Big Data
Big data is a term for data sets that are so large and complex that traditional data processing software is inadequate to deal with them. But it is not the amount of data what is important. It is what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
BIG DATA, BIG OPPORTUNITIES
Data sets grow rapidly, in part because the costs of sensing, storing and processing data have been consistently reducing. For that reason, the amount of data thats being created and stored on a global level is almost inconceivable, and just keeps growing. That means there is even more potential to find key insights from business information, but only a small percentage of data is actually analyzed.
Determine root causes of failures, issues and defects.
Detect fraudulent behavior before it affects your organization.
Calculate best routes for delivering products.
Predict diseases and personalized medicine and prescriptive analytics.
EXPANDING TO MRP II
Big Data was defined by Doug Laney as the three Vs: - Volume: Organizations can collect large amounts of data from a variety of sources, including business transactions, social media, information from sensors and machines, etc.
Velocity: Data is generated 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, financial transactions, etc.