DataOps integrates principles from Agile methodologies to manage data workflows efficiently and to improvement across the full data lifecycle

Components of modern database management includes 1. Hardware 2. Software 3. Data and data store 4. Query processor 5. Storage engine etc.

Data ingestion is the process of collecting, transforming, and loading data from various sources into a centralized system, like a warehouse.

In today’s hyper-connected digital world, businesses generate vast amounts of marketing data across multiple channels, including social media, web analytics, email campaigns, CRM systems, and paid advertising platforms. Without a...

Data orchestration platforms automates, manages & optimizes Siloed data workflows across different storage, processing, & analytical systems

AWS data management is achieved through various managed services like AWS Glue that support batch, real-time, and hybrid processing models.

The Salesforce Nonprofit Connector extends this functionality by providing a seamless integration layer for data management. Read on for more

A modern data platform is built on flexibility, scalability, & high-performance architecture. It supports ingestion, processing, and storage. Read on for more.

Key data engineering best practices are 1. Define Data Sources and Requirements 2. Design a Robust Data Pipeline Architecture 3. ETL vs ELT. Read on for more.