Skip to content
  • Saturday, 13 September 2025
  • 8:37 pm
  • Follow Us
Data Engineer

Data/ML Engineer Blog

  • Home
  • AL/ML Engineering
    • AWS AI/ML Services
    • Compute & Deployment
    • Core AI & ML Concepts
      • Data Processing & ETL
      • Decision Trees
      • Deep Learning
      • Generative AI
      • K-Means Clustering
      • Machine Learning
      • Neural Networks
      • Reinforcement Learning
      • Supervised Learning
      • Unsupervised Learning
    • Database & Storage Services
      • Cortex
    • Emerging AI Trends
    • Evaluation Metrics
    • Industry Applications of AI
    • MLOps & DevOps for AI
    • Model Development & Optimization
    • Prompting Techniques
      • Adversarial Prompting
      • Chain-of-Thought Prompting
      • Constitutional AI Prompting
      • Few-Shot Prompting
      • Instruction Prompting
      • Multi-Agent Prompting
      • Negative Prompting
      • Prompt Templates
      • ReAct Prompting
      • Retrieval-Augmented Generation (RAG)
      • Self-Consistency Prompting
      • Zero-Shot Prompting
    • Security & Compliance
      • AWS KMS
      • AWS Macie
      • Azure Key Vault
      • Azure Purview
      • BigID
      • Cloud DLP
      • HashiCorp Vault
      • Immuta
      • Okera
      • OneTrust
      • Privacera
      • Satori
  • Data Engineering
    • Cloud Platforms & Services
      • Alibaba Cloud
      • AWS (Amazon Web Services)
      • Azure Microsoft
      • Google Cloud Platform (GCP)
      • IBM Cloud
      • Oracle Cloud
    • Containerization & Orchestration
      • Amazon EKS
      • Apache Oozie
      • Azure Kubernetes Service (AKS)
      • Buildah
      • Containerd
      • Docker
      • Docker Swarm
      • Google Kubernetes Engine (GKE)
      • Kaniko
      • Kubernetes
      • Podman
      • Rancher
      • Red Hat OpenShift
    • Data Catalog & Governance
      • Alation
      • Amundsen
      • Apache Atlas
      • Apache Griffin
      • Atlan
      • AWS Glue
      • Azure Purview
      • Collibra
      • Collibra
      • Databand
      • DataHub
      • Deequ
      • Google Data Catalog
      • Google Dataplex
      • Great Expectations
      • Informatica
      • Marquez
      • Monte Carlo
      • OpenLineage
      • OpenMetadata
      • Soda SQL
      • Spline
    • Data Ingestion & ETL
      • Apache Kafka Connect
      • Apache NiFi
      • Census
      • Confluent Platform
      • Debezium
      • Fivetran
      • Hightouch
      • Informatica PowerCenter
      • Kettle
      • Matillion
      • Microsoft SSIS
      • Omnata
      • Polytomic
      • Stitch
      • StreamSets
      • Striim
      • Talend
    • Data Lakes & File Standards
      • Amazon S3
      • Apache Arrow
      • Apache Avro
      • Apache Iceberg
      • Azure Data Lake Storage
      • CSV
      • Databricks Delta Lake
      • Dremio
      • Dremio
      • Feather
      • Google Cloud Storage
      • JSON
      • ORC
      • Parquet
    • Data Platforms
      • Cloud Data Warehouses
        • ClickHouse
        • Databricks
        • Snowflake
          • Internal and External Staging in Snowflake
          • Network Rules in Snowflake
          • Procedures + Tasks
          • Snowflake administration and configuration
          • Snowflake Cloning
      • Cloudera Data Platform
      • NoSQL Databases
      • On-Premises Data Warehouses
        • DuckDB
      • Relational Databases
        • Amazon Aurora
        • Azure SQL Database
        • Google Cloud SQL
        • MariaDB
        • Microsoft SQL Server
        • MySQL
        • Oracle Database
        • PostgreSQL
    • Data Streaming & Messaging
      • ActiveMQ
      • Aiven for Kafka
      • Amazon Kinesis
      • Amazon MSK
      • Apache Kafka
      • Apache Pulsar
      • Azure Event Hubs
      • Confluent Platform
      • Google Pub/Sub
      • IBM Event Streams
      • NATS
      • Protocol Buffers
      • RabbitMQ
