insideBIGDATA

JUNE 15, 2023

Jason Smith, Chief Technology Officer, AI & Analytics at Within3, highlights how many life science data sets contain unclean, unstructured, or highly-regulated data that reduces the effectiveness of AI models. Life science companies must first clean and harmonize their data for effective AI adoption.

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KDnuggets

NOVEMBER 22, 2023

This week on KDnuggets: Learn how to perform data quality checks using pandas, from detecting missing records to outliers, inconsistent data entry and more • The top vector databases are known for their versatility, performance, scalability, consistency, and efficient algorithms in storing, indexing, and querying vector embeddings for AI applications (..)

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databricks

AUGUST 1, 2024

At Data and AI Summit, we announced the general availability of Databricks Lakehouse Monitoring. Our unified approach to monitoring data and AI.

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insideBIGDATA

OCTOBER 12, 2024

the data intelligence company, launched its AI Governance solution to help organizations realize value from their data and AI initiatives. The solution ensures that AI models are developed using secure, compliant, and well-documented data. Alation Inc.,

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insideBIGDATA

MAY 1, 2024

In this contributed article, Stephany Lapierre, Founder and CEO of Tealbook, discusses how AI can help streamline procurement processes, reduce costs and improve supplier management, while also addressing common concerns and challenges related to AI implementation like data privacy, ethical considerations and the need for human oversight.

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insideBIGDATA

MAY 28, 2023

iMerit, a leading artificial intelligence (AI) data solutions company, released its 2023 State of ML Ops report, which includes a study outlining the impact of data on wide-scale commercial-ready AI projects.

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Precisely

NOVEMBER 5, 2024

Key Takeaways: Data quality is the top challenge impacting data integrity – cited as such by 64% of organizations. Data trust is impacted by data quality issues, with 67% of organizations saying they don’t completely trust their data used for decision-making. The results are in!

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insideBIGDATA

AUGUST 12, 2023

In this contributed article, Kim Stagg, VP of Product for Appen, knows the only way to achieve functional AI models is to use high-quality data in every stage of deployment.

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KDnuggets

AUGUST 2, 2022

Sadly, it’s often due to a lack of focus on data quality. Many machine learning models fail to deliver.

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Data Science Blog

OCTOBER 1, 2024

Just like a skyscraper’s stability depends on a solid foundation, the accuracy and reliability of your insights rely on top-notch data quality. Enter Generative AI – a game-changing technology revolutionizing data management and utilization. Businesses must ensure their data is clean, structured, and reliable.

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Dataconomy

MAY 27, 2025

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.

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Precisely

APRIL 7, 2025

Read Challenges in Ensuring Data Quality Through Appending and Enrichment The benefits of enriching and appending additional context and information to your existing data are clear but adding that data makes achieving and maintaining data quality a bigger task.

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Dataconomy

APRIL 4, 2025

Data-centric AI is revolutionizing how organizations approach artificial intelligence by shifting the focus from algorithm optimization to the quality of the data supporting these algorithms. This approach recognizes that even the most sophisticated models are only as good as the data they are trained on.

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Dataversity

APRIL 22, 2024

So why are many technology leaders attempting to adopt GenAI technologies before ensuring their data quality can be trusted? Reliable and consistent data is the bedrock of a successful AI strategy.

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Dataconomy

NOVEMBER 12, 2024

OpenAI Orion, the company’s next-generation AI model, is hitting performance walls that expose limitations in traditional scaling approaches. While this might sound impressive, it’s important to note that early stages of AI training typically yield the most dramatic improvements.

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Precisely

JANUARY 9, 2025

Artificial Intelligence (AI) is all the rage, and rightly so. By now most of us have experienced how Gen AI and the LLMs (large language models) that fuel it are primed to transform the way we create, research, collaborate, engage, and much more. Can AIs responses be trusted? A data lake! Can it do it without bias?

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Data Science Dojo

JANUARY 25, 2024

With the advent of generative AI, the complexity of data makes vector embeddings a crucial aspect of modern-day processing and handling of information. Source: robkerr.ai Key roles of vector embeddings in generative AI Generative AI relies on vector embeddings to understand the structure and semantics of input data.

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Analytics Vidhya

JANUARY 2, 2024

This innovative technique aims to generate diverse and high-quality instruction data, addressing challenges associated with duplicate data and limited control over data quality in existing methods.

