IBM Journey to AI blog

AUGUST 2, 2023

However, analytics are only as good as the quality of the data, which aims to be error-free, trustworthy, and transparent. According to a Gartner report , poor data quality costs organizations an average of USD $12.9 What is data quality? Data quality is critical for data governance.

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Pickl AI

OCTOBER 11, 2024

It supports compliance with regulations and enhances accessibility, allowing organizations to leverage insights for informed decision-making. Introduction In the realm of technology, business, and science, the terms data and information are often used interchangeably. What is Data? Data can include: Numbers (e.g.,

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Flipboard

JUNE 5, 2023

True data quality simplification requires transformation of both code and data, because the two are inextricably linked. Code sprawl and data siloing both imply bad habits that should be the exception, rather than the norm.

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Pickl AI

OCTOBER 19, 2023

Data quality plays a significant role in helping organizations strategize their policies that can keep them ahead of the crowd. Hence, companies need to adopt the right strategies that can help them filter the relevant data from the unwanted ones and get accurate and precise output.

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Flipboard

MARCH 13, 2023

Presented by BMC Poor data quality costs organizations an average $12.9 Organizations are beginning to recognize that not only does it have a direct impact on revenue over the long term, but poor data quality also increases the complexity of data ecosystems, and directly impacts the … million a year.

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Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications.

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Pickl AI

OCTOBER 18, 2023

How to Scale Your Data Quality Operations with AI and ML: In the fast-paced digital landscape of today, data has become the cornerstone of success for organizations across the globe. Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends.

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Flipboard

JUNE 15, 2023

Data Engineers: We look into Data Engineering, which combines three core practices around Data Management, Software Engineering, and I&O. This focuses …

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Pickl AI

DECEMBER 4, 2023

In the realm of Data Intelligence, the blog demystifies its significance, components, and distinctions from Data Information, Artificial Intelligence, and Data Analysis. Data Intelligence emerges as the indispensable force steering businesses towards informed and strategic decision-making. These insights?

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AI News

SEPTEMBER 17, 2024

Privacy follows closely behind, with 64% of IT professionals urging for more robust rules to protect sensitive information. The survey uncovers a troubling lack of trust in data quality—a cornerstone of successful AI implementation. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Unite.AI

AUGUST 28, 2024

Challenges of Using AI in Healthcare Physicians, doctors, nurses, and other healthcare providers face many challenges integrating AI into their workflows, from displacement of human labor to data quality issues. Some providers might also disregard ethics and use patient data without permission.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

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Snorkel AI

JUNE 22, 2023

Jacomo Corbo is a Partner and Chief Scientist, and Bryan Richardson is an Associate Partner and Senior Data Scientist, for QuantumBlack AI by McKinsey. They presented “Automating Data Quality Remediation With AI” at Snorkel AI’s The Future of Data-Centric AI Summit in 2022. That is still in flux and being worked out.

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Marktechpost

OCTOBER 17, 2024

integrates real-time web search results to ensure that statements are grounded in verified, factual information. The Importance of Grounding in AI Grounding ensures that an AI model’s statements generated or assessed are based on factual and accurate data. Low-quality or biased sources can negatively affect the results.

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IBM Journey to AI blog

OCTOBER 21, 2024

Fragmented data stacks, combined with the promise of generative AI, amplify productivity pressure and expose gaps in enterprise readiness for this emerging technology. While turning data into meaningful intelligence is crucial, users such as analysts and data scientists are increasingly overwhelmed by vast quantities of information.

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Marktechpost

NOVEMBER 19, 2023

One possible solution is finding subsets of data inside incredibly huge datasets to address the issues raised. These subsets should contain all the diversity and information in the original dataset but be easier to handle during processing. The quality of the information should be prioritized over gathering enormous volumes of data.

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IBM Journey to AI blog

MAY 9, 2024

Understanding data governance in healthcare The need for a strong data governance framework is undeniable in any highly-regulated industry, but the healthcare industry is unique because it collects and processes massive amounts of personal data to make informed decisions about patient care. The consequence?

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IBM Journey to AI blog

SEPTEMBER 5, 2024

Everything is data—digital messages, emails, customer information, contracts, presentations, sensor data—virtually anything humans interact with can be converted into data, analyzed for insights or transformed into a product. Managing this level of oversight requires adept handling of large volumes of data.

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Unite.AI

JULY 19, 2024

That's an AI hallucination, where the AI fabricates incorrect information. The consequences of relying on inaccurate information can be severe for these industries. These tools help identify when AI makes up information or gives incorrect answers, even if they sound believable. What Are AI Hallucination Detection Tools?

