Developing a centralized repository of data is only useful when you can use it to better explain what is going on in your organization, and for that you are going to want to create Power BI reports to provide that analysis.
Designing for large scale models is different as one needs to be able to accommodate data from multiple different sources and include complex transformations. Data solutions need to accommodate different types of users including methods to support departments as well as releasing enterprise-wide reports.
Data models should be able to provide ad hoc querying, data science as well as self-service reporting models. To govern the solution, there needs to be a plan for providing a location for people to find the answers to the questions they may have about access, design and security in a user accessible design.
During this all day session we will explore the following topics
- Power BI Large scale modeling
- Enterprise Data Transformation techniques
- Release management and lifecycle of Workspaces and Apps
- Data Security and Source Control
- Self Service Reporting Techniques
- Power BI Governance
As part of the session attendees will gain hands on experience to apply the skills discussed on their own laptops.
Biography
Ginger Grant
Ginger Grant is a Data Platform MVP who provides consulting services in advanced analytic solutions, including machine learning, data warehousing, and Power BI. She is an author of articles, books, and at DesertIsleSQL.com and uses her MCT to provide data platform training in topics such as Azure Synapse Analytics, Python and Azure Machine Learning.