SUCCESS STORIES / Cloud

Unlocking the power of data mesh: Strengthening data ownership and governance for improved business outcomes

The data mesh architecture enabled our clients to unlock the full value of their data by improving data management, compliance, security, and accountability.

Background

Organizations have been keen to adopt data lake solutions to converge and efficiently manage the enterprise data generated across their functions – from sales to operations to customer support.

The sheer volume and complexity of data generated in a data lake can rapidly become unmanageable without the appropriate resources and expertise, potentially jeopardizing consistency, data quality, and governance.

Organizations have begun to realize that a data lake solution might be insufficient to support their data-driven decision-making goals during a scale-up of their businesses.

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25% faster time-to-market

25% better data quality

25% enhancement in data asset management

Client Situation

Our client is a prominent communications company in the Caribbean and Latin America.

The organization acknowledged the vast potential of its data and aimed to utilize it effectively to gain meaningful insights and make informed business decisions. As it expanded business operations, the company realized that its conventional data lake lacked the scalability to handle voluminous data sets efficiently. This prevented the company from realizing the full value of its data.

To overcome this obstacle, the organization sought assistance from Prodapt to become a data-driven entity, fulfilling its commitment to deliver exceptional services.

By adopting Prodapt’s data mesh approach, the company built an efficient and scalable data solution to garner rich insights and scale its business faster.

Diagnosis

The data lake platform used by the client was outdated and inflexible, making it difficult to keep up with the rapidly changing business needs. Additionally, the lack of proper data governance and metadata management hindered the company’s ability to innovate.

The company needed a new approach that would enable teams to manage their own data while promoting standardization and governance to enhance data quality and allow for data ownership by the teams. This can be achieved through decentralization, which involves distributing data ownership among teams to manage data independently and securely as a product.

With efficient data utilization, teams will be able to drive informed business decisions, leading to improved performance and competitiveness.

Solving It

Prodapt has successfully implemented a data mesh architecture, which led to more efficient and effective use of data. The architecture is centered around four pillars - the domain-oriented approach, treating data as a product, federated governance, and a self-serve data platform.

The domain-oriented approach involves decentralizing data ownership using data catalog platforms such as AWS Catalog and Google Cloud Data Catalog to enable central discovery, access control, and administration of distributed domain datasets.

Adopting a data-as-a-product approach entailed forming compact, cross-functional teams that take charge of data products, including architecture, quality, and delivery. This fostered greater accountability and a higher likelihood of success.

Implemented Federated data governance enabled compliance and data security, which complies with industry regulations and organizational codes. This is a distributed approach to managing data across multiple locations and systems. We have implemented a sample data infrastructure as a Platform (DaaP) on AWS, which has helped streamline data processing and analysis

The team of experts developed a self-serve data platform that simplified data management by abstracting technical complexities.

The data mesh cut dependencies on centralized data teams, resulting in a 25% faster time-to-market for new data products. The increase in ownership and accountability resulted in a 25% improvement in data quality. The data mesh boosted scalability by allowing teams to build their own data products, increasing the capacity to manage data assets by 25%.

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