The last several years have seen an explosion of interest in Analytics, as more-and- more organisations attempt to become “data-driven”. However, managers and technologists sometimes fail to appreciate that Data Science is more like research and development than it is like software engineering. In this presentation, we will: introduce the three central concepts that underpin Data Science discuss; briefly review the process of extracting insights from data, in order to understand the consequences of the iterative nature of the discipline; and provide real-world examples of Analytics in action that demonstrate the commercial value of Data Science.
- The analytical process has more in common with R&D than with Software Engineering
- The importance of discovery, truth and utility in analytics
- The role of “multi-genre analytics” in constructing a robust analytic pipeline
- Digitise – or die!