Building a Real-Time Analytics Pipeline with Azure Stream Analytics and SQL Server
Learn how a real time analytics solution for ETL and reporting can be built with SQL Server, Power BI, and Stream Analytics.
2026-01-26
1,115 reads
ETL (Extract Transform and Load)
Think LSNs Are Unique? Think Again - Preventing Data Loss in CDC ETL
When using only an LSN to track which changes you have processed, you can lose data. This article shows how to avoid this problem.
2025-12-15
2,606 reads
A gentle introduction to dbt
Over the past years, the tool dbt – short for data build tool – has become quite popular in the data engineering world for handling such an ELT process. dbt takes on the role of the “T”, meaning it’s responsible for transforming the data in a certain data store.
2024-12-23
Time-Series Data Analysis with Apache Druid
Learn the basics of Apache Druid and how it can be used to ingest data into a data lake.
2023-11-10
14,593 reads
What I Wish Everyone Knew About ETL Processes - Traditional to Modern Cloud Solutions
Learn about the evolutionary journey of ETL (Extract, Transform, Load) from traditional processes to modern cloud solutions.
2023-10-18
Unpivot Data Using Python
This article looks at manipulating data using Python to unpivot data received in a cross tab format.
2023-06-30
3,374 reads
Advantages of Kappa architecture in the Modern Data Stack
A comparison of the lambda and kappa architectures for real time ingestion and analysis of big data.
2023-06-19
5,488 reads
Python 3 Script for Generating SQL Insert Statements from CSV Data
This Python 3 script is designed to take CSV file data pasted into the csv_data variable and generate SQL insert statements that can be used to insert the data into a MySQL database. The script is easy to use and can save you a lot of time when working with large amounts of data.
2023-05-08 (first published: 2023-05-05)
5,740 reads
The Art of Data Ingestion - Part 1
Data movement is a fundamental piece of a data engineer’s duties, and recently I’ve been thinking about the art of data movement. What are some of the most important pieces that a data engineer needs to think about when confronted with data ingestion? There is of course data exporting as well, and in that case, […]
2022-11-11
6,072 reads
2021-04-23
637 reads
Blogs
In-Person CISA Training – April 13-16, 2026
By Brian Kelley
I will be leading an in-person Certified Information Systems Auditor (CISA) exam prep class...
EightKB 2026
EightKB is back again for 2026! The biggest online SQL Server internals conference is...
The FinOps Lifecycle: From Budgeting to Reporting
By HeyMo0sh
Working in DevOps long enough teaches you two universal truths: That’s exactly why I...
Forums
Fun with JSON II
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Changing Data Types
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Answering Questions On Dropped Columns
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Question of the Day
Fun with JSON II
I have some data in a table:
CREATE TABLE #test_data
(
id INT PRIMARY KEY,
name VARCHAR(100),
birth_date DATE
);
-- Step 2: Insert rows
INSERT INTO #test_data
VALUES
(1, 'Olivia', '2025-01-05'),
(2, 'Emma', '2025-03-02'),
(3, 'Liam', '2025-11-15'),
(4, 'Noah', '2025-12-22');
If I run this query, how many rows are returned?
SELECT t1.[key] AS row,
t2.*
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t1
CROSS APPLY OPENJSON(t1.value) t2; See possible answers