#data-quality

#data-quality

Email marketers face numerous challenges in 2025, including low engagement rates, data quality issues, accurately measuring ROI, and personalization. Experts highlight the need for collaboration across departments to overcome these obstacles.

Government workers have important jobs that are critical to providing important services to taxpayers. If jobs are cut and those services aren't provided or aren't provided in a timely and competent way, there can be significant negative fallout.

The year two status report stresses how the situation is worsening. Declining budgets, staffing constraints, and inadequate statistical integrity protections identified in the 2024 report have intensified in recent months.

What's become exceedingly important is the ability to attract and retain the best cognitive experts... to take these large models and make them very customized towards solving enterprise AI problems.

There is a complete reset in how data is managed and flows around the enterprise. If people want to seize the AI imperative, they have to redo their data platforms in a very big way. And this is where I believe you're seeing all these data acquisitions, because this is the foundation to have a sound AI strategy.

Traditional monitoring fails to meet the needs of complex data organizations; instead, engineers must develop interactive observability frameworks to quickly identify anomalies.

The evaluation tasks within the biomedical text mining community face significant limitations, particularly regarding data representativeness, quality, and participant innovation in solution development.

In our research, we successfully designed a functional material KG by employing fine-tuned large language models (LLMs), assuring traceability throughout the information process.