BI which break down as:
– Ingesting data, building a data set
– Creating dashboard or reports with visualizations based on that data

In a nutshell Power BI is a simple concept. You take a data set, and build visualizations that answer questions about that data. For example, how many products have we sold in Category A in the last month? Quarter? Year? Power BI is especially powerful when drilling up or down in time scale.
And there are some interesting ways to visualize that data:
However, there are a number of drawbacks to the current product that prevented me from being able to fold these visualizations into our existing business processes.

  1. Integration with PowerPoint is not free. This shocked me.

The most inspiring Power BI demo I saw at a Microsoft event showed a beautiful globe visualization within a PowerPoint presentation. It rendered flawlessly within PowerPoint and was a beautiful, interactive way to explore a geographically disparate data set. I was able to derive conclusions about the sales data displayed without having to look at an old, boring chart.

During the demo, nothing was mentioned about the technology required to make this embedded chart a reality. After looking into the PowerPoint integration I learned that not only was the add-in built by a third party, it was not free, and when I signed up for a free trial the add-in could barely render my Power BI visualization. The data drill up/down functionality was non-existent and not all of the visualizations were supported. Learn more from Power bi online course

  1. Only Dashboards can be shared with other users, and cannot be embedded in our organization’s community on SharePoint.

Folks in our organization spent 50% of their time in Outlook, and the rest in SharePoint, OneNote, Excel, Word, and the other applications needed for producing documents, and other work. Adding yet another destination to that list to check on how something is doing was impossible for us. Habits are extremely hard to change, and I see that consistently in our client’s organizations as well.

Because I was not able to fold in the visualizations with the PowerPoint decks we use during meetings, I had to stop presentations in the middle, navigate to Internet Explorer (because the visualizations only render well in that browser), and then go back to PowerPoint once we were done looking at the dashboard.

This broke up the flow of our meetings, and led to more distractions. I also followed up with coworkers after meetings to see if they ever visited the dashboard themselves at their desk. None of them had ever navigated to a dashboard outside of a meeting.

  1. The visualizations aren’t actually that great.

Creating visualizations that cover such a wide variety of data sets is difficult. But, the Excel team has been working on this problem for over 15 years. When I import my SharePoint or SQL data to Excel I’m able to create extremely customized Pivot Tables and Charts that show precisely the data I need to see.

I was never able to replicate visualizations from Excel in Power BI, to produce the types of visualizations I actually needed. Excel has the ability to do conditional formatting, and other customizations in charts and tables that is simply not possible with Power BI. Because of how generic the charts are, and the limited customization it looks “cool” without being functional.

In conclusion, if you have spare time and want to explore Power BI for your organization you should. However, if you are seriously thinking about how you can fold this product into your work processes, challenge yourself to build a dashboard and look at it once a week. See if you can keep that up for a month, and then think about how that change affected your work habits and whether the data analysis actually contributed value each time. At least half of you will realize that this gimmicky product is fancy, but not actually useful.

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Tableau vs Power BI: Comparing the Data Visualization Tools

In analytics, Tableau is the leading visualisation tool. Its rich analytical features and attention to data details are the reason behind its popularity. Power BI, on the other hand, is preferred by professionals who are more comfortable with Microsoft Office365. The users can connect Excel queries, data models and are able to report to the dashboard.
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While the usage of both these tools might depend on many factors, here is a quick comparison of the two popular tools on various functionalities.

To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training

1. Performance
One of the crucial differences between Tableau and Power BI is that Tableau is an extensible platform which not only provides visualisations but also helps in gaining a better understanding of the data. Both the tools are excellent in visualisation but when it comes to the depth of data, Tableau helps an analyst to dive deeper into the data by performing “what-if” analysis on the data.

