Decoding Data: Value discovery of data via data marketplaces

Uma Ganesh | March 1, 2021 |
Currently, however, the third category of data marketplace derives data from sensors and IoT which is at a nascent stage with only 20% companies managing to monetise their data as per Gartner.

Data is considered the new oil and therefore businesses have been making significant efforts to streamline methods and systems that enable in effective collection, categorisation and organisation of data supporting in the decision making processes. Most of the attention so far has been on mining the data generated by the business through its own transactions and extract useful insights from them for enhancing the customer experience or productivity of resources being deployed.

In the next phase of this journey we are going to see significant attention on accessing and procuring data from market places. Businesses will start realising the realvalue of their own data and would also be able to add more value to their own data blending with the data available from other external sources. According to Gartner Report, by 2022, 35% of large organisations will be either sellers or buyers of data via formal online data marketplaces.

Data marketplaces should not be confused with data lakes and data warehouses as the latter pertain to the storage and analysis of internal data only whereas the former enables in access to data from third parties. Data marketplaces enable businesses to access a variety of data that is categorised based on location, domain or customer profiles and as per requirement could choose appropriate data. Data exchanges are built around high levels of security and consistency and quality of data and thus build confidence in all stakeholders in the monetizing process. Some data marketplaces like Ocean Protocol are integrating blockchain into their solution to ensure anonymity in access to the data and data providers.

Personal data marketplace enables individuals to monetise their own data by selling it to the platform providers and B2B data marketplace enables massive data aggregation from multiple data providers thus making it convenient to buy and sell data as required. Both these data marketplaces have been prevalent for a while now and with sophisticated tools are seeing higher adoption rates.

Currently, however, the third category of data marketplace derives data from sensors and IoT which is at a nascent stage with only 20% companies managing to monetise their data as per Gartner. The volume and types of real time data being gathered through sensors and IoT are extremely valuable for understanding consumer behaviour and improve sales in particular. Steamr and DaweX are examples of data marketplace providers which facilitate machine to machine transactions related to data.

Data marketplaces and exchanges create economies of scale and reduce the costs of third-party data. Data marketplace architecture is also evolving and data buying companies like Facebook, Amazon and others would have to calibrate their architecture on an ongoing basis with the increasing realisation of customers to seek value in the data they can access from them. It is estimated that by 2030 over 1 million organisations shall monetise their data assets and according to Accenture, data marketplace will unlock more than $3.6 trillion in value.

Data marketplaces are enabling businesses to be in an advantageous position to derive better insights and be able to make new offerings to their customers combining their own data with the datasets that can be procured. Eventually organisations would be able to derive true value for their own data through these data marketplaces. For a long time valuation of assets was centred around the physical hard assets but in the last two decades we started seeing trends of valuing human capital. In a not so distant future it would be the quality and quantity of data owned by companies whose value is likely to form a part of the asset valuation. Here in lies the important role of data marketplaces and exchanges—for they would be in a position to help determine the value of such data.

Originally appeared in Financial Express