5 Strategies to Reinvent Data Ecosystem for Better Data Sharing

Decentralized Systems are Trending in Data Ecosystems

With organizations moving towards digitalization, the diversity in the working process and culture of organizations have created new values like leveraging new technologies, moving towards excellence in business competence, and aligning their business goals. Sharing information and exchange of data has become the vanguard in making organizations perform well in analytics and helps in decision-making. It has gained popularity with rising technologies like artificial intelligence (AI) and Internet of Things (IoT) has increased the efficiency of solving problems, understanding customer behavior, and improving the processes in organizations.

The data ecosystem which is a platform or ecosystems like an IoT environment or a marketplace or simply data sharing between companies, that combines data from various providers and manages data to create new values which would not have been possible with the siloed system. In collaboration, similar organizations pursue a common goal and smooth interoperability can be guaranteed by making agreements on technology in the organizational and legal aspects.

To dive deeper in search of a solution for sharing information, collaborative data ecosystems are becoming a norm which is pushing people to develop their collaborative capabilities to ensure value creation.

5 New Strategies for Data Ecosystems to Stay Beyond 2021

To be successful, businesses must be able to connect the dots between various data sources and data types and search how collaboration in the data ecosystem can bring meaningful action.

5 Strategies to Reinvent Data Ecosystem for Better Data Sharing
  1. Open Source Data Ecosystem: More and more companies are adopting open-source data formats to make data compatible between programming languages ​​and implementations.

Open-source data formats such as columnar data storage, memory format for analysis, artificial intelligence, and machine learning mean that businesses can use their data in all their current and future tools. This provides increased flexibility and freedom to contribute to the industry-wide community.

2. New Data Space for B2B Data Sharing: Since data sharing is one of the practices that accelerates the digital transformation, “data-sharing culture” is replacing “data ownership”

Data space is the concept that defines the interaction of different data technological components in order to promote cross-company data sharing while adhering to sovereignty principles. This describes the technical specifications like API, standards, and governance to allow sharing of data between organizations without central data storage.

The European Union’s “Common European Data Space” is an example of data space, which is available for use in the economy and society, keeping companies and individuals in control.

3. Data Mesh for Decentralized Data Governance: “Data Mesh” is an architecture pattern that takes a new approach of domain-driven distributed architecture and decentralization of data. This decentralized strategy distributes data ownership to domain-specific teams that manage, own, and serve data as a product.

This approach encapsulates data, its relationship and context into data products that bring ease of use for business consumption. This data mesh acts as a link between application and analytical system.

KPMG provides data mesh to IBM Cloud Pak provides a 360 degree view of data that enables resources to focus on activities such as data analytics and insight generation while governing and securing data across enterprises.

Data ecosystems have the potential to generate significant value. However, there are some barriers to establishing an ecosystem so companies need to understand the ecosystem landscape, find out which business model works and ensure team participation.

Data Governance will Form Better Data Ecosystem

As data ecosystems evolve and more data is being shared, a more sophisticated data model will often be required to support the linking of disparate data. They will likely need to implement graphical knowledge that provides a high degree of flexibility in the process. These models also need to support data governance by restricting access and use to specific data elements based on data sharing agreements but all these are based on use cases.

Techment Technology can assist with prescribing the right data ecosystem tailored for your organization’s needs and knowing what advancements you need for building the right data architecture.




Techment is a digital catalyst that expedites solution development with high-velocity agile delivery model and in-depth tech expertise for global organizations.

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Techment is a digital catalyst that expedites solution development with high-velocity agile delivery model and in-depth tech expertise for global organizations.

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