A Data-Driven Organisation Requires Data Governance

The purpose of data governance is to ensure data quality and integrity throughout the data lifecycle and compliance with regulatory requirements​

In an era of increasing concern about data privacy, regulation and accountability, data governance is necessary to define how organisations use data, enable reproducibility of experiments and to document and validate decisions made based on data.​

Video cover image

Benefits of Data Governance​

Skills & Expertise​


Ensure decisions
are made on
the right data​​​
Right Projects​

Business ​

Data-driven decision-making across the organisation​
Skills & Expertise​

Improved Financial Performance

Strategic and operational decisions that reduce costs and increase profits​
Right Projects​

Regulatory Compliance​ ​​

Ensure adherence
to regulations
about use and
security of data​
Right Projects​

​ Reduce Risk​ ​​

Reduce security
violations through
better data
handling practices​
Right Projects​

Data Understanding ​ and Lineage​​

Confidence that
data is accurate,
reliable and usable
for analysis
Right Projects​

Data ​

Maximise use of data in your organization, both structured and unstructured​
Right Projects​

of ​ Data

Transparency and accountability of historical business decision​

Why Brainpool?​

Brainpool has the expertise and experience to guide policy and practice that fulfill regulatory requirements, reduce risk and extract more value from data.​
Monitor icon
Data services are tailored to your business needs​
Monitor icon
We can deploy with any cloud or on-prem service​​​​
Monitor icon
Safe and seamless migration and integration​
Monitor icon
Ensure all data channels are encrypted to best practice ​​
Monitor icon
Fast and minimal business disruption​​
Monitor icon
Connect datasets from multiple sources and achieve clearer picture of your business​​​​​
Monitor icon
Maintain and improve data quality and integrity​​​
Monitor icon
Complete transparency through testing, validation and reporting​ ​

Creating a Data Governance Framework​

The approach to creating a data governance framework will depend on organisation size, industry, the types of data collected and legal requirements. Here are some of the key steps involved in creating an effective data governance framework.
Lightning icon
Business Understanding
  • Understand legal and regulatory requirements​
  • Define values​
  • Identify relevant stakeholders
  • High level understanding of data policies and infrastructure​

Bookmark icon
Scope & Develop Data ​ Governance Policy​
  • Develop deep understanding​
  • Determine purpose, scope and structure​ 
  • Rules for ensuring compliance ​
  • Stakeholders responsibility and accountability​
Lightning icon
Implement the Policy​
  • Prioritise and implement those initiatives that ensure regulatory requirements are met
  • Gradually roll-out other data governance initiatives according to importance​
  • Standardise data governance policy​​

Bookmark icon
Measure the Impact​
  • Understand areas where data governance policies are creating business value (e.g. cost savings, improved data quality, risk reduction)
  • Identify further opportunities resulting from existing data governance initiatives​​
  • Identify performance gaps and assess improvements
Lightning icon
Continually reassess​

• Reassess and update data governance framework to reflect changing regulations and company policy
• Evaluate new technologies and processes to support data governance programs
• Automate data governance processes

Contact Us

Understanding everything involved in effective data management can be overwhelming.
Please type your name.
Please provide your email address.
Please provide your Company Name.
Please provide your phone number.