ETL Antipattern: Ignore the Logging
In my last ETL Antipatterns post, I wrote about the unexciting but very necessary work of documenting ETL processes. The logging of ETL operations is just as (un)captivating as...
2020-12-21
6 reads
Tim Mitchell
- Interests: SQL Server, Data Warehousing, ETL, Data Architecture, Python, Dbt
- Website: https://www.TimMitchell.net
- Bluesky: tmitch.net
ETL Antipattern: Skipping The Documentation
Documentation is an asset that is both loathed and loved. Creating technical and business documentation is often looked upon as a tedious chore, something that really ought to be...
2020-12-20
14 reads
ETL Antipattern: Skipping The Documentation
Documentation is an asset that is both loathed and loved. Creating technical and business documentation is often looked upon as a tedious chore, something that really ought to be...
2020-12-20
6 reads
ETL Antipattern: Load Processes that Don’t Scale
One of the most significant design considerations in ETL process development is the volume of data to be processed. Most ETL processes have time constraints that require them to...
2020-12-19
261 reads
ETL Antipattern: Load Processes that Don’t Scale
One of the most significant design considerations in ETL process development is the volume of data to be processed. Most ETL processes have time constraints that require them to...
2020-12-19
6 reads
ETL Antipattern: Failure to Test and Validate
“If it compiles, it works.” – An unemployed developer Building ETL processes is quite easy. Building ETL processes that deliver accurate results as quickly as possible is substantially more...
2020-12-18
14 reads
ETL Antipattern: Failure to Test and Validate
“If it compiles, it works.” – An unemployed developer Building ETL processes is quite easy. Building ETL processes that deliver accurate results as quickly as possible is substantially more...
2020-12-18
7 reads
ETL Antipattern: Failing to Treat ETL Logic as Source Code
In most data projects, building the extract-transform-load (ETL) logic takes a significant amount of time. Enterprise ETL processes must do several things well: retrieve enough data to satisfy the...
2020-12-17
19 reads
ETL Antipattern: Failing to Treat ETL Logic as Source Code
In most data projects, building the extract-transform-load (ETL) logic takes a significant amount of time. Enterprise ETL processes must do several things well: retrieve enough data to satisfy the...
2020-12-17
10 reads
ETL Antipattern: No Error Handling Logic
I usually avoid talking about technology in absolutes, but here’s one that I can share without reservation: On a long enough timeline, every single ETL process will eventually fail....
2020-12-16
15 reads
Blogs
AI: Blog a Day – Day 4: Transformers – Encoder, Decoder, and Attention
By Vinay Thakur
Continuing from Day 3 where we covered LLM models open/closed and their parameters, Today...
Flyway Tips: Multiple Projects
By Steve Jones
One of the nice things about Flyway Desktop is that it helps you manage...
What DevOps Look Like in Microsoft Fabric
By HeyMo0sh
Microsoft Fabric (not to be confused with the more general term “fabric” in DevOps)...
Forums
Can an Azure App Service Managed Identity be used for SQL Login?
I'm fairly certain I know the answer to this from digging into it yesterday,...
Azure Synapse database refresh
Hi Team, I am trying to refresh the Azure Synapse Dedicated pool from production...
how to write this query?
hi everyone I am not sure how to write the query that will produce...
Question of the Day
Fun with JSON I
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 *
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t; See possible answers