In recent years we as data professionals have moved from dealing with SQL Server databases with SQL Server Reporting Server and SQL Server Analysis Services interacting with them (all on-premises) to a wide scale data platform.
In fact even the name of most SQL Server things (like my MVP) have morphed into the name of “Data Platform”.
The name allows for new technologies and processes to be folded into the ecosystem. The radical changes brought about by the Azure platform have recently been matched by the breadth of technological choice in how you interact, manage and understand your data.
Let’s look at some key areas of what Microsoft have to offer on the Data Platform:
SQL Server 2017 – Lets you bring the industry-leading performance and security of SQL Server to the platform of your choice—use it on Windows, Linux, and Docker containers.
SQL Database – Built for developers, SQL Database is a relational database management system with enterprise-class availability, scalability, and security, and built-in intelligence capable of learning app patterns, that can be accessed from anywhere in the world.
Azure Database for MySQL – Quickly stand up a MySQL database and scale on the fly with this fully managed database service for app development and deployment that includes high-availability, security, and recovery at no extra cost.
Azure Database for PostgreSQL – Stand up a PostgreSQL database in minutes and scale on the fly—this fully managed database service for app development and deployment also gives you high-availability, security, and recovery at no extra cost.
SQL Data Warehouse – Scale compute and storage independently with this SQL-based, fully managed, petabyte-scale cloud data warehouse that’s highly elastic and enables you to set up in minutes and scale capacity in seconds.
Azure Cosmos DB – With a guarantee of single-digit-millisecond latencies at the 99th percentile anywhere in the world, this multimodel database service offers turnkey global distribution across any number of Azure regions by transparently scaling and replicating your data to wherever your users are.
Data and analytics products
SQL Server 2017 – With up to 1 million predictions per second using built-in Python and R integration, SQL Server 2017 delivers real-time intelligence as it brings the industry-leading performance and security of SQL Server to the platform of your choice.
HD Insight – A fully managed cloud Spark and Hadoop service, HDInsight provides open source analytic clusters for Spark, Hive, MapReduce, HBase, Storm, Kafka, and Microsoft R Server backed by a 99.9% SLA.
Machine Learning – Easily build, deploy, and manage predictive analytics solutions with this fully managed cloud service and deploy your model into production as a web service in minutes that can be called from any device, anywhere.
Stream Analytics – Develop and run massively parallel real-time analytics on multiple streams of data with this analytics service that helps uncover real-time insights from devices, sensors, infrastructure, and applications.
Azure Bot Service – Accelerate bot development with this intelligent, serverless bot service that scales on demand, requires no server management or patching, and provides built-in templates.
Data Lake Analytics – Develop and run massively parallel data transformation and processing programs in U-SQL, R, Python, and Microsoft .NET over petabytes of data with this on-demand service that provides a simple, scalable way to analyze big data—in seconds.
Data Lake Store – Built to the open HDFS standard, this is a no-limits cloud data lake for your enterprise’s unstructured, semi-structured, and structured data that’s massively scalable and secured, and allows you to run massively parallel analytics.
Data Catalog – Spend less time looking for data and more time getting value from it with this fully managed cloud service that lets you register, enrich, discover, understand, and consume your enterprise data sources.
The current state of the Data Platform is exciting, innovative and vast. For years my aim was to understand how best I could tune, manage and deploy on SQL Server. The good news is that with “recent” improvements to the SQL Server engine:
we can now all focus on other aspects of the Data Platform…. (sorry but I had to put that in there).
With recent enhancements to the SQL Server engine and the maturity of running databases in Azure – it does mean our roles as data professionals are evolving.
Hard core DBAs are now finding themselves talking to Data Scientists on what is required for a stable, reliable, clean, tested, backed-up and secure data processing strategy.
The ability to deploy to the cloud calls for secure and efficient processes around those deployments and nowadays DBAs are also finding themselves involved in conversations around getting database code into source control, code being tested as part of continuous integration and changes deployed via continuous delivery processes.
Or god forbid – knowing being part of something called agile….!!
The data platform has expanded and grown, our approach in how we manage and deploy to it needs to grow as well.
The good thing is that Microsoft have put a massive amount of effort into https://docs.microsoft.com – I used to despair with MSDN and Technet documentation – but I am loving and inspired with the quality of articles being put out on https://docs.microsoft.com
These days if I’m interacting with a new feature or need to diagnose something being able to quickly use these docs has been fantastic in helping me cope with the new world of an expansive Data platform.