Data Governance

Data Governance is a quality control discipline for managing, using and protecting
your data that turns it into a valuable corporate asset.

We can support your efforts in building a sound Data Governance process and
platform in response to the opportunities and risks you face.


  • You have difficulties in formalizing corporate-wide data standards and policies, and
    your Sales still argue with your Finance over the definition of “Revenue”.
  • Your spendings on acquiring and storing the data are growing, but you are not sure
    about the value you extract from your data.
  • There is a lack of understanding between your business departments and IT regarding
    roles and responsibilities for delivery of quality information for decision-making.


Analyze & Architect
Proof of concept, customer cases
Health and readiness check. Quality, problems and recommendations
Strategy and roadmap
DG application scope: Data area/Strategic area/ Critical projects
Data design: model, format, flow, quality and security requirements, life-cycle, solution sizing
DG organizational structure. Roles and processes
Policies and standards. DG effectiveness measure
DG in-line integration with project plans for defined projects
Build & Test
DG components implementation for new and existing projects (MM, MDM, DQ, ECM, BI, DWH)
Data migration and cleansing
DG effectiveness measure reporting system
DG integration test for new and existing projects
DG program operating support
DG program and projects audit
Operational discovery


  • Improvements in competitive differentiation, regulatory compliance and risk management, enabled by accurate and timely information.
  • Optimised investments in business applications and IT infrustructure as a result of clear and unambiguous information requirements.
  • Long lasting results in improvement of information quality due to smooth joint operations between business and IT departments.

Case Study

  • A big Telco company had lots of operational data for everyday activities. Even for basic analytics they applied over 3800 elementary counters and about 700 indicators with ever changing calculation formula. When processing such volume of data there occured constant discrepancies in reporting since there was no unified product catalogue and metadata; no defined roles and procedures for managing data and nobody was responsible for it.
  • Acctiva implemented a Metadata Management System with defined processes for metadata planning, monitoring, transformation and usage. It included a unified documentation to regulate all processes and describe roles and responsibilities.
  • The new System provided the client with a new level of data quality, giving possibilities to control metadata usage, search it effectively in information systems, track it and respond to its changes proactively. The client received a unified reporting across departments and fact-based decision-making.