article thumbnail

Data quality

Dataconomy

Data quality is an essential factor in determining how effectively organizations can use their data assets. In an age where data is often touted as the new oil, the cleanliness and reliability of that data have never been more critical. What is data quality? million annually.

article thumbnail

The 2016 Crystal Ball – What’s Next in Data?

Alation

Considering what we’ve seen this year in industry trends and patterns, we have compiled some predictions for 2016 from our co-founders at Alation. Venky Ganti, CTO & Co-Founder: Data sprawl will finally hit its threshold. Data sprawl has been prevalent for several years. 2016 will be the year of the “logical data warehouse.”

professionals

Sign Up for our Newsletter

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

article thumbnail

AI hallucinations: Are AI models like Chat GPT doomed to always hallucinate?

Data Science Dojo

Inaccuracies span a spectrum, from odd and inconsequential instances—such as suggesting the Golden Gate Bridge’s relocation to Egypt in 2016—to more consequential and problematic scenarios. Generation method: Training and generation methods, even with consistent and reliable data, can contribute to hallucinations.

AI 365
article thumbnail

Data Fabric and Address Verification Interface

IBM Data Science in Practice

Data fabric is defined by IBM as “an architecture that facilitates the end-to-end integration of various data pipelines and cloud environments through the use of intelligent and automated systems.” The concept was first introduced back in 2016 but has gained more attention in the past few years as the amount of data has grown.

article thumbnail

The Hidden Cost of Poor Training Data in Machine Learning: Why Quality Matters

How to Learn Machine Learning

This article explores real-world cases where poor-quality data led to model failures, and what we can learn from these experiences. By the end, you’ll see why investing in quality data is not just a good idea, but a necessity. Why Does Data Quality Matter? The outcome?

article thumbnail

Efficient continual pre-training LLMs for financial domains

AWS Machine Learning Blog

Preprocessing – You might consider a series of preprocessing steps to improve data quality and training efficiency. For example, certain data sources can contain a fair number of noisy tokens; deduplication is considered a useful step to improve data quality and reduce training cost. the SEC assigned identifier).

AWS 133
article thumbnail

10 Years Later: Who’s the GOAT of Data Catalogs?

Alation

March 2015: Alation emerges from stealth mode to launch the first official data catalog to empower people in enterprises to easily find, understand, govern and use data for informed decision making that supports the business. April 2016: Tesco Group becomes first customer outside North America.