Title: P3: PowerBI + PostgreSQL - online analytic [2025-02-23 Sun]
'int64': Integer,
'datetime64[ns]': DateTime,
'datetime64': DateTime
}
And I created very nice automatic comparison of any two
files in Jupyter with histograms and bar plots.
蠡 #dailyreport #powerbi #datawarehouse #dwh #postgresql #python #pandas
Title: P2: PowerBI + PostgreSQL - online analytic [2025-02-23 Sun]
I split all columns to strings and numeric by converting
with Pands function pd.to_numeric and checking if errors
happens.
In PowerBI I download one table with date indexes for
slices and create second table with latest slice.
SQLAlchemy
dtype_mapping = {
'object': String,
'float64': Float, #dailyreport #powerbi #datawarehouse #dwh #postgresql #python #pandas
Title: P1: PowerBI + PostgreSQL - online analytic [2025-02-23 Sun]
+ For real-time operations: Redis > MongoDB > MySQL >
PostgreSQL > SQLite.
For PostgreSQL I prepare data in Python script that use:
- pandas - for coverting types to datetime and numeric
- sqlalchemy - for simplifying type converstion
- asyncpg - sqlalchemy backend to connect to PostgreSQL #dailyreport #powerbi #datawarehouse #dwh #postgresql #python #pandas
Title: P0: PowerBI + PostgreSQL - online analytic [2025-02-23 Sun]
At this week I installed PowerBI and connect it to remote
PostgreSQL.
I asked AI to compare open-source data sources for
PowerBI and compare them by:
- Ease of Setup on Linux: SQLite > PostgreSQL > MySQL >
Redis > MongoDB
- Performance:
+ For large datasets: MongoDB > PostgreSQL > MySQL >
Redis > SQLite. #dailyreport #powerbi #datawarehouse #dwh #postgresql #python #pandas
💡 Databricks Advanced Security with RBAC, RLS & ABAC
Our newest blog-post summarizes authorization patterns on the Databricks platform. How do role-based and attribute-based access control mix with row- and column-level security? All you need to know in a concise little write-up:
🔗 https://www.nextlytics.com/blog/master-databricks-security-with-rbac-rls-abac
#databricks #dataengineering #datascience #sapdatabricks #businessintelligence #blog #azuredatabricks #datawarehouse #datagovernance #unitycatalog
The Data Lakehouse Explained: Why Apache Iceberg Is Quietly Running the Show
https://techlife.blog/posts/data-lakehouse-iceberg
#ApacheIceberg #DataLakehouse #DataWarehouse #DataLake #Snowflake #ApacheSpark #DataEngineering
Datos de Forma Deliberada: Mejores Prácticas para EDW
The article discusses strategies for expanding subject areas in enterprise data warehousing, weighing proactive pre-emption against reactive back-filling. It advocates a balanced approach to governance that allows analysts some flexibility while preventing scope creep. By combining both methods deliberately, organisations can enhance data quality, governance, and responsiveness to business needs.https://goodstrat.com/2026/03/24/datos-de-forma-deliberada-mejores-practicas-para-edw/
Confused by Data Warehouse vs. Data Lake vs. Data Mesh?
Think of it this way:
- 📦 Warehouse = organized storage room
- 🌊 Lake = throw everything in, sort later
- 🕸️ Mesh = each team owns and serves its own data - but there is still a common hub.
The key insight: Mesh isn't a storage technology. You can run a Data Mesh on top of a Warehouse or Lake. It's about ownership, not infrastructure.
👉 https://www.kdnuggets.com/data-lake-vs-data-warehouse-vs-lakehouse-vs-data-mesh-whats-the-difference
#DataMesh #DataLake #DataWarehouse #DataLiteracy
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