The 5 Powerful Ways Data Marketplace Will Change the Industry

5 Ways Data Marketplaces are Changing the Game with their Dynamic Impact

Hanzala Qureshi

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Photo by Cecep Rahmat on Unsplash

Data Marketplace is a modern Bazaar.

It’s a way organisations can consolidate and share data internally and externally. Over the years, billions have been spent on modernising the legacy data stack. However, the self-serve data dream continues to be out-paced by large budget over-spend and poor data transformation.

There are clear use cases in which Data Marketplace will disrupt the industry; here are 5.

1. Uber like aggregation

The current data stack is messy.

Data is on-prem, in various clouds, and disparate data warehouses/marts. And currently, there is no way of centralising this data without spending millions on data transformation.

In the same way Uber uses its platform to aggregate drivers and passengers, Data Marketplace can aggregate data producers and consumers. An organisation with multiple Data Catalogues / Dictionaries and serving platforms often needs clarity on the reliability of the information. This negative feeling leads to separate communities of people championing certain tools. Data standards are not set or followed. Hence, having a centralised consumption platform adds immense value to an organisation.

Aggregating the consumers and producers also has the benefit of reducing friction between teams. Starting with your organisation’s most extensive data store, either aggregating as a Data Product or just a dataset, making it available in Data Marketplace for “viewing” will simplify a dozen processes. Processes such as, “where is this data”, “how can I access it?”, “who is the owner” and “when was it last updated?”.

Simplifying the data stack is difficult, but providing an aggregation layer is a step in the right direction.

2. Reddit like collaboration

Data meetings with project teams feel like deja vu.

Everyone is asking the same set of questions each time. An endless amount of time is wasted explaining the same limitations each time.

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Hanzala Qureshi

Data Architecture Consultant | Data Evangelist | Learn more about all things data by following me @ hanzalaqureshi.medium.com