MUMBAI: Reserve Bank governor Shaktikanta Das has called for better data management systems as we are in an era of data abundance, a long move away from data scarcity of the past.
Stating that the importance and utility of data extend beyond periods of crisis, Das while addressing the 18th Statistics Day celebrations at the RBI headquarters on Friday, said data management systems need to keep pace with the use of unconventional data sources as policy inputs.
“While doing so, we have to be mindful of the importance of eliminating noise and capturing the signals from high frequency indicators because we are moving from an era of data scarcity to data abundance. The volume of digital data stored as well as the storage capacity are growing at an exponential pace, bringing forth new challenges along with new opportunities,” the governor said.
The department of statistics and information management of the RBI celebrate the Statistics Day on the birth anniversary of Prof Prasanta Chandra Mahalanobis, who is honoured as the father of modern day official statistics in the country.
The focus now is naturally on enhancing capacity in artificial intelligence and machine learning techniques and analysing unstructured textual data. While doing so, ethical considerations need to be addressed and biases in algorithms need to be eliminated, Das said.
The RBI is also making efforts to harness the availability of huge computing power and growing digital footprints to analyse measures of expectations, sentiment indicators and policy credibility measures from alternative data sources, the governor said.
He said the RBI is contributing to the formulation of public policies and the overall economic development with its cutting edge information management system and specifically mentioned the launch of the next generation data warehouse - the Centralised Information Management System (CIMS) - with several new features, at the Statistics Day conference last year.
The next generation CIMS incorporates various new age features like a data lake and integrated analytics with much higher processing speeds and scalability. A data lake is envisioned as a part of CIMS, which is more flexible than usual database systems, in terms of data fetching from multiple systems (inside and outside RBI), data storage (both structured and unstructured information) and data processing (standard and dynamic query based reports), he said.