ETL-what can customers bring

What does the ETL data conversion system bring to customers?
With the development of society and computer technology, people began to reprocess the data in the original database to form a comprehensive and analysis-oriented environment to support the emergence of scientific decision-making. As a result, the ideas, technologies, and products of data warehouses are gradually formed. The purpose of building a data warehouse is to establish a systematic data storage environment and separate the large amount of data required for analysis and decision-making from the traditional operating environment, converts scattered and inconsistent operation data into integrated and unified information. Different units in an organization can use the data and information in a single environment, discover new perspectives, new problems, new analysis and ideas, develop an institutionalized decision-making system, and obtain more operational benefits. The data warehouse provides the current and historical data used by users for decision-making support. This data is difficult or cannot be obtained in traditional operational databases.

To build an enterprise data warehouse, you need to regularly and batch load all types of data in the enterprise to the Data Warehouse after necessary conversion and arrangement. Because enterprises have diverse data sources and different data sources have different standards, data conversion, sorting, and loading require a complete and powerful software system, this requires the ETL tool.

ETL solves the following problems:
(1) ability to read data from various data sources. You can use SQL Server, Oracle, access, and other common data source connections to directly obtain data from the data source. The system also provides powerful scalability, for DBF, Excel, text files and other forms of flat files, the system can add various data sources at any time as needed.

(2) standardized data access interface. Data acquisition in the ebuilder data conversion system is diversified, and all data processing is accessed through standard data interfaces, ensuring the free conversion and storage of data in Heterogeneous Database environments.

(3) visualized data extraction process definition. The data extraction process is the bottom layer of the abstract database. The ebuilder data conversion system provides a complete definition of the visual data extraction process, which greatly reduces the threshold for data extraction process design, this not only improves the efficiency of the design data extraction process, but also makes the data extraction process more secure and reliable.

(4) integrated database modeling capabilities for building data warehouses. Data warehouse construction is not completed overnight, but requires iterative processes such as cyclical addition and modification. Therefore, the ability to integrate database modeling in ETL is crucial. ETL integrates database modeling capabilities in the background. You can create data tables in the database based on the user-generated result set, the data warehouse modeling does not fail in the data extraction process because of the mismatch of field types.

(5) detects changes in the business database for data updates. The data in the data warehouse comes from the business database, and the Business Database generally does not retain the addition, deletion, and modification operations on the data. It is unrealistic to clear the data in the data warehouse every time, this requires that the Data Extraction Tool can automatically detect changes in the business database, add, delete, and modify data in the business database, and extract the data in the form of incremental files.

(6) The database extraction can be automatically performed on a regular basis. Once the configuration is complete, no manual intervention is required. Data in a data warehouse is loaded in batches, which takes a lot of time and puts pressure on the operation of the business database. Therefore, the data extraction process must be executed within the idle time of the Business Database. ETL provides complete task scheduling capabilities. You can set the data extraction process to run automatically at idle time based on the running rules of the Business Database.

(7) once the data warehouse of a unit is built, you can start to build applications based on the data warehouse, such as OLAP. The next step is to bring practical benefits to the Unit's decision-making: save time and may explore ideas you never thought about, such as stories about beer and diapers. It will bring practical benefits to your organization, and the ultimate goal of formal informatization of benefits!