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IBM Journey to AI blog

DECEMBER 16, 2022

So, instead of wandering the aisles in hopes you’ll stumble across the book, you can walk straight to it and get the information you want much faster. An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more.

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Unite.AI

JANUARY 29, 2024

This article explores the implications of this challenge and advocates for a data-centric approach in AI development to effectively combat misinformation. Understanding the Misinformation Challenge in Generative AI The abundance of digital information has transformed how we learn, communicate, and interact.

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AI News

NOVEMBER 21, 2023

Addressing this gap will require a multi-faceted approach including grappling with issues related to data quality and ensuring that AI systems are built on reliable, unbiased, and representative datasets. Companies have struggled with data quality and data hygiene.

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Marktechpost

NOVEMBER 16, 2024

The study also showed a trade-off between privacy and data quality. Differential privacy protection compromised data quality, while deep learning models improved data quality but increased the risk of re-identification, especially with more training epochs. Check out the Paper.

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AI News

SEPTEMBER 24, 2024

The data collected by the AI-driven vehicle will support ongoing operational reliability at the site, offering valuable information on areas such as marine growth and potential erosion at the foundations. See also: Hugging Face is launching an open robotics project Want to learn more about AI and big data from industry leaders?

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Marktechpost

MAY 7, 2024

The burgeoning expansion of the data landscape, propelled by the Internet of Things (IoT), presents a pressing challenge: ensuring data quality amidst the deluge of information. However, the quality of that data is paramount, especially given the escalating reliance on Machine Learning (ML) across various industries.

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Unite.AI

AUGUST 13, 2024

From virtual assistants like Siri and Alexa to advanced data analysis tools in finance and healthcare, AI's potential is vast. However, the effectiveness of these AI systems heavily relies on their ability to retrieve and generate accurate and relevant information. This is where BM42 comes into play.

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Marktechpost

JUNE 5, 2024

In addition, organizations that rely on data must prioritize data quality review. Data profiling is a crucial tool. For evaluating data quality. Data profiling gives your company the tools to spot patterns, anticipate consumer actions, and create a solid data governance plan.

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Unite.AI

OCTOBER 30, 2024

Data quality is another critical concern. AI systems are only as good as the data fed into them. If the input data is outdated, incomplete, or biased, the results will inevitably be subpar. Another important consideration is data quality.

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Unite.AI

JUNE 12, 2024

The rapid advancement of AI raises questions about data protection, the integrity of AI models, and the safeguarding of proprietary information. Trust in Data Quality Data Quality Issues : Many IT professionals are cautious about the quality of data used in AI systems.

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IBM Journey to AI blog

OCTOBER 2, 2024

Business intelligence (BI) users often struggle to access the high-quality, relevant data necessary to inform strategic decision making. Inconsistent data quality: The uncertainty surrounding the accuracy, consistency and reliability of data pulled from various sources can lead to risks in analysis and reporting.

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AI News

OCTOBER 17, 2024

Data integrity and security emerged as the biggest deterrents to implementing new AI solutions. Executives also reported encountering various AI performance issues, including: Data quality issues (e.g.,

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Unite.AI

JUNE 19, 2024

Data Deluge in Manufacturing The manufacturing industry is experiencing a data revolution driven by the information flood from sensors, IoT devices , and interconnected machinery. This data provides insights into production processes, from equipment performance to product quality.

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Unite.AI

NOVEMBER 15, 2024

It necessitates having access to the right data — data that provides rich context on actual business spend patterns, supplier performance, market dynamics, and real-world constraints. Inadequate access to data means life or death for AI innovation within the enterprise.

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IBM Journey to AI blog

NOVEMBER 29, 2023

Structured synthetic data types are quantitative and includes tabular data, such as numbers or values, while unstructured synthetic data types are qualitative and includes text, images, and video. While a synthetic dataset may achieve high accuracy, it could compromise privacy by including too much of the original data.

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Unite.AI

NOVEMBER 13, 2024

In the coming years, I expect a few key trends to shape the AI and data observability market. Real-time data observability will become more critical as enterprises look to make faster, more informed decisions.

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Unite.AI

JUNE 10, 2024

The company is developing its flagship product, ThinkLabs Copilot, a digital assistant that comprehends the real world through proprietary physics-informed AI digital twins, providing a foundational model for engineering systems. Can you explain what a physics-informed AI digital twin is and how it benefits grid reliability?

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