10+2 Steps to Enhance Data Consumer Experience (Part 1)

Most organisations know they hold valuable data. Far fewer can say what exists, where it lives, or whether it can be trusted. Twelve practical steps for CIOs and CTOs who want to close that gap.

Graham Meaden

Graham Meaden

4 March 2025·5 min read
10+2 Steps to Enhance Data Consumer Experience (Part 1)

For CIOs and CTOs committed to elevating data management within their organisations, here are twelve serious yet practical steps to improve the experience of data consumers. Originally, this list was meant to include ten strategies, but upon reflection, two additional steps were too essential to leave out.

1. Recognise Data as a Strategic Asset

If your organisation aims to become truly “digital,” data must be treated as a strategic priority. This requires more than intent—it demands dedicated resources, clear communication, structured incentives, and effective governance to ensure data quality. Assign accountability at both team and individual levels to make this happen. This is not just an IT challenge; it is a business challenge that IT supports.

2. Recognise Metadata as an Even Greater Strategic Asset

Having terabytes or petabytes of data is one thing, but can your organisation confidently answer these questions?

  • Do business users know what data is available?
  • Do they know where it is stored?
  • Do they understand its quality and provenance?
  • Do they know how to access it?

Unless your organisation is in the top percentile, the answer is likely “no.” To become truly data-driven, metadata—the data that describes your data—must be taken seriously. Like data, metadata requires dedicated resources, clear communication, structured incentives, and governance to ensure its accuracy and usability. So, what’s the next step? Read on.

3. Strengthen Implementation Governance

Ensure that the design phase of any IT system delivery aligns with its actual implementation. As projects evolve—especially in Agile environments—designs are often refined. However, it is critical to maintain visibility into what has actually been implemented. This is where IT governance must evolve beyond traditional ITIL frameworks. Today, IT must deeply understand the data it manages instead of outsourcing this responsibility to third parties.

4. Conduct a Database Documentation Audit

Start with the basics: a comprehensive review of all databases in your organisation.

  • What databases exist?
  • On which platforms are they hosted?
  • Who manages them?
  • Which systems depend on them?

A clear inventory of databases makes data access and management significantly easier.

5. Overhaul Database Schema Documentation

Once databases are identified, the next step is documenting their schema. This means detailing what data is held in them:

  • The tables, columns, and relationships
  • Data types and constraints
  • Business rules embedded in the schema

Up-to-date documentation streamlines system development and enhances data exploration and usability across the organisation.

6. Refresh API Documentation

If your organisation is opening up data for business users and system integrations, it must audit and document APIs comprehensively.

  • What APIs exist?
  • Where are they hosted?
  • Who manages them?
  • What data do they access and update?

A well-documented API catalogue clarifies data provenance, promotes API reusability, and improves ROI on API investments.

7. Document Stored Procedures

Stored procedures often contain critical business logic that impacts data integrity. Documenting them helps ensure:

  • Clarity on what each procedure does
  • Awareness of how data is transformed
  • Transparency in business logic

This unveils hidden dependencies that could otherwise disrupt your organisation’s digital strategy.

8. Clarify ETL and Data Pipelines

Your ETL (Extract, Transform, Load) and data pipelines dictate how data moves through your systems. Documenting these processes:

  • Enables data consumers to understand data flows
  • Reduces key-man risk by ensuring that technical knowledge is shared
  • Strengthens data governance and lineage tracking

This documentation is critical for maintaining data accuracy and security in a constantly evolving IT landscape.

9. Map External Data Feeds

Identify and document all external data sources feeding into your systems. This ensures:

  • Clarity on data provenance
  • Better management of data integrity risks
  • A clear understanding of external dependencies

Without this, your organisation risks data inconsistencies that could undermine analytics and decision-making.

10. Review Legacy and COTS Data Mappings

Legacy systems and Commercial Off-The-Shelf (COTS) solutions often contain valuable data that must be mapped and understood.

  • What legacy systems are still in use?
  • How does their data feed into modern systems?
  • Which COTS solutions contribute to your data lake or warehouse?

COTS vendors rarely document their databases in a way that’s useful for your organisation. However, if they feed into critical data repositories, you must document which tables and data points are being utilised.

11. Establish Robust Metadata Governance

Someone must be responsible and accountable for governing metadata. This is not a bureaucratic burden—it is a gateway that enables business users to access the data they need while ensuring quality and compliance.

A well-structured metadata governance framework guarantees that metadata remains an asset rather than becoming a liability.

12. Develop a Centralised Data Portal

By following these steps, your organisation will have accumulated a wealth of interlinked data. Now, you need a centralised system to manage and access it.

A data portal allows data scientists, analysts, engineers, and managers to:

  • Find the data they need
  • Understand data lineage and governance
  • Contribute to data documentation

This fosters a data-driven culture where data consumers can make informed decisions quickly.

Taking Action

This is an extensive list, and no organisation can tackle everything at once. To avoid “boiling the ocean,” choose an approach that aligns with your business priorities—whether by line of business, function, or another framework.

Why Act Now?

The demand for data grows daily. Rather than constantly reacting to data requests, CIOs and CTOs must take proactive steps to build a sustainable, self-service data ecosystem.

Next Steps

  • Start working through these steps methodically.
  • Track progress to ensure efficiency.
  • Need help implementing these strategies, or independent expertise? Get in touch.

Stay tuned for Part 2, where we continue the journey toward data excellence.

Graham Meaden

Written by

Graham Meaden

Graphex Software — the affordance-driven data platform.

Want to learn more?

Get in touch to see how we can help your organisation harness the power of connected data.

Get in Touch

Keep Reading

Related Articles

The Critical Role of Reference Data Management for CxOs in the AI Era

Have you ever wondered why it takes months to produce a new management report or corporate dashboard? These frustrating delays, endless debates over data definitions, and inconsistent metrics often point to a hidden issue: poorly managed reference data.

Read more
The AI Revolution: Why Your Legacy Systems Are Holding You Back

“No one ever got fired for buying IBM.” But enterprise software still rooted in 1980s architecture is the source of the poor-quality data that stalls AI programmes, and CIOs now face a do-or-die decision.

Read more
Embracing the Data-Driven Approach to Survive the AI Dominated Era

For CEOs, CFOs and COOs, being data-driven is no longer an innovative strategy but an absolute imperative. What it takes to build the culture, governance and tooling that AI depends on.

Read more