Data & BI Solutions

Data Governance

Data Quality, Master Data Management, Reference Data Management and Metadata Management

Adastra has a wealth of knowledge and experience in implementing Data Governance strategies to take care of your data. Traditional methods and architectures are becoming obsolete. We are continuously innovating and building new solutions to handle the volume and complexities of ever-growing data in the digital world. We leverage our expertise to provide leadership and guidance, bringing your data to life.


of executives agree that inaccurate data hampers an organisation's ability to provide excellent customer experience.  

Our Services

Data Quality

Improving the level of organizational data quality via implementation of our data quality methodology and AI powered tools.

Master Data Management

Consolidate, integrate, and clean data from a variety of sources; get a unified reference data base for your entire organization.

Reference Data Management

We help to maintain accurate, consistent, and standard reference data across the organization.

Metadata Management

We provide a centralized metadata management system ensuring metadata across the organization can be used for various analytical needs.

Data Quality

Poor data quality hampers the value of your enterprise information, delivering imprecise and unreliable results. Enable your data to drive your strategic direction by implementing a robust data quality management (DQM) strategy along with AI and Machine Learning capabilities.

By implementing a sound DQM strategy and a set of processes, organizations may measure, monitor, and improve the quality of their data on an on-going basis so that data issues become easily identifiable and managed. Thus, allowing for data-dependent business processes and applications to deliver more accurate insights. Our DQM services, paired with Machine Learning capabilities for self-healing, set the foundation for a reliable data strategy, catalyzing your digital transformation initiatives.


One-third of customer data is, in some way, poor quality.  

Master Data Management

While data is the oil of the 21st century, it has to be sorted, verified, secured, and managed so that management can use it as a basis for making informed decisions. The objective of Master Data Management (MDM) is to create a single, main source of reference for all important data (business, marketing, manufacturing, operational, financial, etc.).

In practice, these are complex, very sophisticated tasks, as large organizations often process tens of millions of data units from dozens of internal systems. We support organizations with both data access itself and the means of handling data.

Reference Data Management

Managing sophisticated mappings between different reference data representations and hierarchies allows for inter-system communication. If your data is inconsistent, incomplete, or duplicated, your information will lack the integrity needed to extract valuable insights.  

Our Reference Data Management (RDM) approach maintains accurate, consistent, and standard reference data across the organization. Instead of individual users, departments, or business units using their data and data sources, often leading to conflicting conclusions, the RDM aligns the processes creating, maintaining, and using the information. With consistent and shared information, the organization can focus on executing business decisions.

Metadata Management

Metadata management aims at correctly defining, integrating, managing, and sharing reliable metadata within an organization through the combination of organization, policies, processes, procedures, standards, and technology.

With the adoption of emerging technologies and the shift to digital business strategies, organizations are experiencing an influx of data. This new and vast data offers in-depth insights and holds great potential, but without properly defined and managed metadata, there is little context and comprehension, and the value of the data is lost. With a centralized metadata management system, data across the organization can be used for various analytics needs, ensuring its uncompromising purpose spans your organization's business initiatives.