A guide to fixing and preventing the data issues and inefficiencies that are stealing money from your business
You need good quality and accurate data to make strategic decisions about business growth, to find efficiencies, and support innovation that can deliver a competitive advantage.
The reality is levelling up how your business manages, leverages, and secures its data is complex, continuous, and can be costly.
But here’s the catch – while you’re striving to manage your data costs, everyday data issues and inefficiencies are stealing capacity and money from your business.
We know from experience that enterprise organisations can reduce their data spend by at least 35% by fixing data issues and inefficiencies through:
- Correct application of data engineering methodology.
- Supporting operational consistency through good engineering practices.
- Giving capacity back to business teams, IT teams and data analytics teams.
Your Roadmap to Data Cost Savings
Don’t risk being beaten by an organisation that has cleaner data and is therefore better able to integrate AI than you, or that can implement better cyber security capabilities because their systems, data, and teams are better equipped to adapt to change.
Our data engineers have created a roadmap we call the Can-Should-Did Framework. It’s not a complicated algorithm; it’s a practical guide to tackling everyday data challenges. We’ve turned this into a whitepaper outlining a step-by-step approach to help your organisation reduce data costs and regain organisational capacity.
Executive Summary
STATUS:
In business, change is the only constant – in people, processes and technology.
OBJECTIVE:
Do more with less. Use your data for strategic decisions, agile operations, innovation and growth.
CHALLENGE:
Daily data issues hinder progress, costing time and money.
REQUIREMENT:
Consistent, efficient, high-performing data operations that adapt to the ever-changing business landscape.
SOLUTION:
A framework for operational consistency supported by data engineering methodology.
RESULTS:
- Clear data processes with improved visibility
- Identification and resolution of data workflow issues
- A complete model of your data ecosystem for continuous monitoring and maintenance
- Increased responsiveness, boosted capacity and productivity
- Potential 35% reduction in data costs
Ready to take action? Download the whitepaper to discover “A Tactical Guide to Taking Control of Data Ecosystems 2025”