Microsoft Power BI – The Data Community

What is OneLake Catalog?

Microsoft Fabric OneLake Catalog is the next generation, enhanced version of the OneLake Data Hub. It provides a complete solution in a central location for team members (data engineers, data scientists, analysts, business team members, and other stakeholders) to browse, manage, and govern all their data from a single, intuitive location. It provides an intuitive and efficient user interface and truly simplifies and transforms the way we can manage, explore, and utilize content in Fabric. Usage is contextual and it has unified all Fabric item types (including Power BI items) and expanded support to all Fabric item types, integrating experiences, and providing detailed views of data subitems. It is a great tool.

Our team at work recently started using the Power BI platform. We are just getting going but I am already loving this tool. Our current enterprise BI platforms are Qlik and OBI (Oracle Business Intelligence), however, Power BI has has gained significant traction in business teams over the last couple years where it used for departmental reporting and analysis.

I see why the business teams love this tool and am excited about bringing it into our portfolio of tools for delivering analytic solutions across the company. These are some of the reasons I like Power BI:

First and foremost, we have not yet come across anything that we currently do in Qlik or OBI that we will not be able to do in Power BI. This was very important.

Power BI has a very intuitive and well laid out interface. You can easily switch between the visualizations, the data, and the data model. And within each of those tabs, you easily navigate using the well-placed objects and menu items. I found the interface easy to get accustomed to.

You can connect to just about any data source. The list is long. It seems the only source missing is an alien database on Mars. 🙂 I am kidding, but I did not find a native connector for Informix – the most uncommon database that we currently have as a source, but of course, ODBC and JDBC are available for those scenarios. Take a look.

and there are many more!

Some notable connectors are SQL Server Analysis Services, PostgreSQL, Amazon Redshift, Google BigQuery, Snowflake, various Azure data sources, Salesforce, Spark, GitHub, Databricks, and many more.

There are many awesome features for handling Excel data. And although we try to avoid Excel data as a source, it’s just not possible at times, and sometimes it makes sense to use those sources. However, the Power Query functionality allows users to perform ETL tasks on any data from any source.

Power BI has many built-in visualization options.

And you have the ability to “get more” from the marketplace.

Data modeling in Power BI is based on a methodology that our team is very familiar with: Dimensional Modeling, also known as, Star-Schema Modeling. And this is a proven method that works for efficient analytic solutions. In Power BI, it is also easy to create relationships between tables, change data types, and build hierarchies.

Within the data models, you can also use a versatile language called DAX (Data Analysis Expressions) to manipulate data, filter data, build measures, and more. I find that what’s possible with DAX brings Power BI into a whole other tier of flexibility compared to other tools. There is a bit of a learning curve for DAX, but you can start by focusing on a few key functions, and then expand your knowledge over time.
As you would expect in any modern BI platform, the security features in Power BI provide for object-level and data-level security. We have set up some simple security scenarios so far and it was straightforward. We will be digging more into setting up some more complex security scenarios soon and will report on that experience.
Data profiling features are built into Power BI, which may save you some time from having to jump into another query tool to profile your data.
Along with some standard analytic features, such as TopN, conditional formatting, and aggregate functions, Power BI also offers AI visuals, R and Python visuals, and advanced algorithms (such as key influencers and outliers) are available. I can foresee us using these features in the future.
Integration options with Office 365, SharePoint, and Teams.

Power BI is a great platform for one of the most significant trends in analytics – that is, users clamoring for Self-Service Analytics. With the ability to easily secure and share Power BI datasets, and users able to easily connect and use that data with an intuitive, optional code, tool that they may already have exposure to, it will be easier to implement self-service solutions. There are also some cool features for report consumers, such as personalization of visuals and mobile view.
A company called P3Adaptive delivered an awesome training for us, but there are tons of free resources available for learning. A good place to start is the Power BI lessons on Microsoft Learn – Power BI. And then, sign up for Dashboard in a Day (DIAD), a free one-day instructor-led training. You can find and register for DIAD classes here: Microsoft Events – DIAD
There are reasons why the Power BI platform has been at the top of the “Gartner Magic Quadrant for Business Intelligence and Analytics Platforms” for the last 3 years. It has a lot going for it and the company seems to be aggressive about continuous improvement.