Efficient data management

Efficient data management (EDM)

This trai­ning cour­se offers a prac­ti­ce-ori­en­ted intro­duc­tion to the basics of data cle­an­sing and pre­pa­ra­ti­on in sta­tis­tics and data mining. A well-known rule of thumb in the ana­ly­sis busi­ness is that about 80% of the effort is spent on data cle­an­sing and pre­pa­ra­ti­on. From many years of expe­ri­ence with cus­to­mer pro­jects, Stat­Soft knows the typi­cal hurd­les that need to be over­co­me for a suc­cessful ana­ly­sis. The cour­se pro­vi­des a prac­ti­cal over­view of the important steps in data manage­ment.

Con­tents

• Typi­cal errors in data
• Miss­ing data and out­liers
• Dis­tri­bu­ti­on tests and trans­forming
• Rele­vant influen­cing varia­bles
• Opti­mal samples
• Under­stan­ding data using gra­phics

Type
Our method trai­ning cour­ses are desi­gned to be soft­ware-inde­pen­dent and cross-indus­try. We attach gre­at importance to a lively and inspi­ring atmo­sphe­re in the trai­ning and the­r­e­fo­re pre­sent examp­les from various appli­ca­ti­on are­as; soft­ware may also be used.

The cour­se is open to dis­cus­sion and con­tri­bu­ti­ons from par­ti­ci­pan­ts. Our trai­ners respond to all ques­ti­ons from par­ti­ci­pan­ts and ans­wer them at appro­pria­te points during the cour­se.

Par­ti­ci­pan­ts will recei­ve all trai­ning docu­ments in PDF for­mat after­wards.

Key­words
⁸⁰⁄₂₀ rule, out­liers, data explo­ra­ti­on, data errors, data visua­liza­ti­on, miss­ing values, samples, varia­ble weight­ing, dis­tri­bu­ti­on, dis­tri­bu­ti­on tests

Pre­re­qui­si­tes
This cour­se requi­res basic sta­tis­ti­cal know­ledge.