What is a Data Warehouse? The Ultimate Guide to Data Warehouse Architecture

Data warehouses are a key component of many companies’ data management strategies. Data from multiple sources is combined and stored in a single place to support the analysis of company performance. A range of benefits can result from implementing a data warehouse, including improved performance monitoring and reporting, more informed decision-making, and enhanced analysis of market trends. Many different terms get used when talking about data warehouses. Here is our complete guide to help you understand exactly what a data warehouse is and what it can do for your business.

What is a Data Warehouse?

A data warehouse is a centralized repository of all company data. A company’s operational data (e.g., HR, accounting, sales) is extracted, cleansed, and stored in the data warehouse. Operational data is also called source data. The data warehouse is designed to enable easy reporting and analysis of this data. The data warehouse holds data in a standardized and structured format where operational data is often unstructured (i.e., in a format that isn’t easily readable by humans). This standardized format facilitates analysis, as data can be read and interpreted by computers. Data warehouses are the central location for storing data from many different sources. Data from operational systems such as ERP, CRM, supply chain management, and others are combined to create a single, unified data store. This allows relevant data from different systems and departments to be analyzed together to provide a holistic view of the business. Data stored in the data warehouse is often augmented with additional data that provides context. For example, data about a product’s sales performance might be combined with data about the product’s quality to give an overview of overall sales performance.

Why Is Data Warehousing Important?

A data warehouse is a key component of many enterprises’ infrastructure. It allows users to analyze information in a single place rather than having to track down data from many different sources. The data warehouse is a centralized storage area for data, combining information from many different departments, such as sales, marketing, and finance. Data stored in the data warehouse is often cleaned up and standardized in ways it wasn’t in its original source. Data warehousing is important because businesses increasingly collect data from various sources, like customer surveys and sensors. The data warehouse provides a central location for storing and accessing all of this information.

Different Types of Data Warehouses

● Transactional Data Warehouse - It houses data extracted from operational systems such as ERP (enterprise resource planning). It stores data about operational activities such as sales, production, and procurement. Transactional data is often unstructured, needing significant cleaning before being stored in the data warehouse.
● Analytical Data Warehouse - Analytical data warehouses hold summarized data (e.g. aggregated sales data by region). This summarized data is calculated from the raw data. This enables users to access data in a summarized format, which is much easier to work with than raw data.
● Hybrid Data Warehouse - This combines the features of both a transactional and analytical data warehouse. It typically houses both the summarized data in the analytical data warehouse and the raw data in the transactional data warehouse.

Data Warehouse Architecture

Data warehouses are large data stores that hold information from various sources. This includes both operational data from internal business systems (e.g. sales data) and external data (e.g. market research data). Data warehouses are designed to store massive amounts of data and facilitate subsequent data analysis. The sheer scale of data warehouses needs to be designed carefully. A poorly designed data warehouse can be costly to maintain, difficult to use, and provide misleading results. A well-designed data warehouse, on the other hand, can significantly boost business operations. A data warehouse usually has many components, including a data lake, data source, data pipe, business intelligence tools, data visualization tools, and data governance.

Key Elements of a Data Warehouse

● Data Store - The data store is a large database that houses all the data in the data warehouse. It organizes data into tables and columns, enabling it to access and analyze easily.
● Data Transformation - Data transformation involves taking data from its original source and cleaning it up so it can be properly stored in the data warehouse. This includes adding standard information (e.g. product name and price) and removing unneeded data (e.g. sensitive information).
● Data Warehouse Management System - Data warehouse management systems are the software that manages the data in the data warehouse. This includes managing updates and deletions to the data and making it available for authorized people to view.
● Data Discovery and Visualization Tools - Data discovery and visualization tools help people locate and analyze data stored in the data warehouse. They also help people understand the meaning behind the data and whether it is useful.

How to Build a Data Warehouse

The first step in building a data warehouse is deciding which data to store. Many companies decide to store all data, but managing this can be very difficult (and expensive). To choose what data to store, businesses should consider the following questions: What data is important for decision-making? What data is necessary for long-term strategy? What data is being collected (or could be collected)? Which data can be easily standardized? Which data can be easily pulled from existing systems? What should not be included in the data warehouse is just as important as what should be included. The following data should not be stored in the data warehouse:

● Unusable data: Data that can’t be used for analysis or decision-making is pointless.
● Sensitive data: Data that could be harmful if it ends up in the wrong hands should be removed.
● Irrelevant data: Data that isn’t relevant to long-term operations should not be stored in the data warehouse.

Summary

A data warehouse is a centralized repository of all company data. It holds both operational data (e.g. supply chain information) and external data (e.g. market research findings). A data warehouse is designed to enable easy reporting and analysis of this data. Data warehouses are the central location for storing data from many different sources so that it can be analyzed together. The data warehouse has several key components, including a data source, data transformation, and data warehouse management system. A data warehouse is a key component of many companies’ infrastructure because it allows users to analyze information in a single place rather than tracking down data from many different sources.