Posts by Mike Diehl
I’ve been digging into Microsoft Fabric recently – well overdue, since it was first released about a year ago. At the recent SQL Saturday Atlanta event I attended in early February 2024, I took the opportunity to learn from the sessions and speakers that were discussing aspects of Fabric. Shabnam Watson, John Kerski, Stephanie Bruno, and Stacey Rudoy were some of the speakers I learned from. They showed me many other resources for learning more about Fabric, including a great blog by Sandeep Pawar, also known as https://fabric.guru/ I’ve been thinking about some of my clients and how Imaginet has architected their data analytics ecosystems, or how I might … Read more
Recently, I had the opportunity to attend SQL Saturday Atlanta (BI edition), a free annual event for data professionals and enthusiasts held in Alpharetta Georgia. I spoke at this conference a year ago, and I was glad to have one of my abstracts selected so I could return this year. SQL Saturdays are a great opportunity for me to volunteer and give back to the community with my experience, but also for me to learn from others. New speakers are encouraged, and the Data Speaker Community is a worldwide family of friends where everyone is welcomed. Keep your eye on https://sqlsaturday.com/ for events near you or calls for speaker … Read more
Have you been hearing the buzz about Microsoft Fabric? The Data Engineering and Business Intelligence team at Imaginet has been watching with interest the development of Fabric since it was announced in March 2023. As data professionals with deep expertise in the Microsoft stack of data analytics products, we’ve already been using many of the pieces of Fabric and we’re excited to see how they are evolving. Microsoft Fabric brings together several data products into a more unified experience, including Azure Synapse for querying data sources, Azure Data Factory for performing ETL processes (Extract, Transform, Load), and Power BI for showing data in dashboard or paginated forms. These products have … Read more
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We have a lot of discussions with clients about a desire to do “better reporting”. They have been using Power BI but feel they now need a data warehouse to create reports that will give them all the info they need. Fundamentally, organizations often have an analytics problem, one for which a data warehouse forms part of the solution, however, the complexities lie in the data. Often organizations have already applied significant expertise to the problem, and while they understand a lot about the problems, they have reached some difficult data challenges requiring external expertise.
Common pain points experienced when building Business Intelligence (BI) data assets and how Imaginet uses DevOps to mitigate them.
If you’re a Business Intelligence developer, have you experienced some of these challenges?
Data engineering is the work that brings data from one or more sources and shapes it, validates it, cleans it, correlates it, and (often) stores it, and it’s a lot of what we do at Imaginet.
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