![]() ![]() Power BI 2.0 released for general availability almost a week ago, and it has many new features. Azure SQL Data Warehouse is very new, and there are not so much blogs, or articles about it, but documentation page of Azure SQL Data Warehouse has some informational videos about it. you can use Azure SQL Database documentation as starting point. There are fortunately heaps of information about Azure SQL Database that you can read and watch. Azure SQL Database is the SQL Server database engine, and Azure SQL Data Warehouse released recently and optimized and is configurable highly for massive data and the analytical usage of that. ![]() There are two main azure services that are recommended to be used as the Data Warehouse on cloud. To learn more about SSIS please watch SSIS tutorial video series here: SSIS Tutorial Videos. SSIS packages can load data into Azure data stores especially with the new Azure Pack released for SSIS. SSIS is premier data transfer and consolidation tool that supports heaps of data sources, it has many built-in transformation that you can apply on the data set, and the result set can be loaded in any kind of destination. SQL Server Integration Services (SSIS) is a familiar name in database world. If you want to learn more about Azure Data Factory read the article here: Building the first Azure Data Factory. Data Factory can load the data into on-premises data stores as well as cloud based such as Azure SQL Database and Azure SQL Data Warehouse. Azure Data Factory connects to on-premises data sources with a gateway named Data Management Gateway. In the diagram you see two tools used for data extract, load and transform as below:Īzure Data Factory is cloud based compute service for data extraction and loading, it supports data sources such as SQL Server on-premises, Oracle on-premises, CSV files and some other sources. As long as there are some data stored somewhere we can use that as the source.īelow is an architecture high level diagram of the solution the on-premises data store can be of any type such as SQL Server database, Oracle, MySQL DB, or even CSV and Excel files…. I considered data sources to be on-premises because most of the data still sits on companies and organization’s on-premises data store. Obviously above scenarios is only one of the 100 scenarios that these products can be used together to build an end-to-end solution. Power BI as the data analysis and front-end toolĪbove technologies together provide a highly reliable, and scalable data analysis solution.Azure SQL Database or Azure SQL Data Warehouse as the database / data warehouse engine in cloud.Azure Data Factory or SSIS with Azure Pack for Data extraction and transformation.In this post I’ll just explain one example scenario of Hybrid and End-to-End BI solution that uses below technologies Power BI can be used alongside some other Azure services, and even On-Premises services to build an end-to-end enterprise BI and Data Analysis Solution. With the announcement of Power BI a week ago and with great features in this product, there are many opportunities that this product and service can be used. ![]()
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