Data is the compilation of information in the form of written texts, figures, symbols, numbers, or even those passed down from one generation to another through word of mouth. Often considered the be-all and end-all resource connecting the past, present and future, we all look up to data when faced with some of the most complex problems whether in business or in life. In today’s fast paced internet age companies invariably collect data, but mostly with the primary aim of staying ahead of the competition by deriving insights on their products, customers, market share, cash flow, and future areas of innovation and growth.
Data like every other resource, however, first needs to be evaluated, adapted, and used judiciously. The journey of data from information (structured and unstructured) to insights is a difficult one to navigate. Along this path lies hurdles associated with source, sampling, biases, formats, treatments, analyses, errors, and those of interpretation based on contextual relevance. DATA, in short, has to be determinable, analyzable, translatable and applicable!
Having worked with DATA of all types, scales and complexities first hand, we understand and respect the power of these four letters. Whether it is a dataset of few Petabytes in Astronomy, or a sample population of several hundred in quantitative Genetics, or the credit risk score of an individual who just applied for an unsecured personal loan, to goods changing hands on an e-commerce platform with millions of transactions taking place simultaneously, the purpose of data is always to deliver a product or outcome that is credible, superior and acceptable. Data is the means to an end and not the end in itself. Data strategy and Business strategy, therefore, cannot and must not exist independently of each other.