Paul Turley's SQL Server BI Blog
sharing my experiences with the Microsoft data platform, SQL Server BI, Data Modeling, SSAS Design, Power Pivot, Power BI, SSRS Advanced Design, Power BI, Dashboards & Visualization since 2009
Today in Vancouver, British Columbia, at the SQL Saturday #198; I presented a session titled “Data Visualization Choices”. As promised, my slide deck is available for download here.
This is the first draft of the session I’m preparing for the PASS Business Analytics Conference coming up on April 11-12 in Chicago. I’ll have another update for that conference.
DevOps isn’t difficult to implement for small and medium-scale projects, and simple things like managing version control in a code repository can save hours of lost time. Organization who are accustomed to managing large application development initiatives might expect to have a fully automated build and deployment process in concert with an Agile delivery process, managed with specialized tools like Jira, GitHub and Azure DevOps.
Power BI is architected to consume data in a dimensional model, with narrow fact tables and related dimensions. Introducing a big, wide table in a tabular model is extremely inefficient. It takes up space and memory resources, impacts performance, and complicates measure coding. Flattening records into a flat table is one of the worst things you can do in Power BI and a common mistake made by novice Power BI users.
Table partitioning has long been an important task in semantic model design using SQL Server Analysis Services. Since SSAS Tabular and Power BI models are built on top of the SSAS architecture, the pattern of partitioning remains the same as it has been for twenty years. However, the specific methods for implementation have been fine-tuned and improved. The reasons for partitioning large fact tables mainly include:
Improve refresh speed,
Prevent reloading historical records,
Capture updated history,
Reduce database resource load
You don’t have to have massive tables to benefit from partitioning. Even tables with a few hundred thousand records can benefit from partitioning, to improve data refresh performance and to detect source data changes. There is little maintenance overhead, so the benefits usually outweigh the cost, in terms of effort and management.
When all else fails, you can always call your favorite shop and ask
what pizza deals they are offering. Online coupons for pizza often have coupons codes that you have type in when you order a pizza from a pizzeria’s website. It is necessary for us to figure out effective ways to solve this tough trouble.
Hmm is anyone else experiencing problems with the pictures on this blog loading?
I’m trying to find out if its a problem on my end or if it’s the blog.
Any responses would be greatly appreciated.