Analytics as Data Science

We concluded with fair reasonableness in the inaugural post on Analytics Audit that following a Typical Analytics Projects Approach should lead to scientifically verifiable results. Thus, we refer to Analytics as a Data Science stream in contrast to a Data Visualization stream! Since visualization is a creative stream, akin to Art and may take some liberties as to how data is being presented and how deductions are being drawn.

Analytics as a specialized field has been in the making for some time. Various experts define an Analytics professional in different terms, without a coherent approach towards what she is expected to do. Though the EDISON project is an effort towards building the Data Science profession. Thus, a nomenclature of a Data Scientist is emerging, with their associated skill-sets being defined. But here also, the quality of data science work can be judged only by the credentials of the person executing the task, and not with any objective standards, or dispassionate rigor. Even though the Data Science Professional Profiles document seeks to extend ESCO (European Skills/Competences, qualifications and Occupations) framework, it still does not consider an auditor’s role in the whole scheme of Analytics professionals’ profiles.

Since long, we have acknowledged the need for checks and balances in the form of internal and external audits in Accounting profession, even when the accounts are prepared by equally qualified and certified professionals, through adhering to the rules, regulations and commonly accepted Accounting principles. Just like in Accounting, Analytics projects, having data science professionals working with data and human ingenuity, need checks and balances through an independent validation of those projects, aka an Analytics Audit!

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