Long term data integrity is essential to get real value from data

We all want the benefits that big data promises to bring.

Whether it’s for real-time insights, operational efficiency, personalisation, targeting, or to deploy AI models, we all now want to be driven by data.  

But all too often we are not making the right decisions or aren’t willing to put in the hard graft to turn these theoretical benefits into reality.

All too often, data remains messy, disparate and confusing. Legacy systems persist, teams continue to operate in silos, internal expertise is outsourced, vanity projects take precedent, lack of ownership prevails and silver bullets are relied upon.  

This means that organisations are not even close to getting the maximum return on value from their data, or in the worst cases are generating inaccurate and misleading insights.

And in a world where systems continue to get more complex, and the volume of data is growing exponentially, the need for good, clean, reliable data is growing accordingly.

To reap the benefits of big data, organisations need to invest in data integrity.

Data integrity means great data leadership, data culture and data infrastructure to drive a data ecosystem that provides accurate, trusted data that drives efficiencies and performance.

Data integrity cannot be achieved with a silver bullet– no out of the box solution, framework, best practice or technology can provide it.

Data integrity requires a deep understanding of the context of the data and the environment it is being generated and consumed in.

Data integrity requires ownership and buy-in, not just from senior decision makers, but from the whole organisation – it must become a central part of the organisational culture.

Data integrity requires great collaboration within the organisation and with external technology providers and specialists.

Data integrity takes a lot of hard work, particularly around the boring ‘middle’ bits that turn data into value – the business definitions, the presentations layers, the models, etc.

Data integrity needs a long-term investment strategy to generate real returns. Taking time (maybe years) to get underlying systems consolidated, streamlined and operationally sound, and to implement a data culture that includes everyone and that is universally bought into will pay dividends in terms of the accuracy and accessibility of insights, as well as the applications of those insights that genuinely drive change.