Dark data often resides in the hidden recesses of a metaphorical jungle: It comprises unstructured and unused data accumulated over years of digital transactions, interactions, and operations. Dark data is information that has been collected but not actively used or analyzed, leaving its potential benefits to remain speculative. Unlike structured data, which fits neatly into databases […]
Data Modeling Trends in 2025: Simplifying Complex Business Problems
Data modeling, the practice of diagramming business requirements, has grown significantly. According to a 2024 DATAVERSITY® survey on data management trends, 64% of organizations actively use data modeling, a 13% increase since 2023. This trend will only increase in 2025 as companies face heightened opportunities and risks. Newer technologies and AI are set to disrupt predictive analytics, especially with huge volumes of […]
Women in Data: Meet Ghada Richani
The latest installment in our Q&A series with women leaders in data features Ghada Richani, the Managing Director of Data & Technology Strategy and the Project Management Office at Bank of America. (Read our previous Q&A here.) An award-winning tech community thought leader, Ghada Richani started her career at Bank of America in 2001. She worked […]
What Is the EU AI Act and Why Does It Matter?
Technology has always advanced faster than the laws we rely on to protect ourselves from technology’s misuse. Fears of a super-intelligent artificial intelligence arising that manipulates machines and humans to do its will sound like science fiction, but the incredible speed of AI advances make them anything but. The more immediate threats that AI poses to individuals and businesses […]
Data Governance Trends in 2025
As organizations enter 2025, it is time to reflect on the significant trends that shaped data governance in 2024 and anticipate what lies ahead. Multiple factors have driven the rapid evolution of data governance frameworks, including advancements in technology, increased regulatory oversight, and shifting business priorities. To continually improve data governance, it is critical to review key […]
The Growing Importance of AI Governance
New technologies often engender fear and foreboding among people outside tech industries. The latest example of this trend is artificial intelligence (AI), which is a topic of much concern and misunderstanding among the public. It’s easy to dismiss these qualms as the common human tendency to mistrust the unknown. However, much of the alarm about AI […]
Data Strategy Trends in 2025: From Silos to Unified Enterprise Value
Data strategy trends for 2025 reflect a growing paradox: While organizations race to adopt generative AI and automation, their disconnected data initiatives are creating new silos rather than breaking them down. DATAVERSITY’s® 2024 Trends in Data Management survey highlights this growing challenge, with 68% of respondents citing data silos as their top concern – up 7% from […]
The Impact of Advanced Data Lineage on Governance
In today’s data-driven business landscape, data quality – the availability of usable and business-ready information – remains a significant and worsening challenge for many organizations. To mitigate these effects, businesses need swift resolution of data issues with transparent and trustworthy information. However, in our fast-paced digital environment, complex data architectures with more system variables make it difficult to understand the problems. […]
Predictive Analytics Techniques
The process of predictive analytics has three main steps: defining the objectives, collecting relevant data, and developing a predictive model using sophisticated algorithms. These models are further tuned for greater accuracy before being applied to real-world situations like risk analysis or fraud detection. Predictive analytics techniques are at the forefront of modern data science, enabling organizations to […]
Common Data Integrity Issues (and How to Overcome Them)
To say data has “integrity” means that it can be trusted and relied upon and is ultimately useful. Data integrity also conveys a sense of unity and completeness. The greatest challenges to ensuring that data has integrity are any characteristics or events that detract from the data’s usefulness, trustworthiness, and reliability, as well as anything […]