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Data Warehouse and Machine Learning

Machine learning is a trend in modern-day warehousing, which computes store large amounts of data from various sources. The reason for data warehousing is because machine learning works best when more data is fed to it.

Characters of a Data Warehouse

  • Bottom tier – consist of a server to collect, cleanse and transform data through Extract, Transform and Load (ETL) process.
  • Middle tier – it consists of online analytical processing (OLAP) which is the reason for fast query speeds.
  • Top tier – is a front end user interface that is responsible for ad-hoc analysis of the business data.

Benefits of a Data Warehouse in Machine Learning

Data warehouse serves the following functions in machine learning:

BenefitDescription
Better data qualitySourcing its data from various sources like operational databases and transactional systems, cleanses the data, gets rid of the duplicates and standardizes to get a single source of truth.
Faster Business InsightsData warehouses allow organizations to leverage all company’s information into each implementation step through data integration.
Smarter Decision-MakingData warehouse supports large scale functions like data mining, machine learning tools and artificial intelligence. These can be used to arrive at hard evidence that will help in business make decisions businesses processes and financial management.
Better Competitive AdvantageCombined, the above functions will bring opportunities found in data faster.

Topics in Machine Learning

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