Layers Of Data Processing- Raw, Staging, Bronze, Silver, Gold, Harmonized, Archival

January 14, 2024

Data layers like Raw, Staging, Bronze, Silver, Gold, and harmonized represent different stages in the data processing pipeline, commonly known as a data processing or data transformation pipeline. Each layer serves a specific purpose in managing and refining data as it progresses through the pipeline Why we need Data Layers Any Enterprise Data Project has … More Layers Of Data Processing- Raw, Staging, Bronze, Silver, Gold, Harmonized, Archival

Data Lake-history, pros and cons with real world examples

January 10, 2024

A data lake is a centralized repository that allows organizations to store large volumes of raw and unstructured data in its native format until it is needed. Unlike a traditional data warehouse, which is optimized for structured data and predefined schemas, a data lake can store diverse data types, including raw files, images, videos, logs, … More Data Lake-history, pros and cons with real world examples

Azure Data Engineering Comprehensive Learning Guide

January 4, 2024

Embark on a transformative learning journey in Azure Data Engineering, where you will delve into the core principles, tools, and best practices for designing and implementing robust data solutions in the Azure cloud. This comprehensive guide is structured into five milestones, each carefully crafted to build your expertise progressively over six months. Whether you’re a … More Azure Data Engineering Comprehensive Learning Guide

Data Hub with real world implementation, challenges, pros and cons

January 1, 2024

Definition: A Data Hub is a centralized, organized repository for storing, managing, and processing data from various sources across an organization. It acts as a hub for data integration, enabling a unified and consistent view of data for analytics, business intelligence, and decision-making purposes. Key Components of a Data Hub: Example 1: Enhancing Customer Insights … More Data Hub with real world implementation, challenges, pros and cons

What is Data Fabric? what are its components, examples, pros/cons with detailed Realtime scenario

December 29, 2023

Definition: Data Fabric is a distributed data management framework that allows organizations to seamlessly integrate, access, and manage data across various locations and environments. It provides a unified and consistent layer for data sharing, processing, and analytics, regardless of the underlying infrastructure or data storage systems. History: The concept of Data Fabric emerged as a … More What is Data Fabric? what are its components, examples, pros/cons with detailed Realtime scenario

Data Mesh and its Pros and Cons detailed

December 28, 2023

Definition: Data Mesh is a concept introduced by Zhamak Dehghani, a principal consultant at ThoughtWorks, to address challenges in managing and scaling data in large organizations. It is an architectural paradigm that suggests treating data as a product and decentralizing data ownership and architecture. The core idea is to distribute data responsibilities across the organization, … More Data Mesh and its Pros and Cons detailed

Database Normalization with different Normal Forms- Explained with simple example

December 26, 2023

Database normalization is a process used in designing a relational database to reduce data redundancy and dependency by organizing fields and table of a database. The normalization process involves breaking down large tables into smaller, related tables, which helps in reducing data redundancy and improving data integrity. There are several normal forms, each building on … More Database Normalization with different Normal Forms- Explained with simple example

Star, Snowflake and Galaxy Schema in Datawarehouse with examples

December 24, 2023

Star, snowflake, and galaxy schemas are three common data warehouse schema designs used for organizing and structuring data for efficient querying and reporting. 1. Star Schema: 2. Snowflake Schema: 3. Galaxy Schema (Constellation Schema): Conclusion: Each schema design has its own advantages and considerations. The star schema is often preferred for its simplicity and ease … More Star, Snowflake and Galaxy Schema in Datawarehouse with examples

Types of Data Modeling with Purpose, Use case and Example

December 20, 2023

Data modeling is a process used to define and organize data requirements for a system or business process. It involves creating abstract representations of the data and its relationships to help in understanding, analyzing, and designing the structure of the database or information system. There are several types of data modeling, each serving different purposes … More Types of Data Modeling with Purpose, Use case and Example

ETL vs ELT with detailed use case and scenarios

December 20, 2023

ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) are two different approaches to data integration and processing. Each approach has its own set of use cases and scenarios, and the choice between ETL and ELT depends on various factors such as data volume, data sources, processing requirements, and data warehousing architecture. ETL (Extract, Transform, … More ETL vs ELT with detailed use case and scenarios