Advanced Guides
What Is a Data Warehouse? Architecture & Concepts
Data warehouse is a system for storing & reporting on data. It's built to support business' decision making & reporting. Learn more about the architecture.
read moreAn enterprise data warehouse (EDW) is a database that centralizes all of a company’s data in one place for reporting.
The information kept in an EDW typically originates in operational systems, such as ERP, CRM, and HR systems. The EDW empowers companies to aggregate and structure this data in a format that teams and employees across the company can use.
An enterprise data warehouse is used to store and report all of a business’s data, regardless of where the data originates from and what team or department will use the information.
In comparison, the data in a data warehouse may be specific to a single department or a line of business.
Businesses rely on useful, accurate data to make informed decisions about products, employees, customers, and more. Without quality data, company leaders must rely on their gut feelings to make these crucial choices.
EDWs empower business leaders to evolve past gut feelings and integrate data from multiple, unstructured sources into business intelligence and data visualization tools, such as Tableau, PowerBI, and Qlik. The tools then provide teams with quick, data-driven answers to pressing questions.
Enterprise data warehouses fall broadly under two categories — on-premises or “traditional” data warehouses and cloud data warehouses. Some organizations use a third type: virtual data warehouses.
On-premises data warehouses are primarily used within the company’s firewall. These include Teradata, Netezza, and Exadata. The on-premises data warehouses provide full control; however, the control comes with more responsibility. A traditional data warehouse needs a full tech stack and has to be maintained by database administrators, system administrators and network engineers.
Organizations have started investing heavily on cloud data warehouses. Cloud data warehouses are designed to provide scalability, elasticity and cost efficiency. Cloud data warehouses include Amazon Redshift, Google BigQuery, and Snowflake. With cloud data warehouses, organizations can purchase compute power and storage as needed. Plus, cloud data warehouses don't need additional tech resources and staff to manage the data.
Some organizations go with a third option called data virtualization. In this scenario, the data stays in the source systems and a virtual layer is created for data analytics and reporting. This can appear to be an easier and faster technique for getting started. However, data virtualization causes major performance issues at scale and has to rely on source systems for querying the data.
The data in enterprise data warehouses help companies answer specific business questions and make data-driven decisions. Enterprise data warehouses answer questions such as:
An enterprise data warehouse helps businesses answer questions that involve cross-organization data and teams. They can help elevate data-driven decision-making across the entire enterprise.
Dremio's forever-free lakehouse platform enables interactive BI and high-performing analytics directly on your cloud data lake. It opens up a broader set of data to a larger set of data consumers for diverse analytical needs. Learn more about how Dremio complements your data warehouse.
Data warehouse is a system for storing & reporting on data. It's built to support business' decision making & reporting. Learn more about the architecture.
read moreThis article will focus on a comparison between Data Lakes and Data Warehouses, examining the similarities, differences, and pros and cons of each. You may also want to cover potential use cases, costs, industries that could benefit, etc.
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