The recent buzz about chief TLA’s (three-letter-acronyms), specifically Chief Data Officers (CDO) is in my opinion similar to a Chief Customer Office (CCO). Both roles should fall in existing corporate domains, either IT or Sales and Marketing. If an enterprise does have a CCO, the lead data role could just as easily fall under them.
What really matters is the value of data as a corporate asset. While ITconnecter will continue to harp on IT’s 3 key pillars (data, process and integration), if IT is not being run using the “business of IT” model, IT risks losing another strategic technology leadership role, that of data officer.
The best way to establish the leadership role in enterprise data? Start by reading this Best’s Review article (“All About the Data”, 2nd article at http://www.itconnecter.com/technology-articles/) and then take ITconnecter’s “agile MDM” challenge. The “agile MDM” challenge is simple: in the next 3 months, start implementing agile Master Data Management (MDM) within your enterprise.
If scoped and implemented properly, ITconnecter GUARANTEEs you will win a TDWI Best Practice Award (see below). Don’t believe it? Take ITconnecter up on this and we’ll volunteer our time to help you make it happen…
From “Recognition for BI/DW Implementations –TDWI -The Data Warehousing Institute” via Recognition for BI/DW Implementations — TDWI -The Data Warehousing Institute.
Enterprise Data Management Strategies – The data that goes into solutions for BI and DW is only as good as the data management solutions that collect, aggregate, and improve the data. The same is true of many operational and transactional applications. Whether for BI/DW or operational systems, enterprise data management strategies involve a long list of disciplines: data integration, data quality, data profiling, master data management MDM, event processing, database administration, and many more. TDWI is interested in uses of these and other DM disciplines that push the envelope with real-time operation, system interoperability, multi-structured data types, and very large data volumes. Equally of interest are organizations that coordinate data standards, governance, and team productivity across multiple DM disciplines, as well as innovations in data architecture.