Empowering Lakehouse Users – Data Engineering with Fabric
Learn how to use the OneLake Explorer and Data Wrangler extension in VS Code to empower users to work with data in Microsoft Fabric.
2024-05-22
1,770 reads
Learn how to use the OneLake Explorer and Data Wrangler extension in VS Code to empower users to work with data in Microsoft Fabric.
2024-05-22
1,770 reads
This next article in the series creates objects at the gold layer for consumption by combining tables from the silver layer of the lake house.
2024-05-15
3,215 reads
This article explains metadata driven pipelines and shows an example in Microsoft Fabric.
2024-05-01
4,667 reads
Learn how to perform full and incremental loads in Fabric with a little SparkSQL.
2024-04-17
6,289 reads
In this article, learn how you can manage files and folders for both full and incremental loading situations.
2024-03-27
3,594 reads
Learn how to get started with Microsoft Fabric along with the differences between managed and unmanaged tables.
2024-03-20
4,536 reads
Generative Al tools like Gemini and GPT promise to automate and augment knowledge-based work. Data professionals must adapt to this transformation by acquiring new skills and playing a central role in their organization's AI-driven future. Data preparation, curation, ethical sourcing and labeling, and collecting user feedback become crucial as high-quality data is essential for effective LLM based application.
2024-03-04
2,665 reads
Get ready to be blown away! The highly anticipated Microsoft Build in May 2023 has finally unveiled its latest and greatest creation: the incredible Microsoft Fabric - an unparalleled Data Intelligence platform that is guaranteed to revolutionize the tech world! fig 1: OneLake for all Data One of the most exciting things in Fabric I […]
2023-07-26
5,197 reads
This article examines how one can structure a pipeline for processing real-time data using Kafka and Informatica.
2023-04-26
4,625 reads
Whether you work as a Data Engineer or a Data Scientist, a Jupyter Notebook is a helpful tool. One of the projects I was working required a comparison of two parquet files. This is mainly a schema comparison, not a data comparison. Though the two .parquet were created from two different sources, the outcome should […]
2021-05-17
5,448 reads
By Steve Jones
This value is something that I still hear today: our best work is done...
By gbargsley
Have you ever received the dreaded error from SQL Server that the TempDB log...
By Chris Yates
Artificial intelligence is no longer a distant concept. It is here, embedded in the...
Comments posted to this topic are about the item Planning for tomorrow, today -...
We have a BI-application that connects to input tables on a SQL Server 2022...
At work we've been getting better at writing what's known as GitHub Actions (workflows,...
I try to run this code on SQL Server 2022. All the objects exist in the database.
CREATE OR ALTER VIEW OrderShipping AS SELECT cl.CityNameID, cl.CityName, o.OrderID, o.Customer, o.OrderDate, o.CustomerID, o.cityId FROM dbo.CityList AS cl INNER JOIN dbo.[Order] AS o ON o.cityId = cl.CityNameID GO CREATE OR ALTER FUNCTION GetShipCityForOrder ( @OrderID INT ) RETURNS VARCHAR(50) WITH SCHEMABINDING AS BEGIN DECLARE @city VARCHAR(50); SELECT @city = os.CityName FROM dbo.OrderShipping AS os WHERE os.OrderID = @OrderID; RETURN @city; END; goWhat is the result? See possible answers