The few big remaining energy companies have a huge task on their hands handling all their new customer data from their acquisitions.
How to keep your Millennial workforce engaged with a Data Strategy. Avoid the ‘Big Quit’ by empowering your team with access to data and data tools.
Before Christmas, our CEO, Rob Jones, gave us his take on data fabric, one of Gartner’s strategic technology trends for 2022, and why he feels we’re still some years away from it becoming a genuine possibility. Now we’re turning our attention to the new data developments and innovations we can expect to come to the fore through 2022. Here, Rob shares his predictions with us.
In today’s data landscape, companies are increasingly looking to control and maximise the value of their data. Data storage can have a huge impact on this. A data warehouse can act as a central hub for business data, connected to all other tools and applications. The common end goal is a data infrastructure that matches up with your business ecosystem – but time and again businesses are unsure of how to get there.
Data fabric has been named as one of Gartner’s strategic technology trends for the coming year…
This year we’ve worked with 38 clients, completed 17 data migrations, worked on 70 consulting projects, and welcomes 10 new starters.
During this season of giving, we wanted to look back on some of the amazing charities we’ve worked with on data projects this year.
We are working with our technology partner to make sure that non of our customers are susceptible to this vulnerability.
The most recent figures suggest that nearly 40% of data migration projects end up being over deadline, over budget or failing entirely. More often than not, this is because there isn’t a solid framework in place that futureproofs and adds structure to the project.
How clear and consistent is the data your organisation relies on for decision making and planning? Is it helping you communicate with customers effectively, manage operations efficiently, and plan new products and services knowing they match demand? Or are you struggling with a mass of disparate data sitting in multiple applications, unable to pull together complete and accurate information or uncover useful insights?