Data Engineering Tip Day 26: Consolidate Pipeline Failures #thedatachannel #dataengineering

Data Engineering Tip Day 25: Validate Business Logic with Stakeholders #dataengineering

Data Engineering Tip Day 24: Secure Your Pipelines End-to-End #thedatachannel #dataengineering

Data Engineering Tip Day 23: Avoid Overuse of UDFs #thedatachannel #dataengineering

Data Engineering Tip Day 22: Automate Metadata Collection #thedatachannel #dataengineering

Data Engineering Day 21: Make Testing a First-Class Citizen #thedatachannel #dataengineering

Data Engineering Tip Day 20: Choose the Right File Format #dataengineering #thedatachannel

Data Engineering Tip Day 19: Use CDC Over Full Loads When Possible #thedatachannel #dataengineering

Data Engineering Tip Day 18: Minimize Cross-Region Data Movement #thedatachannel #dataengineering

Data Engineering Tip Day 17: Enforce Data Quality at Ingestion #thedatachannel #dataengineering

Data Engineering Tip Day 16: Track Data Lineage Automatically #thedatachannel #dataengineering

Data Engineering Tip Day 15: Build for Backfill from Day 1 #thedatachannel #dataengineering

Data Engineering Tip: Day 14: Version you Code and Data Together #dataengineering

Data Engineering Tip Day 13: Design pipelines that can safely re-run without side effects. #data

Data Engineering Tip Day 12: Use data profiling tools before writing any transformation logic.

Data Engineering Tip Day 11: Move pipeline logic and parameters into YAML/JSON config files

Data Engineering Tip Day 10: Treat your raw ingestion layer as append-only and immutable.

Data Engineering Tip Day 9:Prefer transactional storage formats like Delta Lake,Apache Iceberg,Hudi

Data Engineering Tip Day 8: Always reduce data size before performing joins. #thedatachannel

Data Engineering Tip Day 7: Establish data contracts between producers and consumers

Data Engineering Tips Day 6:Keep data models,transformations and assumptions documented in one place

Data Engineering Tip Day 5 #dataengineering #dataEngineeringTips

Data Engineering Tip Day 4: Choose optimal partitioning strategies when working with big data

Data Engineering Tip Day 3: Add logging and monitoring to every data pipeline you build.

Data Engineering Tip Day 2: Implement schema validation and drift detection early in your pipelines.

Data Engineering Tip Day 1- Always break your ETL/ELT jobs into reusable functions or modules.

Top 5 Data Skills- 2024 #thedatachannel #theDatapedia #bigdata #machinelearning #ai #azure #aws

Top 5 Programming Languages for Data Processing #python #thedatachannel #theDatapedia #rprogramming

#thedatachannel #datawarehouse #datalake #datamesh #lakehouse