Data, and why it’ll still be the answer in 2025 and beyond

Whether you’re chasing the successful application of AI and GenAI tools or trying to solve a data infrastructure challenge, it always comes back to your data.

The big question I’m hearing from our customers is, ‘Where should we focus our attention next’? With cloud, data resilience and cyber security, AI, sustainability, consumption models and more all competing for our focus (topics we’ll be diving into in this issue of Bytesize), it confirms the one thing that underpins the success of all of it.

Your data.

It's not the first time you've heard it. However, the data tsunami continues to accelerate as predicted. With the momentum of application modernization, 5G networks and IoT sensors, data (and everything to do with data) is skyrocketing. It’s causing challenges in storing and protecting data, as well as enriching and activating it to 1. improve their customer experience, 2. find ways to generate new revenue streams, 3. improve operations saving money and 4. mitigate risk. As you address these challenges, it’s vital to pay attention to the downstream effects on your data.

Data: your foundation for success

Just as when building a physical structure, a strong foundation is key. With a solid data infrastructure together with intelligent data management and AI-powered hybrid cloud and security solutions, you have a foundation for the mission-critical that can pass the test of time. With the right foundation, you’re empowered to innovate and scale through data so that endless possibilities can be realized. 

But a weak foundation will undermine your innovation and goals 

Our recent survey, How AI is Shifting Data’s Foundation, gave stark insights into the state of data. Speaking to 1,200 decision-makers across 15 countries, three-quarters of IT leaders said the data they store is unstructured, and 18% said half the data they store is dark data. Almost a quarter (24%) don’t review the datasets they use to train AI for quality.

In North America, 38% of IT leaders are concerned with the impact of data on sustainability. Yet poor data quality means inefficient AI outputs that could negatively impact not only your sustainability, but also your overall brand. 54% of US IT leaders also say security is the top concern for data storage, and there are obvious security and recovery risks of not knowing what data is where, such as the costs of unknowingly storing low-value data in high-value storage. Accurate, complete and consistent data is key to success and building a confident path ahead (view the full ten dimensions for data quality on page 33 here). 

Clarity of data: critical to better experiences and operational success

For 43% of respondents in the US, accuracy is the highest priority for successfully implementing AI – coming in just behind speed (46%). With full accuracy and clarity of data, you can unlock opportunities to monetize that data, opening up new business channels with tailored services, new AI-driven applications, and increased personalization. 

When you have clarity of data, you can properly classify it. You can improve costs and efficiency by only storing what you need and where you need it. You can enhance security and resilience, protecting your brand during a time when reputation matters more than ever. By delivering those more personalized experiences, you win over more customers at a time when competition is on the rise and brand loyalty is fragile. 

You’re already halfway there 

This isn’t a do-over – we’re not starting from scratch here. It’s simply another step on the modernization journey. The success of AI and the rise of Edge computing has happened at a speed that takes a moment to catch up with. Once you take stock and take a fresh look at your data landscape, refine classification, and focus on investments for the long term, you’ll be ready for the next wave of digital innovation and all the exhilarating opportunities that’ll no doubt come in its wake. 

In this issue of Bytesize, I hope you’ll find plenty of food for thought, with articles spanning AI and the ethical and ESG considerations around it, as well as automation and harnessing big data and a Zero Trust philosophy to build resilience and protect against risks. As always, reach out to me if you have any questions.