Data warehousing, big data and business intelligence (BI) are often presented as separate disciplines, but they are all part of the modern analytics landscape and are inextricably related. Having to learn them one at a time can be challenging and make mastering any one of them seem overwhelming. The best way forward is to learn them together.

Come to this two-day workshop, from long-time data expert Andrew Brust, to do just that. We'll cover analytics concepts like dimensional modeling, columnar storage, and vector processing; then proceed to learn about data warehousing, both on premises and in the cloud. Next, we'll learn about big data and data lake technology including Apache Spark teamed with cloud data lake storage, both on their own and in combination with the data warehouse. We'll also cover Business Intelligence, comprehensively. We'll look at BI engine technology, including both classic OLAP and in-memory approaches. We'll of course also cover reporting and data visualization, including the basics, AI-assisted visuals; and augmented analytics. We'll even investigate hybrid BI technologies that allow you to combine local storage for small data with remote querying for big data. We'll cap things off with a look at data governance, and how to use Azure Purview to build a comprehensive data catalog across all of the data services covered in the workshop.

Technologies covered include Azure Synapse Analytics (formerly SQL Data Warehouse), SQL Server Big Data Clusters, Power BI, SQL Server/Azure Analysis Services, Azure HDInsight, Azure Databricks and Azure Purview. We'll cover a broad range of tools, too, including Azure Data Studio, Synapse Studio, Jupyter Notebooks, and classics like SQL Server Management Studio and SQL Server Data Tools in Visual Studio.

Beyond all the Microsoft technology, material in this workshop will be directly applicable to non-Microsoft platforms, and non-Azure clouds, too. This will make the content relevant for users of data warehouses like Snowflake, big data services like Google Cloud Dataproc, data lake platforms like Amazon Athena and BI platforms like Tableau and Looker. And throughout the material, workshop attendees will also gain essential expertise in industry dynamics, and the competitive landscape, enabling them to select offerings from the strongest industry players, and to exercise caution around offerings and vendors who carry more risk.

This workshop seminar is designed for busy professionals who need to be knowledgeable, get skilled-up and understand the analytics ecosystem quickly. If that sounds good to you, please join us for this seminar.

You will learn:

• The basics of dimensional design, data warehouse technology, business intelligence and data governance fundamentals, for cloud and on-premises scenarios
• About provisioning, basic use of, and integration points between, Azure Synapse Analytics, Azure Data Lake Storage, Azure Purview and Power BI
• Integrated tooling strategies with Azure Data Studio, Synapse Studio, Jupyter Notebooks, SQL Server Management Studio and SQL Server Data Tools
• About the analytics ecosystem competitive landscape, including promising new startups and the effects and patterns of analytics provider mergers and acquisitions