Big Data vs Data Warehouse
Explore the key differences and overlaps between Big Data and Data Warehouses. Learn how data warehouses support business intelligence with structured, historical data, while Big Data handles diverse, unrefined sources. Understand when to use each system and their relationship with data lakes and cloud solutions to optimize data processing and analytics.
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Big Data vs Data Warehouse
Big Data and Data Warehouse seem to cater to the same markets and address similar use cases. It is instructive to know when the two concepts overlap and when they differ.
Data Warehouse
Data warehouse is another commonly used term in the industry. You may wonder how it is different from the traditional SQL-based databases or Big Data. The primary difference lies in the utility of these systems. A data warehouse is a system that pulls data from many different sources to an organization, transforms and stores it for reporting and analysis purposes. A data warehouse stores large quantities of historical data and enables fast, complex queries across all the data. The reports created from complex queries within a data warehouse are used to make business decisions. Data warehouse enables Business Intelligence from which managers and analysts glean insights, trends, and potential issues by analyzing corporate data. You’ll hear the term Online Analytical Processing (OLAP) in the context of Data Warehousing. Data warehouses use OLAP, optimized to handle a low ...