Every second there is a plethora of data generated in various forms. Organizations value this vast quantum of data, analyzing it and deriving insights to make data-driven decisions. However, the ability to drive actionable insights from the data is still limited to data analysts or data scientists, who know how to organize, crunch, and interpret data.
Data democratization is a game-changer. It is the process that enables everyone in an organization, irrespective of their technical know-how, to have access to data without any gatekeepers that create a bottleneck, work comfortably, make data-driven decisions and build delightful customer experiences. It establishes the base of self-service analytics and allows everyone (technical or non-technical) to gather and analyze data without seeking help from data professionals. The ability to instantly access and understand data will translate into faster decision-making and more agile teams.
The first step would be to break down information silos. Customizable analytics tools capable of desegregating and connecting previously siloed data, making it manageable from a single place, are imperative. This single source of all data is called a Data Marketplace; It enables online transactions which facilitate data sharing and data monetization, driven by the volume, velocity, variety, and veracity of big data.
Factors that shape maturity of the Data Marketplace
A data marketplace is not a one size fits all model. Instead, multiple factors shape the maturity of a Data Marketplace. The most important factors to consider before adopting the data marketplace ecosystem are the authenticity, quality, and reliability of the data in use. The reliance would be on data coming from multiple sources including, but not limited to – third-party datasets, primary sources like Business units data, or various personas within and outside the organization. Checking the quality and reliability of data on multiple checkpoints is of utmost importance since that data would drive critical business decisions.
Decisions based on incorrect data can be catastrophic to an organization. Once the quality is in check, next-in-line is data governance, the value chain of collection of processes, roles, policies, standards, and metrics that ensure the effective and efficient use of information.
Then, it’s important to decide and determine the level of access for data architecture (centralized or decentralized) data for various members of the organization and the subscription model: free, freemium, or pay-per-use basis.
Brillio’s Maturity Framework
Brillio has built a Data Marketplace Maturity framework that assesses multiple stages of maturity for an organization’s data strategy and its ability to adopt a data marketplace ecosystem. They are designed in such a manner that each one is an addition to the previous one i.e., each successor stage consists of all the features that the predecessor had and adds them up with enhanced features. Below, we define the four maturity stages in the Data Marketplace model –
The Building Blocks of the Maturity Stages
The foundational building blocks are the key to improving the maturity of an organization’s data strategy and adopting the data marketplace ecosystem.
All the above factors combined can provide a good head start for anyone who wants to venture into a data marketplace model. Keep in mind all the factors, decide on and analyze the building blocks, and assess the maturity level your organization currently stands at. Only then conduct a gap analysis with the maturity level that you want to get to. Brillio’s assessment methods provide a clear roadmap laying out the features and building blocks on the path to a successful data marketplace journey.
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