Data Warehouse (Cont.)
Data Warehouse vs Database
A database is built primarily for fast queries and transaction processing, not analytics.
A database typically serves as the focused data store for a specific application, whereas a data warehouse stores data from any number (or even all) of the applications in your organization.
A database focuses on updating real-time data while a data warehouse has a broader scope, capturing current and historical data for predictive analytics, machine learning, and other advanced types of analysis.
Benefits of a Data Warehouse
A data warehouse provides a foundation for the following:
- Better data quality:
A data warehouse centralizes data from a variety of data sources, such as transactional systems, operational databases, and flat files.
It then cleanses it, eliminates duplicates, and standardizes it to create a single source of the truth.
- Faster, business insights:
Data from disparate sources limit the ability of decision makers to set business strategies with confidence.
Data warehouses enable data integration, allowing business users to leverage all of a company’s data into each business decision.
- Smarter decision-making:
A data warehouse supports large-scale BI (business intelligence) functions such as data mining, artificial intelligence, and machine learning—tools data professionals and business leaders can use to get hard evidence for making smarter decisions in virtually every area of the organization, from business processes to financial management and inventory management.
- Gaining and growing competitive advantage:
All of the above combine to help an organization finding more opportunities in data, more quickly than is possible from disparate data stores.