Enter­pris­es tack­ling the dig­i­tal trans­for­ma­tion chal­lenge with Indus­try 4.0 will lever­age IoT to enable them to react to changes in busi­ness oper­a­tions in real time. Time­series data plays a big role in real­iz­ing the val­ue of IoT and is used in SAP Line of Busi­ness appli­ca­tions to cre­ate pre­dic­tive mod­els for asset main­te­nance, inven­to­ry man­age­ment or man­u­fac­tur­ing operations.

Insights gleaned from IoT and busi­ness process data will enable data dri­ven deci­sion mak­ing from the shop floor super­vi­sors to the c‑level exec­u­tives. Since IoT data and its stor­age is crit­i­cal to automat­ing busi­ness process­es, SAP believes that cus­tomers of its busi­ness appli­ca­tions should have the choice to use SAP’s data stor­age or to bring spe­cif­ic non-SAP data lakes to store time­series data.

In this ses­sion, we will cov­er the func­tion­al­i­ty and high-lev­el archi­tec­ture of the SAP IoT data lake abstrac­tion lay­er, which enables SAP busi­ness appli­ca­tions to lever­age IoT data regard­less of where it resides, with­out devel­op­ing code or chang­ing access patterns.