Big Data
Data Storytelling: The Critical Path for CIOs to Become Communication Leaders
In an era where data-driven decision-making is increasingly important, misunderstandings between CIOs and business teams remain prevalent. Based on the perspectives of a Gartner Senior Research Director, this article systematically elaborates on the core role of data storytelling in bridging communication gaps and proposes specific practices—including standardized visualization playbooks, automated narrative tools, contextual connections, and emotional resonance—to help CIOs transform insights into actionable business actions.
How the NFL is reshaping its rookie scouting combine with data
The 2025 NFL Scouting Combine begins Thursday, with hundreds of players participating in four days of testing. The league, in partnership with AWS, has launched the Combine IQ dashboard, making advanced data visualizations available to the public for the first time, covering comparative rankings and draft scores for events such as the 40-yard dash and jumps. The tool, built on three years of sensor data, aims to reveal patterns behind the numbers and assist teams in making smarter decisions ahead of April's draft.
Runaway cloud storage costs are dragging down enterprise project progress and budgets
An annual survey commissioned by Wasabi Technologies and conducted by Vanson Bourne reveals that the proportion of enterprises exceeding their cloud storage budgets in 2024 rose to 62%, up 9 percentage points from 2023. Data egress and usage fees have become major pain points, with over half of surveyed enterprises experiencing business delays as a result.
Weak Enterprise Data Foundations Lead to Frequent Decision-Making Failures
SoftServe commissioned Wakefield Research to survey 750 business leaders and found that about two-thirds of decision-makers believe no one in their organization truly understands the data collected, and nearly 60% admit that key decisions are based on inaccurate or inconsistent data. Nearly 75% of leaders attribute the problem to improper prioritization and resource allocation, especially over-investing in generative AI while neglecting data and analytics. Industry cases show that companies such as USAA and American Honda are strengthening their data foundations to support AI applications, but many enterprises remain stuck in the pilot phase with delayed returns on investment.