One thing’s for sure: in 2023, Machine Learning will penetrate even more businesses in even more sectors, following tremendous growth last year. But when it comes to ML, what should organizations have their eyes on, to stay ahead of their competitors?

85% of Machine Learning (ML) projects fail. This stark reminder from Gartner – despite more tools being available to businesses than ever. The thing is ML success is not just about tools and technology; it’s about how they’re put into production by experts. Plural. Machine Learning – that improves productivity and profitability by finding valuable insights buried deep in your company databases – needs a small army to leverage it.

Timerie Bahler is no stranger to digging deep into the data of organizations – from telecommunications to trucking and finance companies. Many different industries, with many different challenges. What they all have in common is that somewhere in the data there’s always something new to discover that has the power to enhance operations and bottom lines. And that keeps Timerie motivated, professionally, as she turns ostensibly hidden information into actionable insight.

Deep within data lies stories that can help businesses of all shapes and sizes see hidden detail – and act on it. Take a US healthcare provider, for example, who came to us with a pressing issue: the greatest cause of its patient dissatisfaction was due to waiting times. When were the longest peaks? Where was the epicenter of the backlog? And once this was known, what targeted processes could be introduced to speed things up?

Artificial Intelligence’s ability to augment and support progress and development over the past few decades is inarguable. However, when does it become damaging, contradictory even? In our latest Beyond Data podcast AI’s Climate Jekyll & Hyde – friend and foe, Tessa Jones (our VP of Data Science, Research & Development) and Sophie Chase-Borthwick (our Data Ethics & Governance Lead) discuss exactly this with Joe Baguley, Vice President and Chief Technology Officer, EMEA, VMware.

In our second Beyond Data podcast episode ‘Autonomous mass transportation and its impact on citizen privacy’, we will sit down with Beep’s Chief Technology Officer, Clayton Tino to explore the current landscape of autonomous vehicles (AVs), whether AVs truly can replace the human factor in public transportation, and how AV ethics can be holistically measured. Here we give you a snapshot of that fascinating discussion by digging into a few of the explored topics.

When it comes to how truly intelligent Artificial Intelligence (AI) is, it’s a polarizing debate. Either AI will solve the world’s woes or robots will rule us all – Matrix-style. But it’s all a little more complicated than Hollywood makes it seem… For a deep dive, do listen to our Beyond the Data podcast hosted by Sophie Chase-Borthwick (Calligo’s Global Data & Governance Lead) and Tessa Jones (VP of Data Science Research & Development).

Today, Calligo announced that we have partnered with BigID. The BigID data intelligence platform enables organizations to know their enterprise data and take action for privacy, security, and governance. This partnership will enable Calligo to provide clients with the ability to proactively discover, manage, protect, and gain more value from their regulated, sensitive, and personal data across their data landscape.

In this blog post, we explore how we boost our MLaaS approach to create the best blend of innate human nuance and computational ability of machines to solve your business challenges…

To uncover how to build the best data strategy for your business, we chat with Adam Ryan, Calligo’s Chief Data Officer for Data Strategy on what to do, what to avoid – and everything else in between…