Data warehouse processes, transforms, and ingests data to fuel decision-making within an organization. Data warehouse solutions act as a singular central repository of integrated data from multiple disparate sources that provide business insights with the help of big data analytics software and data visualization software. Data within a data warehouse comes from all branches of a company, including sales, finance, and marketing, among others.
Data warehouses can combine data from CRM automation tools, marketing automation platforms, ERP and supply chain management suites, and more, to enable precise analytical reporting and intelligent decision-making. Businesses may also use predictive analytics and artificial intelligence (AI) tools to pull trends and patterns found in the data. A critical capability of a data warehouse includes its ability to integrate with third-party business Intelligence software, data lake, data science workflows and machine learning, and AI technology.
Data warehouses are used in a diverse set of industries, including banking, finance, healthcare, insurance, and retail. Deployment models of a data warehouse include on-premises, private cloud, public cloud, and hybrid cloud. A modern cloud data warehouse is capable of handling a massive amount of complex data, can instantly be scaled up or down based on the business needs, perform rapid advanced analytical queries, and contain limited infrastructure setup costs.
To qualify for inclusion in the Data Warehouse category, a product must:
Contain data from several or all branches of a company
Integrate data prior to going into the data warehouse through an extract, transform and load (ETL) process
Allow users to perform queries and analyze the data stored inside the data warehouse
Offer multiple deployment options
Integrate with third-party reporting and business intelligence tools
Serve as an archive for historical data
