Data infrastructure is the set of technologies and processes that enable organizations to collect, store, manage, and use data. Data infrastructure can be physical or virtual, centralized or decentralized, static or dynamic.
A modern data infrastructure typically includes a variety of components, such as data stores (such as databases), processing engines (such as analytics tools), communication mechanisms (such as APIs), and integration points (such as connectors). These components work together to provide an organization with the ability to collect, store, manage, and use data.
Data warehousing is a fundamental technology underpinning a modern infrastructure. Data warehousing is the process of transforming raw data into well-integrated information assets that can be used to support decision-making. Data warehousing can help organizations achieve three goals: insights generation, speed to action, and improved governance.
Insight generation refers to the ability of data warehousing solutions to generate meaningful insights from large volumes of data. By providing analysts with access to aggregated information across multiple tables and dimensions, data warehousing solutions can help identify patterns and trends in your data that may otherwise go unnoticed.
Speed to action refers to the ability of a good data warehouse solution to quickly provide business users with actionable insights about their business performance. By providing analysts with quick access to high-quality information within seconds instead of minutes or hours, a good data warehouse solution can help reduce decision time by enabling business users to make better decisions more quickly.