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Data Science Dojo

SEPTEMBER 15, 2023

AI hallucinations: When language models dream in algorithms. What Are AI Hallucinations ? AI hallucinations occur when a large language model (LLM) generates inaccurate information. An alternative term for AI hallucinations is “confabulation.” Cats need to be fed at least once a day.”

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The Data Administration Newsletter

FEBRUARY 5, 2025

Unsurprisingly, my last two columns discussed artificial intelligence (AI), specifically the impact of language models (LMs) on data curation. addressed some of the […]

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Flipboard

MAY 30, 2025

Generative AI revolutionizes business operations through various applications, including conversational assistants such as Amazons Rufus and Amazon Seller Assistant. AI-generated content provides comprehensive product details that help with clarity and accuracy, which can contribute to product discoverability in customer searches.

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Dataconomy

FEBRUARY 11, 2025

A survey conducted by Carta Healthcare found that while the majority of clinical data abstractors believe artificial intelligence (AI) could improve their workflow, most do not have access to AI-powered tools in their workplace. Half of the respondents also believed AI could improve data quality.

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The Data Administration Newsletter

DECEMBER 4, 2024

We have lots of data conferences here. Over the years, I’ve seen a trend — more and more emphasis on AI. I’ve taken to asking a question at these conferences: What does data quality mean for unstructured data? Frequently. Almost always right here in NYC. This is my version of […]

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Dataversity

MAY 1, 2025

This is the second in a two-part series exploring data quality and the ISO 25000 standard. You recognize that having quality data is important for accurate AI models. Youre with the program.

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Dataconomy

APRIL 17, 2025

Explainable AI is transforming how we view artificial intelligence systems, specifically regarding their decision-making processes. As AI continues to permeate various sectors, the need for understanding how these systems arrive at specific outcomes grows ever more critical. What is explainable AI?

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Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. AI drives the demand for data integrity.

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insideBIGDATA

APRIL 3, 2024

In this contributed article, Jonathan Taylor, CTO of Zoovu, highlights how many B2B executives believe ecommerce is broken in their organizations due to data quality issues.

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Dataconomy

FEBRUARY 11, 2025

AI readiness is a crucial factor in determining an organizations ability to successfully integrate artificial intelligence into its operations. As AI technologies evolve, businesses must adapt by upgrading infrastructure, refining data strategies, and equipping employees with the necessary skills. What is AI readiness?

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Flipboard

DECEMBER 27, 2023

Presented by SQream The challenges of AI compound as it hurtles forward: demands of data preparation, large data sets and data quality, the time sink of long-running queries, batch processes and more. In this VB Spotlight, William Benton, principal product architect at NVIDIA, and others explain how …

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Flipboard

APRIL 15, 2025

Gen AI success starts with business clarity, emotional intelligence, and ethical governance. Leaders must define outcomes and test prototypes quickly to see real value from Gen AI. Effective Gen AI adoption requires addressing resistance, risk, and human factors in integration.

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AWS Machine Learning Blog

NOVEMBER 7, 2024

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle. Generative AI gateway Shared components lie in this part.

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AWS Machine Learning Blog

NOVEMBER 25, 2024

Amazon Web Services (AWS) is excited to be the first major cloud service provider to announce ISO/IEC 42001 accredited certification for AI services, covering: Amazon Bedrock , Amazon Q Business , Amazon Textract , and Amazon Transcribe. Responsible AI is a long-standing commitment at AWS. This is why ISO 42001 is important to us.

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Dataconomy

MARCH 29, 2025

However, an expert in the field says that scaling AI solutions to handle the massive volume of data and real-time demands of large platforms presents a complex set of architectural, data management, and ethical challenges.

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Dataconomy

MARCH 13, 2025

Artificial intelligence is making its way into oncology, but before AI-driven Clinical Decision Support Systems (CDSS) can transform treatment planning, theres a fundamental problem to solve data readiness. AI needs better data to assist oncologists Clinical decision-making in oncology is complex.

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Data Science Dojo

OCTOBER 10, 2023

AI conferences and events are organized to talk about the latest updates taking place, globally. The global market for artificial intelligence (AI) was worth USD 454.12 The global market for artificial intelligence (AI) was worth USD 454.12 Why must you attend AI conferences and events? billion by 2032. billion by 2032.

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AWS Machine Learning Blog

NOVEMBER 15, 2024

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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Precisely

JANUARY 30, 2025

Recognize that artificial intelligence is a data governance accelerator and a process that must be governed to monitor ethical considerations and risk. Integrate data governance and data quality practices to create a seamless user experience and build trust in your data.

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