{"id":10555,"date":"2023-08-28T09:00:03","date_gmt":"2023-08-28T06:00:03","guid":{"rendered":"https:\/\/globalit.com.tr\/data-management-with-data-warehousing-and-bigquery-the-power-of-data-storage-and-analytics\/"},"modified":"2025-01-08T13:05:38","modified_gmt":"2025-01-08T10:05:38","slug":"data-management-with-data-warehousing-and-bigquery-the-power-of-data-storage-and-analytics","status":"publish","type":"post","link":"https:\/\/globalit.com.tr\/en\/data-management-with-data-warehousing-and-bigquery-the-power-of-data-storage-and-analytics\/","title":{"rendered":"Data Management with Data Warehousing and BigQuery: The Power of Data Storage and Analytics"},"content":{"rendered":"\n
The data storage system used to collect, organize, and manage large amounts of structured and unstructured data is called a data warehouse. A Data Warehouse typically aggregates data from different sources into a single center, making it possible for businesses to analyze that data for easy access. In this way, businesses can make better decisions and have a competitive advantage. BigQuery is a managed data warehouse and data analytical database service. It allows you to analyze large data sets effectively and quickly, as well as to query them. Thanks to its distributed architecture, it is the focus of a high-performance solution. <\/p>\n\n
It facilitates data analysis using a similar query language and speeds up the process of users querying large data sets. Explain how the data warehouse works and why it’s important. Information is given about the areas of use and their advantages. Topics such as how businesses can improve their data management strategies and increase analytical power are addressed. The prepared data is analyzed, stored, reported and made available for business decisions. Traditional business databases are different because instead of the operational databases used for businesses, databases optimized for analysis are used. <\/p>\n\n
Optimized for performing daily operations, the databases provide quick access to generally detailed and up-to-date data. Querying large data sets to analyze and performing complex analyses can be difficult in such databases. The data warehouse is designed as OLAP databases and is also optimized for analysis. Thanks to the data structure and query algorithms, you can effectively query large masses of data. Businesses can quickly analyze large amounts of data and gain meaningful insights, helping to support decision processes.<\/p>\n\n