Why Would you need this service?

If your organisation experiences the following pain points, it may be because your data is not managed and maintained with the same rigor as other assets.

  • Inaccurate, duplicate counting of financial figures in reports;
  • No single version of truth exists for key information;
  • Proliferation of customer accounts for the same customer leading to lack of standardised quotation;
  • Lack of 360-degree visibility of supplier spend;
  • Poor data security leading to vulnerability;
  • Poor data quality and lack of timely access.

In the modern economy, data should be valued as an asset. To harvest the right data and ensure maximum value from it there is no substitute for investing in a data management capability.

How we deliver this service

1Tech has developed a data management framework enhancing DAMA to include big data, predictive analytics, artificial intelligence and machine learning. The framework provides a set of capabilities for instituting an independent, self-sufficient data management business unit. Our framework tools and templates are a starting point to tailor and deploy a capability that is right for your organisation.

We deliver the design blueprint and implementation roadmap plan which we define for consumption and use by our client’s delivery partners.


Typical deliverables and outputs include:

  • Data management capability business architecture (services, functions, business requirements and processes);
  • “As-Is” vs To-Be gap analysis;
  • Data management maturity model;
  • Enterprise data architecture;
  • Enterprise data security architecture;
  • Enterprise data governance approach, charters and processes;
  • Data migration and remediation approach;
  • Data management capability Target Operating Model (ToM);
  • Data management performance management approach (including metrics and balanced scorecard dashboard);
  • Data management tools assessment;
  • Roadmap and implementation plans.

Benefits/ Typical Outcomes

  • 360 view of your data landscape;
  • Improved data integrity, quality and assets;
  • Secured data assets;
  • Understand the value of data / data having a value;
  • Data is fit for purpose and usable in a way that can be monetised;
  • Auditability of data;
  • Business confidence in data;
  • Informed decisions based on insights gained from data;
  • Secure and compliant data landscape;
  • Compliant data landscape.

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