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
1,792 reads
data engineering
Combining Silver Tables into a Model – Data Engineering with Fabric
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
3,357 reads
Metadata Driven Pipelines – Data Engineering with Fabric
This article explains metadata driven pipelines and shows an example in Microsoft Fabric.
2024-05-01
4,919 reads
Full vs. Incremental Loads – Data Engineering with Fabric
Learn how to perform full and incremental loads in Fabric with a little SparkSQL.
2024-04-17
6,506 reads
Managing Files and Folders with Python – Data Engineering with Fabric
In this article, learn how you can manage files and folders for both full and incremental loading situations.
2024-03-27
3,678 reads
Managed Vs Unmanaged Tables – Data Engineering with Fabric
Learn how to get started with Microsoft Fabric along with the differences between managed and unmanaged tables.
2024-03-20
4,672 reads
Evolving Role of Data Professionals in Artificial Intelligence Era
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
2,697 reads
What is OneLake in Microsoft Fabric?
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
5,268 reads
Revolutionizing Real-Time Data Management with SQL Server, Kafka, and Informatica
This article examines how one can structure a pipeline for processing real-time data using Kafka and Informatica.
2023-04-26
4,646 reads
Step by Step Guide to Install Jupyter Notebook
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
5,487 reads
Blogs
Why Optimize CPU for RDS SQL Server is a game changer
One feature that I have been waiting for years! The new announcement around optimize...
Performance tuning KubeVirt for SQL Server
Following on from my last post about Getting Started With KubeVirt & SQL Server,...
T-SQL Tuesday #193 – A Note to Your Past, and a Warning from Your Future
By DesertDBA
I haven’t posted in a while (well, not here at least since I’ve been...
Forums
Refactoring SQL Code
Comments posted to this topic are about the item Refactoring SQL Code, which is...
The Read Committed Snapshot Isolation behaviour
Comments posted to this topic are about the item The Read Committed Snapshot Isolation...
Working with JSON/JSONB Data in PostgreSQL using Python
Comments posted to this topic are about the item Working with JSON/JSONB Data in...
Question of the Day
The Read Committed Snapshot Isolation behaviour
I am currently working with Sql Server 2022 and AdventureWorks database. First of all, let's set the "Read Committed Snapshot" to ON:
use master; go alter database AdventureWorks set read_committed_snapshot on with no_wait; goThen, from Session 1, I execute the following code:
--Session 1 use AdventureWorks; go create table ##t1 (id int, f1 varchar(10)); go insert into ##t1 values (1, 'A');From another session, called Session 2, I open a transaction and execute the following update:
--Session 2 use AdventureWorks; go begin tran; update ##t1 set f1 = 'B' where id = 1;Now, going back to Session 1, what happens if I execute this statement?
--Session 1 select f1 from ##t1 where id = 1;See possible answers