What is a Data Warehouse?
An Enterprise Data Warehouse, commonly referred to as a data warehouse, is a single, centralized repository for storing persistent and structured information. A data warehouse is an enterprise-wide repository of historical data that comes from different sources across an organization. Each type of data commonly resides in a separate database or storage area but ends up in the same place for analysis purposes. They're the core of what businesses need to function both on the day-to-day and for making decisions across job functions in the future.
Data Warehouse vs Database
Data warehouses collect and store an organization’s raw data. They are used by data stewards to conduct analyses, create reports and make confident decisions that impact the business as a whole. A data warehouse is a database management system (DBMS) that’s customized for data warehousing. It uses the concepts of data virtualization, while maintaining flexibility in its functionality. Data warehouses can be categorized based on their implementation into two types: centralized and distributed architecture, as well as three types: Extract-Transform- Load (ETL), Hybrid, and in-memory.
A database, on the other hand, has no other purpose but to record information and actions. It typically only pulls information from one source, and is limited in what you can "ask" it, or query. Data warehouses are for recording and analyzing information, and are much more complex in where they store information and what queries you can make.
Understanding the value
As businesses grow and scale, so does the need to make data-backed decisions. With a data warehouse, businesses can gleam insights that impact all job functions- engineering, product, marketing, and business development. It also acts as a place that houses all sources of information from these various functions, as opposed to relying on multiple sources of truth.
With a data steward maintaining your data warehouse, you'll be able to create models to analyze past trends and predict future ones. It also allows for data analysis in a fast and efficient manner if managed properly.
How does a data warehouse work?
A data warehouse (DW) is a storage system for analyzing very large amounts of data for reports, dashboards, and analytical readouts. They first begin with the collection of data from multiple sources. Once the data is collected, it's stored in the warehouse, sorted by which fields, parameters, and layout the data steward has put in place. That same data steward will be responsible for asking the data warehouse questions, or queries, based on requests from other members in the organization.
Examples
Data warehouses play a pivotal role in modern data-driven businesses by consolidating and optimizing data for analytical purposes. For instance, Amazon Redshift is a widely used data warehouse service that helps organizations analyze large datasets to gain insights into customer behavior, sales trends, and inventory management. Retail giant Walmart utilizes Teradata for its data warehousing needs, allowing them to track inventory levels, optimize supply chains, and improve customer satisfaction through data-driven decision-making. In the healthcare sector, Kaiser Permanente relies on Snowflake's data warehousing capabilities to securely store and analyze patient records, enabling them to enhance healthcare outcomes and resource allocation. These examples illustrate how data warehouses empower organizations across various industries to extract valuable insights from their data for informed decision-making, ultimately driving growth and efficiency.
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