CI CD in Azure Synapse Analytics Part 3
In this edition of our series we will create an Artifact / Build pipeline, create a Release pipeline, deploy our Azure Synapse Analytics environment from Dev to QA. Review what was created and what was NOT created. Also pause your SQL Pools if you are not using them.Oracle HA in Azure- Options
A common conversation for bringing Oracle workloads to Azure always surrounds the topic of Real Application Clusters, (RAC). As it’s been quite some time since I’ve covered this topic, I wanted to update from this previous post, as with the cloud and technology, change is constant. One thing that hasn’t changed is my belief RAC is A solution for Oracle for a specific use case and not THE solution for Oracle. The small detail that Oracle won’t support RAC in any third-party cloud is less important than the lack of need for RAC in most cases for those migrating to an enterprise level cloud such as Azure.Bring Vision to Life with Three Horizons, Data Mesh, Data Lakehouse, and Azure Cloud Scale Analytics
Bring Vision to Life with Three Horizons, Data Mesh, Data Lakehouse, and Azure Cloud Scale Analytics – Plus some bonus concepts! I have not posted in a while so this post is loaded with ideas and concepts to think about. I hope you enjoy it! The structure of the post is a chronological perspective of 4 recent events in my life: 1) Camping on the Olympic Peninsula in WA state, 2) Installation of new windows and external doors in my residential house, 3) Injuring my back (includes a metaphor for how things change over time), and 4) Camping at Kayak Point in Stanwood WA (where I finished writing this). Along with these series of events bookended by Camping trips, I also wanted to mention May 1 st which was International Workers Day (celebrated as Labor Day in September in the US and Canada). To reach the vision of digital transformation through cloud scale analytics we need many more workers (Architects, Developers, DBAs, Data Engineers, Data Scientists, Data Analysts, Data Consumers) and the support of many managers and leaders. Leadership is required so analytical systems can become more distributed and properly staffed to scale vs the centralized and small specialist teams that do not scale. Analytics could be a catalyst for employment with the accelerated building and operating of analytical systems. There is evidence that the structure of the teams working on these analytical systems will need to be more distributed to scale to the level of growth required. When focusing on data management, Data Mesh strives to be more distributed, and Data Lakehouse supports distributed architectures better than the analytical systems of the past. I am optimistic that cloud-based analytical systems supported by these distributed concepts can scale and progress to meet the data management, data engineering, data science, data analysis, and data consumer needs and requirements of many organizations.Realtime analytics from SQL Server to Power BI with Debezium
Almost every modern data warehouse project touches the topic of real-time data analytics. In many cases, the source systems use a traditional database, just like SQL Server, and they do not support event-based interfaces. Common solutions for this problem often require a lot of coding, but I will present an alternative that can integrate the data from SQL Server Change Data Capture to a Power BI Streaming dataset with the good help of an Open-Source tool named Debezium.
