Data Warehouse Stocks List
Symbol | Grade | Name | % Change | |
---|---|---|---|---|
TDC | D | Teradata Corporation | 1.33 | |
HCAT | D | Health Catalyst, Inc. | 4.08 | |
INFY | C | Infosys Limited | -0.14 | |
SNOW | B | Snowflake Inc. | 31.64 |
Related Industries: Data Storage Health Information Services Information Technology Services Software - Application
Symbol | Grade | Name | Weight | |
---|---|---|---|---|
FNGD | F | BMO REX MicroSectors FANG Index -3X Inverse Leveraged Exchange Traded Notes | 9.1 | |
DGIN | D | VanEck Digital India ETF | 7.61 | |
CIBR | B | First Trust NASDAQ CEA Cybersecurity ETF | 7.06 | |
DAT | B | ProShares Big Data Refiners ETF | 7.01 | |
RVER | A | Advisor Managed Portfolios Trenchless Fund ETF | 5.29 |
Compare ETFs
- Data Warehouse
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis, and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise.The data stored in the warehouse is uploaded from the operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the DW for reporting.
The typical extract, transform, load (ETL)-based data warehouse uses staging, data integration, and access layers to house its key functions. The staging layer or staging database stores raw data extracted from each of the disparate source data systems. The integration layer integrates the disparate data sets by transforming the data from the staging layer often storing this transformed data in an operational data store (ODS) database. The integrated data are then moved to yet another database, often called the data warehouse database, where the data is arranged into hierarchical groups, often called dimensions, and into facts and aggregate facts. The combination of facts and dimensions is sometimes called a star schema. The access layer helps users retrieve data.The main source of the data is cleansed, transformed, catalogued, and made available for use by managers and other business professionals for data mining, online analytical processing, market research and decision support. However, the means to retrieve and analyze data, to extract, transform, and load data, and to manage the data dictionary are also considered essential components of a data warehousing system. Many references to data warehousing use this broader context. Thus, an expanded definition for data warehousing includes business intelligence tools, tools to extract, transform, and load data into the repository, and tools to manage and retrieve metadata.
Recent Comments
- TraderMike on BOOT
- Dr_Duru on BOOT
- TraderMike on Stochastic Reached Oversold
- SuccessfulGrasshopper897 on Stochastic Reached Oversold
- Cos3 on Adding float as advanced filter criteria?
From the Blog
Featured Articles