When It Comes to Data Quality Delivery, the Soft Stuff is the Hard Stuff (Part 1 of 6) by Richard Trapp.
From the post:
I regularly receive questions regarding the types of skills data quality analysts should have in order to be effective. In my experience, regardless of scope, high performing data quality analysts need to possess a well-rounded, balanced skill set – one that marries technical “know how” and aptitude with a solid business understanding and acumen. But, far too often, it seems that undue importance is placed on what I call the data quality “hard skills”, which include; a firm grasp of database concepts, hands on data analysis experience using standard analytical tool sets, expertise with commercial data quality technologies, knowledge of data management best practices and an understanding of the software development life cycle.
Read Richard’s post to get the listing of “soft skills” and evaluate yourself.
I am going to track this series and will post updates here.
Being successful with “big data,” semantic integration, whatever the next buzz words are, will require a mix of hard and soft skills.
Success has always required both hard and soft skills, but it doesn’t hurt to repeat the lesson.
