With data-driven decision-making now the best competitive advantage a company can have, business leaders will increasingly demand to get the information they need at a faster, more consumable clip. Because of this, we’ll continue to see calls for AI to become a business-consumer-friendly product rather than one that only technically savvy data scientists and engineers can wield....

Can you tell us about your journey and what motivated you to co-found ForwardLane, particularly focusing on AI’s role in financial services? My journey into fintech came to me when I worked at the multi-asset alternative asset manager, CQS. There, we could find insights and act on them far ahead of financial institutions. When I saw how difficult it was for advisors to get to insights, I...

In the evolving landscape of data management, age-old approaches are gradually being outpaced to match the demands of modern organizations. Enter as a savior: Data Mesh, a revolutionary concept that modern organizations harness to reshape their business models and implement “data-driven decisions.” Therefore, understanding and implementing Data Mesh principles is essential for IT...

As the trajectory of computing power continues its exponential ascent, quantum computing stands at the forefront, poised to tackle challenges that have long confounded traditional computational methods. In the ever-evolving landscape of the 21st century, quantum computing emerges as a dynamic field brimming with promise, offering a plethora of solutions across diverse domains such as climate...

Throughout 2024, data analytics continued to play a crucial role in driving data-based decision-making for B2B companies, while investment in advanced data technologies surged. These new tools offer deeper insights, predictive capabilities, and more sophisticated analytics to improve governance. The tools listed below are equipped with powerful features across BI, predictive modeling, natural...

Many businesses have learned the hard way that not every AI project leads to glory and success. In fact, a 2023 CIO.com survey found that more than half of AI projects fail to produce actionable results at all. There are many reasons for this, but one of the biggest causes we frequently see is a disconnect between the data scientists who are actually building the models and the end users who...