      • Red Hat AMQ Streams
    • Data Warehouse Design
      • Data Governance and Management (DGaM)
        • Compliance Requirements
        • Data Lineage
        • Data Retention Policies
        • Data Stewardship
        • Master Data Management
      • Data Warehouse Architectures (DWA)
        • Enterprise Data Warehouse vs. Data Marts
        • Hub-and-Spoke Architecture
        • Logical vs. Physical Data Models
        • ODS (Operational Data Store)
        • Staging Area Design
      • Data Warehouse Schemas (DWS)
        • Data Vault
        • Galaxy Schema (Fact Constellation)
        • Inmon (Normalized) Approach
        • Kimball (Dimensional) Approach
        • Snowflake Schema
        • Star Schema
      • Database Normalization
      • Dimensional Modeling Techniques (DMT)
        • Bridge Tables
        • Conformed Dimensions
        • Degenerate Dimensions
        • Junk Dimensions
        • Mini-Dimensions
        • Outrigger Dimensions
        • Role-Playing Dimensions
      • ETL/ELT Design Patterns
        • Change Data Capture (CDC)
        • Data Pipeline Architectures
        • Data Quality Management
        • Error Handling
        • Metadata Management
      • Fact Table Design Patterns(FTDP)
        • Accumulating Snapshot Fact Tables
        • Aggregate Fact Tables
        • Factless Fact Tables
        • Periodic Snapshot Fact Tables
        • Transaction Fact Tables
      • Modern Data Warehouse Concepts (MDWC)
        • Data Lakehouse
        • Medallion Architecture
        • Multi-modal Persistence
        • Polyglot Data Processing
        • Real-time Data Warehousing
      • Performance Optimization (PO)
        • Compression Techniques
        • Indexing Strategies
        • Materialized Views
        • Partitioning
        • Query Optimization
      • Slowly Changing Dimensions(SCD)
        • SCD Type 0
        • SCD Type 1
        • SCD Type 2
        • SCD Type 3
        • SCD Type 4
        • SCD Type 6
        • SCD Type 7
    • Distributed Data Processing
      • Apache Beam
      • Apache Flink
      • Apache Hadoop
      • Apache Hive
      • Apache Pig
      • Apache Pulsar
      • Apache Samza
      • Apache Sedona
      • Apache Spark
      • Apache Storm
      • Presto/Trino
      • Spark Streaming
    • Infrastructure as Code & Deployment
      • Ansible
      • Argo CD
      • AWS CloudFormation
      • Azure Resource Manager Templates
      • Chef
      • CircleCI
      • GitHub Actions
      • GitLab CI/CD
      • Google Cloud Deployment Manager
      • Jenkins
      • Pulumi
      • Puppet: Configuration Management Tool for Modern Infrastructure
      • Tekton
      • Terraform
      • Travis CI
    • Monitoring & Logging
      • AppDynamics
      • Datadog
      • Dynatrace
      • ELK Stack
      • Fluentd
      • Graylog
      • Loki
      • Nagios
      • New Relic
      • Splunk
      • Vector
      • Zabbix
    • Operational Systems (OS)
      • Ubuntu
        • Persistent Tasks on Ubuntu
      • Windows
    • Programming Languages
      • Go
      • Java
      • Julia
      • Python
        • Dask
        • NumPy
        • Pandas
        • PySpark
        • SQLAlchemy
      • R
      • Scala
      • SQL
    • Visualization Tools
      • Grafana
      • Kibana
      • Looker
      • Metabase
      • Mode
      • Power BI
      • QuickSight
      • Redash
      • Superset
      • Tableau
    • Workflow Orchestration
      • Apache Airflow
      • Apache Beam Python SDK
      • Azkaban
      • Cron
      • Dagster
      • Dagster Change
      • DBT (data build tool)
      • Jenkins Job Builder
      • Keboola
      • Luigi
      • Prefect
      • Rundeck
      • Temporal
  • Tech People
    • AI/ML Visionaries
    • Community Champions
    • Data Quality
    • Data Strategy
    • Modern Stack Leaders
    • Platform Founders
    • Real-time Systems
  • Home
  • Archive by category "ETL/ELT"
The Great ETL Migration
Data ETL/ELT

