acquisition life cycle model overview
Data warehouses are designed to provide an overview of data from business over time, by combining huge amounts of current and historical data into a single repository. Data warehouses also provide value to the operations of applications by transforming and optimizing data for analytical use. They are therefore the mainstay for business analytics and enterprise Intelligence.
Online data warehouses are accessible via the cloud, and provide more information for business users. Businesses can also make use of them to connect to new data sources and apps without requiring IT intervention or manual configuration.
The best online data warehouses support a wide range of data types and scenarios. Some are suitable for the analysis of unstructured information like videos and text. But they work best with structured data that is organized in a specific way (e.g. tables,).
Modern data warehouses also allow users to define relationships between their tables and data sets. This allows you to explore and share information with colleagues on data in a secure, governed environment.
Amazon Web Services’ Redshift and Snowflake are among the most popular online data warehouses. Other vendors include Google Cloud Platform BigQuery and Microsoft Azure SQL Data Warehouse. These solutions can be scalable to an almost infinite extent, so they can handle large amounts of activity without overloading CPUs or consuming a lot of storage. They are especially well-suited for the ELT process (extract load transform) in which business analysts and users of business intelligence turn raw data into an easier form that can be analyzed.
