Cloud Analytics

Data Warehousing in the Cloud: A Practical Guide Moving analytics to the cloud changes how teams store, access, and analyze data. A cloud data warehouse is a managed service that scales storage and compute on demand, lowers maintenance, and blends with modern tools. The result is faster insights and less operational risk, especially for growing organizations. This practical guide outlines a clear path to plan, migrate, and operate a cloud warehouse that supports dashboards, BI, and data science. ...

Data Lakehouses: Combining Lake and Warehouse Data lakehouses blend the best parts of two older ideas: the data lake and the data warehouse. A data lake stores raw data in many formats, from log files to JSON to images. A data warehouse stores clean, shaped data ready for fast SQL queries. A lakehouse adds reliable transactions, governance, and a unified view on top of the lake. This makes data easier to access, while keeping the lake’s flexibility. ...

Data Warehouses, Lakes, and Meshes: Architectures Explained Data teams often choose among three patterns: data warehouses, data lakes, and data meshes. Each has a clear purpose, a typical setup, and trade-offs. This article explains them in plain language with simple examples you can relate to. Data warehouses A data warehouse stores clean, structured data for fast reporting. It is usually centralized, governed, and tuned for business intelligence. The common flow is ETL or ELT: extract data from sources, transform it into a consistent format, and load it into separate, well-defined tables. Example: a monthly sales dashboard built from a few clean tables that answer questions like “What were sales by region?” ...