What is Data Modeling, exactly?
Some might say Data Architecture. Some might say Data Preparation. Some might say Data Consolidating. Some might say it’s creating Data Relationships. It’s really all of those things. Quite simply, Data Modeling is organizing and preparing your data in the best possible way for consumption. The problem is, doing that is not always simple!
Data Warehousing
If your organization already has a Data Warehouse (well organized and structured clean data), that’s terrific! But if you don’t, a Data Warehouse is not always the Field of Dreams. Data Warehouses are expensive to create, and with new technologies like Dataflows, you may be able to avoid the potentially expensive endeavor.
AI.BI OnDemand can help your organization with:
- Data Warehousing
- Dataflows
- Datasets
- Azure Data Lakes
Check out Microsoft’s Adam Saxton in his YouTube video on Dataflows.
ETL Methods
Getting Data ready for consumption in a BI solution requires the process of Extracting, Transforming and Loading (ETL) the data into a Data Model. What used to require SQL skills is now a drag-and-drop, self-service capability.
Introducing…the Citizen Data Scientist! That could be you! This refers to any business user performing analyses that a few years ago would have required the skills of a full-time, highly experienced data scientist. (Source - Predicts 2019: Analytics and BI Strategy)
One of Microsoft’s newest features inside of Power BI is called Dataflows. It’s a service that allows self-service data preparation (like PowerQuery), but Dataflows can be stored in a centralized location and shared! The Dataflows service allows you create ETL steps inside of a Dataflow and allow others to take advantage of those ETL steps as well.