Remove Data Lake Remove Data Quality Remove Strategy Remove Technology
article thumbnail

Data architecture strategy for data quality

IBM Big Data Hub

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

article thumbnail

Navigating the Chaos of Unruly Data: Solutions for Data Teams

DataKitchen

The core issue plaguing many organizations is the presence of out-of-control databases or data lakes characterized by: Unrestrained Data Changes: Numerous users and tools incessantly alter data, leading to a tumultuous environment. Monitor freshness, schema changes, volume, and column health are standard.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Avoid generative AI malaise to innovate and build business value

CIO Business Intelligence

The research cited a lack of talent and skills to work with the technology (62%), unclear AI and GenAI investment priorities (47%), and the absence of a strategy for responsible AI (41%) as the top three obstacles. Reach consensus on strategy. GenAI requires high-quality data. This playbook can help.

Data Lake 121
article thumbnail

Analyzing the business-case approach Perdue Farms takes to derive value from data

CIO Business Intelligence

Mark Booth: We have a growth strategy to improve our business, and to support that, we’re driving a transformation in technology and business processes. But the more challenging work is in making our processes as efficient as possible so we capture the right data in our desire to become a more data-driven business.

Data Lake 116
article thumbnail

CIOs weigh where to place AI bets — and how to de-risk them

CIO Business Intelligence

Amid the turbulence of AI, technologies are emerging rapidly, startups are clamoring for attention, and hyperscalers are scrambling to corral market share. Brian Hopkins, vice president for emerging technology at Forrester Research, agrees. The CIO has strategies in place to address all three. The opportunity is too big.

Risk 125
article thumbnail

A comparative assessment of digital transformation in Italy

CIO Business Intelligence

It’s universally accepted that to thrive, enterprises must embrace transformation through technology. The challenge of digital transformation projects lies not so much in the technological implementation, but in the operational change required of people and the entire business organization,” he says.

article thumbnail

Putting the Business Back Into Business Innovation

Timo Elliott

The future is enabled by technology, but it’s not about the technical infrastructures: it’s about optimizing end-to-end processes, business capabilities, and business ecosystems. And that’s where SAP Business Technology Platform (SAP BTP) comes in. The analysts call this a data mesh or data fabric strategy.

Data Lake 105