{"id":5781,"date":"2015-11-30T16:51:35","date_gmt":"2015-12-01T00:51:35","guid":{"rendered":"http:\/\/www.ramonchen.com\/?p=5781"},"modified":"2023-05-29T19:36:04","modified_gmt":"2023-05-30T03:36:04","slug":"why-life-sciences-must-go-beyond-mdm","status":"publish","type":"post","link":"https:\/\/www.ramonchen.com\/?p=5781","title":{"rendered":"Why Life Sciences Must Go Beyond MDM"},"content":{"rendered":"

Originally Published at Reltio.com\/blog<\/a><\/p>\n

Many of the\u00a0team here at Reltio<\/a>\u00a0formed the nucleus of Siperian (acquired by Informatica in 2010<\/a>), the leading on premise MDM tool widely adopted\u00a0by\u00a0life sciences companies. Back in 2005, master data management \u00a0(MDM) was just taking shape and companies used MDM primarily to improve\u00a0Siebel CRM data quality before upgrading and migrating their on premise systems. Back then Siperian was preferred by many to the “seamlessly integrated Siebel Universal Customer Master (UCM)” offering, proving that best-of-breed solutions can be superior to integrated offerings that are designed for a single primary purpose.<\/p>\n

One of the biggest issues we faced with Siperian (now Informatica MDM) was defining a relational life sciences data model that could capture not only the basic attributes of healthcare professionals and organizations, but represent real-world \u00a0HCP-to-HCP, HCO-to-HCO and HCP-HCO relationships.\u00a0Also thrown in for good measure was an emerging need to master product data, product hierarchies, groups and baskets for pricing and competitive analysis, and to feed product information (PIM) systems.<\/p>\n

At Siperian we admittedly struggled with basic hierarchy management and performance issues with merge and especially unmerge. While we preached multi-domain and coined the term Universal MDM, we were never completely successful with standalone product master data management, let alone bringing together both customer and product data into a single consolidated Siperian Hub.<\/p>\n

Back then, the best databases we had to model and store life sciences entities and their relationships were the likes of Oracle, DB2 and SQL Server. Cloud and big data technologies such as graphs, columnar stores, HBase (on Hadoop) and Cassandra simply weren’t available.<\/p>\n

Fast forward to the present, the MDM landscape remains more or less unchanged despite a quantum leap in technology.<\/p>\n