Data Warehouses and Data Mining
This article gives a detailed summary of the role of data warehouses and data mining, and their relationship to organizational databases. As you read, pay attention to how data warehouses are used to improve decision-making in organizations. Keep a summary in your notes of how an organization you are involved with could benefit from data mining and data warehousing.
The term "big data" is relatively new, the act of gathering and storing large amounts of information for eventual analysis is ages old. Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, search, sharing, storage, transfer, visualization, and querying and information privacy. The term often refers simply to the use of predictive analytics or certain other advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making, and better decisions can result in greater operational efficiency, cost reduction, and reduced risk. Definition of big data as the three Vs:
- Volume: Organizations collect data from a variety of sources, including business transactions, social media, and information from sensor or machine-to-machine data
- Velocity: Data streams in at an unprecedented speed and must be dealt with in a timely manner.
- Variety: Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data, and financial transactions.