Yes, you read it correctly. You can travel in time on your data using Azure Data Bricks and DeltaLake. The feature is quite easy to use and comes with a lot of very nice features and business value. Even a value so powerfull that the business does not need to make descissions up front when you are building your data warehouse. A little word about the background Azure has abopted DataBricks into the Azure Synapse portfolio with seemless integration between all the services from within the umbrella of Azure Synapse.
edit: Added the same aproach for JSON at the bottom of this post Have you also seen alot of “Helper Queries” in Power Query when working with files from folders? I think it is very cluttered to have all these helpers laying around in the Power Query editor. What I’m used to see Above is the usual way of Power Query to handle several files in the same folder. The approach is done to have only 1 (usually the first) file to create the schema from.
Ever been as frustrated as I have when importing flat files to a SQL Server and the format suddenly changes in production? Commonly used integration tools (like SSIS) are very dependent on the correct, consistent and same metadata when working with flat files. So I’ve come up with an alternative solution that I would like to share with you. When implemented, the process of importing flat files with changing metadata is handled in a structured, and most important, resiliant way.
Have you ever tried to delete an object from the database by mistake or other error? Then you should read on in this short post. I recently came across a good co-worker of mine who lost one of the views on the developer database. He called me for help. Fortunately the database was in FULL RECOVERY mode – so I could extract the object from the database log and send the script to him for his further work that day.
First of all, a quick recap on what a recursive query is. Recursive queries are useful when building hierarchies, traverse datasets and generate arbitrary rowsets etc. The recursive part (simply) means joining a rowset with itself an arbitrary number of times. A recursive query is defined by an anchor set (the base rowset of the recursion) and a recursive part (the operation that should be done over the previous rowset).
I attended a TDWI conference in May 2016 in Chicago. Here I got a hint about the datatype hierarchyid in SQL Server which could optimize and eliminate the good old parent/child hierarchy. Until then I (and several other in the class) hadn’t heard about the hierarchyid datatype in SQL Server. So here’s an article covering some of the aspects of the datatype hierarchyid – including: Introduction How to use it How to optimize data in the table How to work with data in the hierarchy-structure Goodies Introduction The datatype hierarchyid was introduced in SQL Server 2008.
Recently I got a request inside my organization to make sure that a dimension would keep track of the changes due to requrementes from the business. This needed to be done in a single transaction in pure T-SQL code. So – what to do and how to do it. Here’s one way. The sourcetable looks like this: The request was to keep track of changes in the ManagerId according to CaseId.
Along with the release of SQL server 2016 CTP 3 now comes the preview of a brand new feature for on premise databases – the Query Store. This feature enables performance monitoring and troubleshooting through the log of executed queries. This blogpost will cover the following aspects of the Query Store feature: Introduction How to activate it Configuration options What information is found in the Query Store How to use the feature What’s in it for me Introduction The new feature Query Store enables everyone with responsibility for SQL server performance and troubleshooting with insight to the actual queries and their query-plans.
This blogpost will cover the aspects of the many-to-many feature from SQL Server 2016 – including: Prerequisites The old way The new way This post is based on data from the AdventureWorksDW2012 database. Prerequisites In order to test the new many-to-many feature from SQL Server 2016 SSAS Tabular you’ll need to download the latest CTP from Microsoft – it can be found here: Technet Also you’ll need the Visual Studio 2015 and the add-in for Business Intelligence:
With the release of SQL Server 2016 also comes a great new feature to get a live view of the current execution plan for an active query. This blogpost will cover the aspects of this new feature including: Introduction How to activate How to use and read the output Downsides – if any Introduction The introduction of live query plans are in the current release of SQL Server 2016 CTP 2.