Remove 2030 Remove Data Governance Remove Data Quality
article thumbnail

It’s 2025. Are your data strategies strong enough to de-risk AI adoption?

CIO Business Intelligence

Data readiness and governance are critical for AI success Getting these foundational aspects of AI governance in place will be critical to successful adoption, and for unlocking an opportunity that the Tech Council of Australia estimates could contribute $45 billion to $115 billion per year to the Australian economy by 2030.

Risk 111
article thumbnail

Gartner Data & Analytics Summit 2022 in London: 3 Key Takeaways

Alation

Synthetic data will be invaluable for avoiding privacy violations in the future, and Gartner predicts that by 2025, synthetic data will enable organizations to avoid 70% of privacy violation sanctions. Gartner predicts that by 2030, synthetic data will completely overshadow real data in AI models. Data Governance.

Insiders

Sign Up for our Newsletter

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

article thumbnail

Semantic Technologies and Knowledge Graphs in Healthcare: An Interview with Isabelle de Zegher

Ontotext

Europe’s Digital Decade declaration targets for 2030 outline the digital rights and principles complementing data protection, privacy legislation and other rights. This includes Principle 4, “citizens able to engage and have control over their own data” (including their health data).

article thumbnail

Elevating Productivity: Cloudera Data Engineering Brings External IDE Connectivity to Apache Spark

Cloudera

AI pioneer Andrew Ng recently underscored that robust data engineering is foundational to the success of data-centric AI —a strategy that prioritizes data quality over model complexity.

article thumbnail

Prioritizing AI investments: Balancing short-term gains with long-term vision

CIO Business Intelligence

Start with data as an AI foundation Data quality is the first and most critical investment priority for any viable enterprise AI strategy. Data trust is simply not possible without data quality. A decision made with AI based on bad data is still the same bad decision without it.