Without clear understanding of the data, it is very difficult to collect clear requirement and set both specifications and expectations. Data must be clearly defined and understood to be leveraged by any platform.
It is true that a proper understanding of requirements and specifications is necessary for the success of a business analytics project. This would ensure that the analyst and the client are on the same line of thought before the project starts. Clear understanding of the data is also a must, since it is impractical to provide an analytical solution using data which you do not understand.
Project scope creep (assuming clear expectations and corresponding specifications) is the biggest risk. If all of the important pieces are covered, scope creep can cause delay, missed development milestones, design flaws and an ultimately late, over budget and incomplete project.
The writer does not seem to have an understanding of project scope creep. Scope creep occurs when the scope of a project changes, in most cases grows, during development. With objectives and requirements properly specified at the beginning of the project, this should not be an issue
a) A clear ability to translate and interpret business requirements into technical ideas: I have found that this soft skill is absolutely necessary in the age of portable, mobile, agile and high volume analytics. There is no really ability to encapsulate technical staff from business users and the direct communication between the two can heavily influence success and trust.
b) A solid understand of SQL(and NoSQL methods if appropriate), data relationships, and basic database design: all solid analytics professionals should have good SQL skills and a solid ability to explore, understand and prototype data. This gives them a significant head start when discussing and analyzing requirements and designs.