- Looking for the most effective way to plan for data reusability?
- Looking to increase user adoption of the investments made in the unified data platform?
- Want to free your IT team from serving ad hoc information requests and reduce your cycle time by making the discovery self- serviceable?
As experimentations are happening at an unprecedented pace, data will be the core pivot to lend agility and fluidity to enterprises to drive new possibilities. The enterprises need to create an Enterprise portal gateway in the form of Data marketplaces to enable a data-driven organization.
A data marketplace is a storefront that facilitates democratizing trusted data within and outside of the organization in a secure, governed manner.
As many businesses seek to augment or enrich internal data sets with external data, cloud-based data marketplaces are growing to match data consumers with the right data sellers. While data volumes continue to explode and machine learning and AI become more important in decision-making, data marketplaces are helping organizations draw value from data and enhance data reusability.
Data marketplaces typically offer information across internally generated datasets such as business intelligence, advertising, demographics, sales, operations, derived data products in the form of KPIs, external data sourced such as weather, research and market data & any created reports and advance analytical models. Data types can be mixed and structured in a variety of ways.
To draw value from a marketplace information exchange, it’s imperative to have a strong and well-governed data estate. Following are some of the key factors that both the data producers and data consumers need to consider to make Data marketplace transactions successful –
- Create meaningful data products – Integrating multiple data sources to build reusable data sets. Data in isolation might not have value. However, when the right attributes are combined, the data value increases exponentially. These could be enabled by combining data from internal and external sources. However, integrating data comes with a cost as it might require a lot of Compute and Storage.
- Improve trustworthiness of Data – Data is valuable only when it can be trusted. Hence, an organization needs to ensure that data quality is maintained and measured constantly. Apart from data quality, trusting a data marketplace requires trusted partners, user authentication, user verification mechanism, and a conflict resolution mechanism.
- Make it Discoverable and intuitive – User-friendly ecosystem for the producers to share and consumers to easily find the data that they are looking for. Bringing in an interactive social context to the data sets also increases the weightage of the information as these are user-driven drivers allowing the marketplace to be interactive and meaningful. This can be done by enabling features such as:
- User-Generated Reviews – This allows users to submit reviews on the content
- Up vote/Down vote – Votes based on which of the content display will be promoted and demoted: Content democratization
- Rating – Scale of 1- 10 where 10 is most preferred and 1 is least preferred
- You may also like – Related datasets to be displayed based on the current search
- Bookmark/Wishlist – Tag the content for future reference and specific enhancements that may be desired
- Blogs – Details on any related topic that users may want to share experience on can be used to promote
- Security and Compliance – Any shared data needs to ensure that its secure and compliant with existing laws especially in the area of PII and Finance Details.
Most enterprises today are constrained by challenges such as the right talent to define the right arch/tech tool stack, define the modern data estate blueprint and build and drive adoption of analytical insights optimally.
The need is to build agile Data Platforms with established Data Governance, Catalogues & Semantic Models to support Data Democratization driven by Data Marketplaces.
