#data-quality

#data-quality

Your sales rep finally reaches out to a "hot lead" that marketing flagged weeks ago, only to discover that the contact no longer works there. Or worse, the company has merged, and your CRM still lists them under an outdated domain. It's frustrating, time-wasting, and surprisingly common. CRM systems are supposed to be the single source of truth for customer relationships. Yet, for many businesses, that "truth" becomes outdated faster than they realize.

Almost half of respondents to Ocient's "From Roadmap to Reality" report say that their companies have not experienced meaningful revenue growth from artificial intelligence (AI) investments due to "poor data quality and overtaxed infrastructures." The data analytics firm further found that "security and compliance pressures" are "shaping enterprise deployment strategies that prioritize flexibility and cost savings, driving movement away from the cloud."

Over 40 minutes, the panel returned again and again to three themes: data quality, organizational alignment and cultural readiness. The consensus was clear: AI doesn't create order from chaos. If organizations don't evolve their culture and their standards, AI will accelerate dysfunction, not fix it. Clean data isn't optional anymore Allen set the tone from the executive perspective. He argued that enterprises must build alignment on high-quality, structured and standardized data within teams and across workflows, applications and departments.

Retail media promises billions in new revenue, but for grocers, the real test is whether their data can deliver. By 2025, RMN revenue is projected to hit $176.9 billion globally, overtaking combined TV and streaming revenues and accounting for 15.9% of total ad spend ( GroupM, This Year Next Year 2024 ). For grocery retailers running on razor-thin margins, this feels like salvation.

"What we had noticed was there was an underlying problem with our data," Ahuja said. When her team investigated what had happened, they found that Salesforce had published contradictory "knowledge articles" on its website."It wasn't actually the agent. It was the agent that helped us identify a problem that always existed," Ahuja said. "We turned it into an auditor agent that actually checked our content across our public site for anomalies. Once we'd cleaned up our underlying data, we pointed it back out, and it's been functional."

The Government Accountability Office (GAO) said that data it reviewed from 23 key US government agencies (out of 24, as the Pentagon was excluded from this report) indicated there were at least 63,934 full-time federal cybersecurity employees, costing the government around $9.3 billion per year. An additional 4,151 contractors were reported to the GAO, and those cost taxpayers an additional $5.2 billion.

We were able to confirm just 11 reported incidents, either directly with schools or through media reports. In 161 cases, schools or districts attested that no incident took place or couldn't confirm one. In at least four cases, we found, something did happen, but it didn't meet the government's parameters for a shooting. About a quarter of schools didn't respond to our inquiries.

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.

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.