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In order to solve this problem, this article introduces the corresponding analysis and answer in detail, hoping to help more partners who want to solve this problem to find a more simple and feasible way.

Data warehouse

A data warehouse is a data center repository used to provide new business insights. These data represent a comprehensive and consistent view of the business. In general, these historical datasets have the following characteristics:

Topic-oriented: data warehouses usually provide specific topics or business requirements, such as sales or productivity.

Time-varying: the data are historic, so results can be analyzed in specific time frames, such as monthly or quarterly over the past two years. Enterprise data warehouses are usually provided by data encapsulated in a transactional system, in which only the most recent data is required. For example, a transaction system might reflect only the customer's most recent phone number, while the data warehouse would contain all previously used numbers.

Integration: the data warehouse integrates information from many different sources into the same view. For example, different stores may have different names for the same product, but they will still have the same inventory unit (SKU) or part number.

Non-volatile: the information stored in the enterprise data warehouse does not change. In order to maintain the integrity of historical data, it is read-only and never changes.

What kind of data is loaded into the data warehouse?

Business data operations are almost real-time, such as sales information captured from chain stores at POS terminals. The daily sales data are captured by the system and sent into the data file. These files are then managed by ETL (extract, transform, and load) software or scripts, or the data is "normalized" into fields that can be uploaded directly to the data warehouse table.

For example, a large retail chain will capture data on goods sold, such as salespeople, stores, time, payment methods, special offers or coupons, and so on. Another company may be more interested in collecting customer service activities for regular performance analysis.

Most of the stored data is relational. This means that the information exists in the form of numeric ID fields that can be linked to a single table, such as a product ID list of product names linked to text and a description of each different ID. This can save space in the enterprise data warehouse and provide more meaningful information in the data report.

The difference between data Warehouse and traditional Database

The database supports daily operations by capturing information, whether electronically or manually. These are also known as transaction or operational databases. They are mainly used to capture information from the source. The database also allows information to be edited to reflect changes in the real world more closely. They are optimized for data entry: coordinate small and frequent updates and additions. The data is organized into rows or individual records.

Although both systems can be used for reporting, data warehouses are designed to aggregate large amounts of fixed information. The information in a report that runs from transaction data may change.

Data warehouses are mainly used to report and analyze business operations in order to identify patterns. Information is usually extracted from one or more databases and becomes a historical record in the data warehouse. The data warehouse will reflect all changes. Most enterprise data warehouse solutions require that information be stored in columns or dimensions, such as time or location, to retrieve a series of units of measurement, such as dollars or quantities. This allows for an in-depth understanding of the details in the same reporting tool.

Data Mart

Smaller companies, or even large companies, when close to a particular data project, may divide the data into smaller, more limited data sets, known as "data marts". This can eliminate the operating expenses of too much or irrelevant information. Data Marts can be extracted from the data warehouse as needed, or exist separately.

New or small companies may not need to maintain data warehouses. But in large and medium-sized enterprises, transactional databases and data warehouses are usually used every day. The important difference is that enterprise data warehouse solutions are read-only and optimized to analyze growing business data to support business decisions.

This is the answer to the question about what the enterprise data warehouse is. I hope the above content can be of some help to you. If you still have a lot of doubts to be solved, you can follow the industry information channel to learn more about it.

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