Data Governance

Data governance encompasses the people, process and technology required to control and standardise the governing and handling of the data across the enterprise.

With the increase in data, data volumes, complexity around data movement and data integration, the intricacies around data quality, Data Governance is forced to be a strategic and tactical discipline within the enterprise. The Data Governance council will drive long term strategic objectives and short term tactical drivers.

Data Governance as a disciple should appeal to one of many of the following business driver / goals:

  • Increasing consistency and confidence in decision making
  • Regulatory compliance and mitigation of risk
  • Improving data security
  • Maximizing the income generation potential of data
  • Designating accountability for information quality
  • Increase in revenue and ROI (make money / save money)
  • Manage cost and complexity

These goals are realised by the implementation of Data Governance Programs, or initiatives. Data governance has multiple focus areas and depending on the focus area which receives higher preference will determine the way that it will be implemented within the organisation and it will determine the success rate of the business drivers / goals.

Data Governance is a system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods. - Data Governance Institute

Kwezi Software Solutions Service Offering:

Kwezi software solutions will be able to provide the following consulting services:
  • Identify business priorities analysing it from a People, Process and Technology point of view
  • Recommendations of Data Governance focus areas within your organisation
  • Data Governance Maturity Assessment including an AS-IS analysis of your data quality management capability
  • Recommendations of your Future State Data Governance capability based on the outcome of the Data Governance Maturity Assessment and AS-IS analysis of your data quality management capability
  • Analyse gaps and determine activities
  • For Data Governance activities with a strong focus on Data Quality:
    • Assess your current Data Quality state
    • Analysis of your current data landscape and data lineage to assess important data sets
    • Data Quality Strategy, Framework and Roadmap
  • Data Governance Strategy, Framework and Roadmap consultancy services