Data Lifecycle Management focuses on data governance, data cleansing and quality, and data stewardship. The rubric applies to articles that focus primarily on the high-level preparation, flow, and use of data through an organization, rather than with one single facet such as storage or analysis.
In the previous article, I discussed three models of your company that should inform and guide your efforts to transform: the four-level Logical Model, the… Read More »A Framework for Understanding Transformation–Part III
An organization has to go through a lot before finding the ideal human resource management solution suitable for their business. But let’s say after watching… Read More »Common Reasons Why Organizations Fail to Implement SAP SuccessFactors
In Part I of this series, we discussed the VUCA environment in which business are operating and the impact this has had and will continue… Read More »A Framework for Understanding Transformation–Part II
Introduction In Agile Enterprise Risk Management, Risk-Based Thinking, Multi-Disciplinary Management and Digital Transformation I focus on several topics tied to transformation. The overarching objective of… Read More »A Framework for Understanding Transformation–Part I
Predicting the length of time it will take to get a Machine Learning (ML) project into production can be tricky. If there is an issue,… Read More »Seven Rules for Delivering Machine Learning Projects on Time
