Data Management Literacy
Educating organization’s stakeholders on the key Fundamentals on Data Management is one of the key, possibly the most important, living principle of ThriveOnData LLC. Including Education-oriented, with content tailored to specific audiences in terms of complexity and building knowledge incrementally, sessions and other activities on Business Process Transformation Initiatives is one of our key differentiators.
About
Enterprise Data Management Key Disciplines
Instilling and growing an organizational Data Management culture so businesses are able to nurture their data assets towards competitiveness and profitability rests on ensuring multiple stakeholders understand the overarching, umbrella framework of Enterprise Data Management. Enterprise Data Management (EDM) is a set of Disciplines including methods, processes, standards, policies, procedures and tools to allow treatment, management, usage of data assets (IE: Master Data such as Customer, Vendor, Products Master Data and Transactional such as Sales and Purchase Orders) to the advantage, strategic goals achievement, cost effectiveness and profitability for the organization. EDM derives into multiple sub-disciplines as laid-out on the right
Enterprise Data Governance
Data Quality
Data Conversion
Master Data Management
Data Architecture
How
Our Leadership Testimonial on Effective Management of Data Tracks on Transformation Efforts
Be on the look for a soon upcoming publication, below, of a Testimonial from ThriveOnData LLC President and CEO on the Key Success Drivers and Factors behind effectively managing organization’s Transformation Initiatives Data Tracks…
TESTIMONIALS
Interesting Quotes on Data Management…
As per my multi-decade experience relating to Data matters, Non-Technical efforts while delivering Data Management solutions such as involvement of business stakeholders and process experts amount roughly to 80% of the overall effort hours devoted to a Data track on a Program”
On Organization’s Transformation Initiatives, Process Solutioning Design should be executed as in parallel as possible with Master and Transactional Data Definition Design so Data Quality, Conversion and Master Data Management (Sustainment) needs are identified as soon as possible”
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