A lire sur: http://it.toolbox.com/blogs/inside-erp/what-big-data-mining-means-for-erp-59295
Enterprise resource planning (ERP) software allows a business to consolidate previously separate data into a single application. This means that finance, sales, production, and other business functions use the same application, and the data for that application are in a single database. This has several implications. Because all of the data are stored in the same place, it is much easier to analyze data from multiple business functions. Because so much more data are in the same place, new tools are needed to analyze the data.
What is Big Data?
Big data simply refers to data sets that are too large to be stored or analyzed using traditional tools. Big data has become more and more important over the past several years as more data are collected on a regular basis. To understand what big data means, it must be analyzed. That is done using data mining.
What is Data Mining?
Data mining is the application of a wide variety of statistical techniques to big data sets. Data mining is usually used to predict outcomes or events, but it is also useful to detect trends.
Data mining is crucial in today’s business environment. It allows a business to extract the most information from its data. This, in turn allows the business to make better decisions and forecasts. Businesses that are not mining their data are losing out on a chance to leverage what they already have; the competition is not making that mistake.
Because ERP software combines the information from several areas—finance, sales, production—it is a vein of data gold for the business to mine. Most major ERP vendors, such as SAP and Sage, offer add-ons or other products that can be used to mine ERP data. Others provide built-in functionality for many data-mining techniques.
ERP data can be mined in a variety of ways, depending on the use case.
Predictive modeling can be used to forecast future events and trends, such as the demand of a product. This technique can leverage data from sales and production to create better models of how much product a business may need at any given time. It can also be used to determine which first-time customers will be likely to remain customers and which will not. By predicting future outcomes, the business has more information with which to make decisions about strategy. Leveraging the data in the ERP system through data mining improves those decisions greatly.
Clustering can be used to find like groups of things. This technique is similar to segmentation, but unlike segmentation, where the user predefines the groups into which that things will be placed, clustering uses mathematical and statistical algorithms to determine what belongs in which group. This allows the data to speak for itself, relying on the preconceived ideas of the relationship between things. Clustering can be used for many things, such as suggesting and advertising future products.
Big data mining allows a business to leverage the data it is currently storing in its ERP system to make decision and improve processes. The combination of ERP and big data mining means more money through reduced costs or increased sales for the user.
About the Author
Christopher Louden is from San Antonio, Texas. He is a writer and biostatistician who loves working at the intersection of technology and science as well as an analyst with Studio B.