Tag: data quality
Tips on Building a Winning Data and AI Strategy from JPMC
With $274 billion in revenue last year and $3.3 trillion in assets under management, JPMorgan Chase has more resources than most to devote to building a winning data and AI strategy. But as James Massa, JPMorgan Chase’ Read more…
Monte Carlo Brings GenAI to Data Observability
Monte Carlo has made a name for itself in the field of data observability, where it uses machine learning and other statistical methods to identify quality and reliability issues hiding in big data. With this week’s up Read more…
Quest’s New Report Highlights the Evolving Landscape of Data Intelligence
Organizations are increasingly leveraging data intelligence to enhance their data and analytics, according to an annual report released this week by Quest, a provider of cybersecurity, data performance, and database solu Read more…
AI Has a Data Problem, Appen Report Says
AI may be a priority at American companies, but the difficulty in managing data and obtaining high quality data to train AI models is becoming a bigger hurdle to achieving AI aspirations, according to Appen’s State of Read more…
Astronomer’s High Hopes for New DataOps Platform
Astronomer last month rolled out a new observability product called Astro Observe that’s aimed at giving customers the full picture of how their data is flowing using Apache Airflow, the open source data orchestration Read more…
Monte Carlo Detects Data-Breaking Code Changes
There are many causes of data corruption in our world, including human error, malware, and even cosmic rays. Now the folks at data observability firm Monte Carlo have come up with a way to detect another source of errone Read more…
Data Governance Programs Expand, But Trust in Data Declines, Precisely Finds
As companies begin adopting AI, they’re taking a closer look at their data and ramping up data governance programs. That’s the good news. But upon closer inspection of their data, they’re finding that it’s not up Read more…
Legacy Data Architectures Holding GenAI Back, WEKA Report Finds
While large language models (LLMs) have kickstarted an exciting new phase in AI, companies are not able to satisfy their GenAI goals due to several factors, with poor quality data and legacy data architectures chief amon Read more…
Focus on the Fundamentals for GenAI Success
Humans are prone to look for quick and easy solutions to life’s problems. The tendency toward thriftiness probably is programmed into our DNA. But when it comes to succeeding at generative AI, there are no silver bulle Read more…
Appen CEO Ryan Kolln Discusses the Data Annotation and Labeling Biz on the Big Data Debrief
Appen CEO Ryan Kolln recently joined us on the innaugural edition of the Big Data Debrief to talk about Appen’s work in data annotation and labeling, and how the rise of GenAI will impact the world’s appetite for tru Read more…
GenAI a Top Driver of Data Modernization in the Cloud, Hakkoda Says
One of the top reasons that companies are modernizing their data estates and moving to a centralized cloud data platform is to enable generative AI capabilities, Hakkoda says in its new study, titled “Generative AI Sta Read more…
Unlocking the Full Potential of Data: The Crucial Role of Data Governance in Integrated Analysis
Organizations today are built on data. However, in the quest to become data-driven, businesses must maintain their trust, which becomes challenging with the huge volumes of data generated and collected every day. The qua Read more…
Data Is the Foundation for GenAI, MIT Tech Review Says
Pretrained large language models (LLMs) like GPT-4 and Gemini are great, but real competitive advantage comes from combining LLMs with private data. Unfortunately, there are questions as to how well companies have prepar Read more…
Informatica CEO: Good Data Management Not Optional for AI
The big data era may have started a decade-and-a-half ago, but for many companies, it’s the current AI revolution that’s forcing them to finally get serious about data management, says Informatica CEO Amit Walia. “ Read more…
Data Quality Is A Mess, But GenAI Can Help
A recurring theme in big data over the past two decades is the poor quality of data. No matter how much ink is spilled on the topic, organizations continually seem surprised that the data they want to use for analytics o Read more…
The Top Five Data Labeling Firms According to Everest Group
The process of annotating and labeling data is critical for supervised learning tasks, such as training a large language model (LLM) and other types of machine learning models. However, the need for human cognition and i Read more…
Data Quality Getting Worse, Report Says
For as long as “big data” has been a thing, data quality has been a big question mark. Working with data to make it suitable for analysis was the task that data professionals spent the bulk of their time doing 15 yea Read more…
GenAI Doesn’t Need Bigger LLMs. It Needs Better Data
An exorbitant amount of time and energy is being spent developing and talking about the technology that goes into large language models. While the tech is indeed impressive, businesses that are building generative AI app Read more…
Data Observability in the Age of AI: A Guide for Data Engineers
Data observability refers to the ability to comprehensively monitor and understand the behavior of data within a system. It provides transparency into real-time aspects of the data pipeline beyond data monitoring. These Read more…
Data Quality Top Obstacle to GenAI, Informatica Survey Says
A new survey of data leaders by Informatica points to data quality as the number one obstacle to implementing generative AI. The number of data management tools that companies are using, as well as the fact that a large Read more…
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