A data architecture should set data standards for all its data systems as a vision or a model of the eventual interactions between those data systems. Data integration, for example, should be dependent upon data architecture standards since data integration requires data interactions between two or more data systems. A data architecture, in part, describes the data structures used by a business and its computer applications software.

Data Governance

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The design of data governance strategies and creation of policies describing user roles, rights and responsibilities as well as data-related standards and metrics. Such strategies aim to provide a transparent enterprise-wide approach to capture, store, process and access data.

Master and metadata management

The creation of strategies for enterprise-wide master and metadata management. We assess all external and internal data sources as well as relevant existing technologies to come up with standards and metrics to track your master and metadata quality.

Data Quality Management

Low quality data can take many forms: duplicated, incomplete, erroneous or obsolete data. We run data quality assurance and data cleaning activities to fight them all and make your insights genuinely true to life.


Data management and BI analysis is a problem-solving exercise focused on the business’ specific goals. Our approach is accurate, methodical and targeted towards achieving meaningful outcomes through our impressive gamut of BI services. 

Data integration

Reports built on disintegrated data cannot show a full and consistent picture. Our expertise helps you to unite flows from disparate data sources. Keeping in mind your data types, we can come up with a relevant BI or big data architecture, as well as a data warehouse or a data lake design (or both, if needed). This will make your reporting more comprehensive.

Data migration

Based on an assessment to identify sensitive and critical data our experts devise a data migration plan. To speed up the migration process and minimize mistakes, the process is as automated as possible. Post migration, a verification process is run to ensure that no data was lost.

Data enrichment

Recommendation of additional sources and new data to get extra insights make your decisions more informed and predictions more accurate. Our experts make this external data an integral part of your existing data sets.

Data extraction

Regardless of whether your data is structured or not, our experts retrieve it from multiple sources, load it into a data warehouse or a data lake and transform it according to your needs. Automated web data extraction procedures to get valuable insights from comments and posts in social networks, real estate listings, competitor prices, etc.

Data security

To ensure that your data is secure and only authorized users have access to it, our experts analyze your business specifics and apply best practices to review your current approach to enterprise information management. Trough assessment in standard processes our team evaluates the capacity and reliability of the existing architecture and technology stack as well as suggest ways to improve the security of your solution. Data architecture audit and implementation. Our team helps you to your as-is architecture to check whether it complies well with data management procedures and provides you with a blue print for the road forward. Those can consist in follow up tasks such as implementing a BI or big data solution from scratch or data management techniques.