What is a data warehouse?
A data warehouse, or enterprise data warehouse (EDW), is a system that aggregates data from different sources into a single, central, consistent data store to support data analysis, data mining, artificial intelligence (AI), and machine learning.
What are the common problems with data warehousing?
2. Hidden problems in source systems Hidden issues associated with the source networks that supply the data warehouse may be found after years of non-discovery. For example, when entering new property information, some fields may accept nulls, which may result in personnel entering incomplete property data, even if it was available and relevant.
What is IBM Watson Studio and IBM Data Warehouse?
And IBM Watson Studio, a data science and machine-learning offering, empowers organizations to tap into data assets and inject predictions into business processes and modern applications. For more information on data warehouses, sign up for an IBMid and create your IBM Cloud account.
What are the steps involved in data warehousing?
The following steps are involved in the process of data warehousing: Extraction of data – A large amount of data is gathered from various sources. Cleaning of data – Once the data is compiled, it goes through a cleaning process. The data is scanned for errors, and any error found is either corrected or excluded.
What is Citus and how does it work?
Citus is an open source extension that transforms Postgres into a distributed database. Because Citus is a Postgres extension, you can leverage the Postgres features, tooling, and ecosystem you love.
What is the VA Corporate Data Warehouse (CDW)?
The Department of Veterans Affairs (VA), Office of Information & Technology, has the mission to provide a high-performance business intelligence infrastructure through standardization, consolidation and streamlining of clinical data systems. Toward this end OI has built the Corporate Data Warehouse (CDW) and 4 Regional Data Warehouses (RDW1-4)
How do I Choose an enterprise data warehouse?
To choose an enterprise data warehouse, businesses should consider the impact of AI, key warehouse differentiators, and the variety of deployment models. This ebook helps do just that.