What is a data warehouse? A data warehouse, sometimes categorized as an Enterprise Data Warehouse, (DW or DWH) is a data analysis and reporting system. Data warehouses are fundamental storehouses of integrated data from single, or multiple sources, storing historical or current data in one location where data is utilized, creating reports for designated Enterprise users.
A DW is considered an integral component of business intelligence and describes a system used to analyze an organization's raw data. The data warehouse oversees the performance of a business database and monitors its agility when loading and retrieving data.
IT professionals on PeerSpot have certain core requirements when looking at the integration of a data warehouse. Some of these include which analytical capabilities are supported. For example, support of SAP HANA is viewed as a plus because it has necessary, analytical layers built within the data warehouse.
Other important criteria include the variety of supported data, structured and unstructured, and how they co-exist among various big data solutions. There are options where a data warehouse would have the capability to integrate or support other data management solutions. The inclusion of ETL tools, with extensibility, is always a preference in the data warehousing solution.
Some IT and DevOps professionals see data warehousing address both business and technical requirements because of the evolution from high-powered databases, with storage locally or in the cloud, (enhanced storage) to significant Enterprise information management solutions. Certain warehouse data is transferred from dedicated systems, such as sales or marketing. Data may be cleansed to ensure the quality of data before using it for reporting purposes.
Hence, ease of using in finding and retrieving data is essential. For data warehousing, IT and DevOps are focused on the total cost of ownership, scalability and performance features such as in-memory architecture, and row-based optics versus columnar or parallel processing. Storage optimization is key for data compression capability and caching. Of course, security and compliance for regulated organizations need support for data access control, masking, and auditing.
A data warehouse serves as a central repository for information that flows into it from various databases. The data is then processed, standardized, and merged so that it can be accessed by users in spreadsheets, SQL clients, and business intelligence tools. Once all of the data is compiled in one place, organization executives can analyze it and mine the data for patterns that will assist in making business decisions.
Data warehousing is used in many sectors, including:
Data warehouses and databases are both used for storing data. A database is used to store a large amount of real-time information, such as which items are in stock or have been sold. It processes your company’s daily transactions via simple queries. A data warehouse (DW or DWH) compiles historical (not current) data from multiple sources within your organization, handling complex queries which are used to create and analyze reports and then extract insights and make business decisions.
Databases and data warehouses process data differently. Databases use OLTP (online transactional processing) to quickly update a large amount of simple online transactions. OLTP responds immediately and therefore is useful in processing real-time data. Data warehouses, on the other hand, use OLAP (online analytical processing) to analyze large amounts of data and find out trends from them, such as how much is sold each day.
There are three main kinds of data warehouse:
1. Enterprise Data Warehouse (EDW). This is a centralized warehouse that offers a unified approach for representing and organizing data. It allows data to be classified according to subject and helps executives to make tactical and strategic decisions.
2. Operational Data Store (ODS). This database integrates data from various sources for operational reporting and decision-making, and complements the EDW.
3. Data Mart. This subset of the data warehouse is specially designed for use by a specific department within the business, such as sales or finance, and can collect data directly from the sources.
The benefits of a data warehouse include:
A data warehouse serves as a central repository for information that flows into it from various databases. The data is then processed, standardized, and merged so that it can be accessed by users in spreadsheets, SQL clients, and business intelligence tools. Once all of the data is compiled in one place, organization executives can analyze it and mine the data for patterns that will assist in making business decisions.
Data warehousing is used in many sectors, including:
Data warehouses and databases are both used for storing data. A database is used to store a large amount of real-time information, such as which items are in stock or have been sold. It processes your company’s daily transactions via simple queries. A data warehouse (DW or DWH) compiles historical (not current) data from multiple sources within your organization, handling complex queries which are used to create and analyze reports and then extract insights and make business decisions.
Databases and data warehouses process data differently. Databases use OLTP (online transactional processing) to quickly update a large amount of simple online transactions. OLTP responds immediately and therefore is useful in processing real-time data. Data warehouses, on the other hand, use OLAP (online analytical processing) to analyze large amounts of data and find out trends from them, such as how much is sold each day.
There are three main kinds of data warehouse:
1. Enterprise Data Warehouse (EDW). This is a centralized warehouse that offers a unified approach for representing and organizing data. It allows data to be classified according to subject and helps executives to make tactical and strategic decisions.
2. Operational Data Store (ODS). This database integrates data from various sources for operational reporting and decision-making, and complements the EDW.
3. Data Mart. This subset of the data warehouse is specially designed for use by a specific department within the business, such as sales or finance, and can collect data directly from the sources.
The benefits of a data warehouse include:
