Great walkthrough on building a robust data quality score using dbt + Elementary Data. Clear, actionable, and perfect for modern data teams. medium.com/@alexandroab... #DataEngineering #AnalyticsEngineering #dbt #DataQuality #Data
Great walkthrough on building a robust data quality score using dbt + Elementary Data. Clear, actionable, and perfect for modern data teams. medium.com/@alexandroab... #DataEngineering #AnalyticsEngineering #dbt #DataQuality #Data
About Quality and Data Testing medium.com/p/382581ae9a55
Self-service analytics
open.substack.com/pub/alexabal...
๐/๐ ๐จ ๐๐ง๐๐ฅ๐ฒ๐ญ๐ข๐๐ฌ ๐๐ง๐ ๐ข๐ง๐๐๐ซ๐ข๐ง๐ ๐ฏ๐ฌ. ๐๐๐ญ๐ ๐๐ง๐ ๐ข๐ง๐๐๐ซ๐ข๐ง๐ : ๐๐ก๐ ๐๐ซ๐๐๐ญ ๐๐ฅ๐ฎ๐ซ ๐ข๐ฌ ๐๐๐๐.
With tools like #dbt redefining workflows, where do these roles start to merge? Letโs unpack it. ๐
(Hint: SQL is the new battleground.) โ๏ธ
#DataEngineering #AnalyticsEngineering #ModernDataStack
โก๏ธ LOGICAL_OR returns TRUE because at least one of the values in the array is less than 3.
SELECT LOGICAL_OR(x < 3) AS logical_or FROM UNNEST([1, 2, 4]) AS x;
Learned in medium.com/data-enginee...
Exactly! And this same approach, using a row_number partitioned by client and group_id, can be used to create customer journeys leading up to each purchase.
Can anyone figure out what the window function in this query does? What do you think? ๐ค #SQL #DataBS
Need to adjust a date field to the start of the week in #BigQuery ?
Do you prefer sunday or monday as the first day?
For sunday, use:
DATE_TRUNC(date_field, WEEK)
For Monday, use:
DATE_TRUNC(date_field, WEEK(monday))
Quick and easy! #SQL #Data #DataAnalysis
Simplify ROW_NUMBER() usage with QUALIFY.
You can do it in one step instead of using a CTE and filtering. Less code, same result. #BigQuery #DataBS #DataAnalysis
Want to reuse the same OVER clause across multiple fields in #BigQuery? Define the WINDOW once at the end of your query! Example #DataBS #SQL
Definitely, IMHO, one of the biggest challenges within a Data & Analytics department is teaching stakeholders to correctly interpret the data. What do you think would be yours? #DBT #DATABS #DataEngineer www.linkedin.com/posts/dbtlab...
Do you know which #attribution model this query corresponds to? #DataBS #Data #Analytics
Understanding RANK() vs DENSE_RANK() in BigQuery:
Example: Scores in descending order
๐ RANK() skips numbers after ties, while DENSE_RANK() doesn't. Use wisely! #SQL #BigQuery #Data
Metabase 51 is here! ๐ New features include chart-level permissions for secure sharing, interactive filters for embedded analytics, and an upgraded UI for better usability. Power up your data game! ๐โจ Full release: www.metabase.com/releases/met... #Metabase #DataWorld
Really important to keep this in mind every time we run a simple query.
1. FROM + JOIN
2. WHERE
3. GROUP BY
4. HAVING
5. SELECT
6. ORDER BY
7. LIMIT
#SQL #Data
#jinja
A simple use case of #Jinja code
Using Jinja in dbt is like adding superpowers to your SQL! ๐ชโจ From dynamic filters to reusable macros, it boosts efficiency and keeps your code DRY. Just remember: a little Jinja goes a long way, donโt overcomplicate! #dbt #Jinja #DataWorld
Discover what's new in dbt Cloud this November! ๐ Exciting updates include enhanced collaboration features, improved testing workflows, and more. Check out the full details here: www.getdbt.com/blog/whats-n... #dbt #DataEngineering #DataWorld
Ever heard of dbt? ๐ It's the magic wand for transforming raw data into actionable insights! With dbt, analysts own the transformation layer, enabling version control, testing, and modularity. ๐ปโจ #dbt #DataAnalytics #DataWorld
Data visualization is more than charts and graphs, it's storytelling! ๐ The best visualizations help uncover patterns, trends, and insights. I recommend having a look at Storytelling with Data by Cole Nussbaumer. #DataViz #BI #DataWorld
Did you know SQL has been around since the 1970s? ๐ It's the backbone of data querying, and still relevant today! Start with basics like SELECT, WHERE, and JOIN to unlock data insights. What's your favorite SQL trick? #SQL #DataAnalysis #DataWorld
Since I started working, I've seen several 'dinosaur' companies that, purely for the sake of 'prestige', have implemented BI tools so poorly designed, dense, and slow that they end up achieving the opposite of becoming a data-driven company.