Cloud & Data Platforms

Data Lakes vs Data Warehouses: A Practical Guide Both data lakes and data warehouses store data, but they serve different goals. A data lake is a large store for many kinds of data in its native form. A data warehouse holds clean, structured data that is ready for fast analysis. Understanding the difference helps teams choose the right tool for the task. What they are A data lake collects raw data from apps, websites, logs, or sensors. It keeps data in its original formats and uses schema-on-read, meaning you decide how to read it later. A data warehouse cleans and organizes data, applying a schema when data is loaded (schema-on-write). This makes querying predictable and fast, useful for dashboards and reports. ...

Big Data Lakes and Data Warehouses Explained In data work, two patterns come up often: data lakes and data warehouses. They store data to help people explore, analyze, and decide. Each serves a different need, yet both are common in modern analytics and decision making. Understanding them helps teams move faster without losing quality. What is a data lake? A data lake is a large store for data in its native format. It accepts raw files, logs, JSON, images, and text. It is cheap to scale and flexible for data scientists. People can search, sample, or transform data there as a first step in exploration, before any heavy processing. ...

Streaming vs Batch Processing: Use Cases Streaming and batch processing are two fundamental ways to handle data. Streaming processes events as they arrive, updating results continuously. Batch processing collects data over a period, then runs a job that produces a complete result. Both patterns are essential in modern data systems, and many teams use a mix to balance freshness, cost, and complexity. Real-time use cases fit streaming well. Operational dashboards need fresh numbers to detect issues quickly. Fraud detection and anomaly alerts rely on fast signals to stop problems. Live personalization, such as recommendations on a website, improves user experience when data arrives fast enough to matter. ...