2. Flexibility
A user can deploy tableau on-premises, on the public cloud on Microsoft Azure, Amazon Web Services, or Google Cloud Platform, or on Tableau Online. While PowerBI, an upgradation of Microsoft Excel can be said as not so flexible as it serves only as a software-as-a-service model.
Power BI vs Tableau: A Data Analytics Duel - TechnologyAdvice

3. User Interface
Tableau is mainly designed keeping data analysts in mind. The richer analytical capabilities for visualisation helps an analyst gain insight into large datasets. It allows the user to create customised dashboards which can be considered as more of a pro-level. Microsoft PowerBI is simpler than Tableau and offers a better intuitive interface, especially for the beginners. This tool can be used by a coder as well as a non-coder.

4. Visualisation
Power BI focuses on data modelling and offers features of data manipulation and then provides data visualisation while tableau strictly focuses on data visualisation. Learn more from Power BI online course

5. AI-Powered
PowerBI tool with its Microsoft Flow and its AI builder tool can help in building apps with a layer of intelligence. With the advantages of Microsoft AI, the user can prepare data, build machine learning models and gain insights from both structured and unstructured data. On the hand, Tableau is working on natural language capabilities to simplify analytics and help the users who have no prior data analysis experience, known as Ask Data. Recently, Tableau has also announced the beta version of Explain Data, a new AI-powered feature to help users understand the “why” behind unexpected values in their data.

6. Price
PowerBI offers two subscription offerings, Power BI Pro and Power BI Premium. Power BI Pro is priced at .99 per user per month which is a self-service BI where user can collaborate, publish, share and perform ad-hoc analysis. Whereas Power BI Premium is priced at ,995 per month per dedicated cloud compute and storage resource. Here, the user can perform big data analytics, advanced administration and more.

Tableau, on the other hand, offers three subscriptions — Tableau Creator, Explorer, and Viewer. Tableau Creator is priced at user per month and it includes Tableau Desktop, Prep Builder and one creator license of Tableau Server. Tableau Explorer is priced at per user per month where they can explore the trusted data with self-service analytics and the Tableau Viewer is priced at user per month and here the user can view and interact with dashboards and visualisations in a secured way. These pricings are for teams and organisations where multiple users/viewing is required.
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Power BI In Brief – 2020

Every month, we bring you news, tips, and expert opinions on Power BI? Do you want to tap into the power of Power BI? Ask the Power BI experts at ArcherPoint.

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Power BI Desktop – Feature List
More exciting updates for August—as always:

  • Reporting - Perspectives support for Personalize visuals; rectangular lasso-select for data points; additional dynamic formatting support to more visuals
  • Analytics - Direct Query support for Q&A
  • Visualizations - Linear Gauge by xViz; advanced Pie & Donut by xViz; ratings visual by TME AG; toggle switch by TME AG; fdrill down Pie PRO by MAQ Software; ADWISE RoadMap; updates to ArcGIS Maps; extending Admin capabilities for AppSource visuals
  • Template Apps - Agile CRM analytics for Dynamics 365
  • **Data Preparation ** - Text/CSV By Example
  • Data connectivity - Cherwell connector; Automation Anywhere connector; Acterys connector

To get in-Depth knowledge on Power BI you can enroll for a live demo on Power BI online training

Power BI Developer Update
And the updates continue—this time, for developers:

  • Updates in embedded analytics
  • Automation & life-cycle management
  • New API for updating paginated reports data sources
  • Get dataset/s APIs return new additional properties
  • Embed capabilities
  • Persistent filters support for embedding in the organization
  • Phased embedding
  • Control focus behavior for create/clone visual
  • Additional Javascript API enhancements
  • Selected learning resources

Multiple Data Lakes Support For Power BI Dataflows
And if that’s not enough, Microsoft also announced improvements and enhancements to Azure Data Lake Storage Gen2 support inside Dataflows in Power BI. Improvements and enhancements include: Support for workspace admins to bring their own ADLS Gen2 accounts; improvements to the Dataflows connector; take-ownership support for dataflows using ADLS Gen2; minor improvements to detaching from ADLS Gen2. Changes will start rolling out during the week of August 10. Read more on multiple data lakes support in Power BI dataflows.

To get more knowledge of Power BI and its usage in the practical way one can opt for Power bi online training Hyderabad from various platforms. Getting this knowledge from industry experts like IT Guru may help to visualize the future graphically. It will enhance skills and pave the way for a great future.

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