Creating an Information Edge with Conversational Access to Data

As our world is getting more global and dynamic, businesses are more and more dependent on data for making informed, objective and timely decisions. However, as of now, unleashing the full potential of organisational data is often a privilege of a handful of data scientists and analysts. Most employees don’t master the conventional data science toolkit (SQL, Python, R etc.). To access the desired data, they go via an additional layer where analysts or BI teams “translate” the prose of business questions into the language of data. The potential for friction and inefficiency on this journey is high — for example, the data might be delivered with delays or even when the question has already become obsolete. Information might get lost along the way when the requirements are not accurately translated into analytical queries. Besides, generating high-quality insights requires an iterative approach which is discouraged with every additional step in the loop. On the other side, these ad-hoc interactions create disruption for expensive data talent and distract them from more strategic data work, as described in these “confessions” of a data science <a href="https://medium.com/towards-data-science/enabling-the-data-driven-organisation-with-text2sql-f8e07089dd0c">Read More</a>