The Great ETL Migration

Alex Jul 6, 2025 0

The Great ETL Migration: Why Companies Are Ditching Traditional Tools for Cloud-Native Solutions in 2025 A Fortune 500 manufacturing company…

Read More
AI Copilots Are Replacing
AI Data ETL/ELT

How AI Copilots Are Replacing Manual Data Pipeline

Alex Jun 28, 2025 0

How AI Copilots Are Replacing Manual Data Pipeline Development: The 40% Revolution Transforming Data Engineering The data engineering landscape is…

Read More
Data Mesh
Data DataLake ETL/ELT

The Hidden Economics of Data Mesh

Alex Jun 19, 2025 0

The Hidden Economics of Data Mesh: Why 67% of Implementations Fail and How Platform Teams Can Save $2M Annually Introduction…

Read More
The Hidden Psychology of ETL
Data ETL/ELT

The Hidden Psychology of ETL

Alex Jun 18, 2025 0

The Hidden Psychology of ETL: How Cognitive Load Theory Explains Why Most Data Pipelines Fail Introduction Picture this: A senior…

Read More
Real-Time Data Engineering at Scale
AI Data ETL/ELT

Real-Time Data Engineering at Scale

Alex Jun 7, 2025 0

Real-Time Data Engineering at Scale: Apache Kafka, Flink, and the Rise of Edge AI In today’s hyper-connected world, the ability…

Read More
AWS Glue vs. Traditional ETL Tools
Data ETL/ELT VS

AWS Glue vs. Traditional ETL Tools

Alex May 28, 2025 0

AWS Glue vs. Traditional ETL Tools: A Cost-Performance Analysis When I began modernizing our organization’s data infrastructure last year, we…

Read More
Modern Data Integration
ETL/ELT

Modern Data Integration with Streaming Analytics

Alex Apr 22, 2025 0

Modern Data Integration with Streaming Analytics: Real-Time Ingestion & Processing In today’s fast-paced digital landscape, the ability to ingest, process,…

Read More
The Rise of Real-Time Data Processing: Why Apache Kafka and Flink Are Essential in 2025
Data ETL/ELT

The Rise of Real-Time Data Processing

Alex Mar 20, 2025 0

The Rise of Real-Time Data Processing: Why Apache Kafka and Flink Are Essential in 2025 How Streaming Data Is Rewriting…

Read More
Building Cost-Efficient Data Pipelines in 2025
Data ETL/ELT

Building Cost-Efficient Data Pipelines in 2025

Alex Jan 14, 2025 0

Building Cost-Efficient Data Pipelines in 2025: Strategies for Modern Workloads In 2025, as organizations continue to scale their data operations,…

Read More
Ensuring Data Quality
Data ETL/ELT

Ensuring Data Quality

Alex Sep 17, 2024 0

Ensuring Data Quality: Best Practices for Data Engineers Data engineering isn’t glamorous, but it’s the foundation of every successful data…

Read More

Posts pagination

1 2

Recent Posts

  • How Snowflake Cortex Changes MLOps
  • Data Mesh vs Data Fabric
  • Zero-ETL Revolution
  • Vector Databases in Production
  • The Great ETL Migration

Recent Comments

  1. smortergiremal on Comparison of Equivalent Cloud Services Across AWS, Google Cloud, and Azure
  2. Ustas on The Genius of Snowflake’s Hybrid Architecture: Revolutionizing Data Warehousing

Archives

  • August 2025
  • July 2025
  • June 2025
  • May 2025
  • April 2025
  • March 2025
  • February 2025
  • January 2025
  • November 2024
  • October 2024
  • September 2024
  • August 2024
  • July 2024
  • June 2024
  • May 2024
  • April 2024
  • March 2024
  • February 2024
  • January 2024
  • December 2023
  • November 2023
  • October 2023
  • September 2023
  • August 2023
  • July 2023
  • June 2023
  • May 2023

Categories

  • AI
  • Analytics
  • AWS
  • ClickHouse
  • Data
  • Databricks
  • DataLake
  • DuckDB
  • ETL/ELT
  • Future
  • ML
  • Monthly
  • OpenSource
  • Snowflake
  • StarRock
  • Structure
  • VS
YOU MAY HAVE MISSED
Cortex
AI Data ML Snowflake
How Snowflake Cortex Changes MLOps
Alex Aug 26, 2025
Data Mesh vs Data Fabric
Data
Data Mesh vs Data Fabric
Alex Aug 19, 2025
Zero-ETL Revolution
AI Data Future ML
Zero-ETL Revolution
Alex Aug 5, 2025
Vector Databases in Production
AI Data
Vector Databases in Production
Alex Jul 15, 2025

(c) Data/ML Engineer Blog