IBM Journey to AI blog

JUNE 12, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

Data Quality 187

Data Quality Automation Data Ingestion Data Platform 187

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.

Data Quality 184

Data Quality Data Scientist Automation Data Platform 184

Flipboard

NOVEMBER 14, 2023

Modern data quality practices leverage advanced technologies, automation, and machine learning to handle diverse data sources, ensure real-time processing, and foster collaboration across stakeholders.

Data Quality 145

Data Quality Machine Learning Automation Big Data 145

AI News

JANUARY 31, 2025

They must demonstrate tangible ROI from AI investments while navigating challenges around data quality and regulatory uncertainty. After all, isnt ensuring strong data governance a core principle that the EU AI Act is built upon? To adapt, companies must prioritise strengthening their approach to data quality.

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Data Quality Big Data AI AI 287

Unite.AI

MARCH 16, 2025

To operate effectively, multimodal AI requires large amounts of high-quality data from multiple modalities, and inconsistent data quality across modalities can affect the performance of these systems.

AI 259

AI AI Data Quality Natural Language Processing 259

AI News

DECEMBER 9, 2024

The best way to overcome this hurdle is to go back to data basics. Organisations need to build a strong data governance strategy from the ground up, with rigorous controls that enforce data quality and integrity. The many obstacles holding companies back from rolling out AI tools can be overcome without too much trouble.

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Explainability AI AI Data Quality 285

Cassie Kozyrkov

FEBRUARY 25, 2023

The industry-wide neglect of data design and data quality (and what you can do about it) Continue reading on Towards Data Science »

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Data Quality Data Science Artificial Intelligence Artificial Intelligence 349

Unite.AI

DECEMBER 27, 2024

Its not a choice between better data or better models. The future of AI demands both, but it starts with the data. Why Data Quality Matters More Than Ever According to one survey, 48% of businesses use big data , but a much lower number manage to use it successfully. Why is this the case?

Data Quality 130

Data Quality Data Drift Explainability Big Data 130

Unite.AI

NOVEMBER 1, 2024

This is creating a major headache for corporate data science teams who have had to increasingly focus their limited resources on cleaning and organizing data. In a recent state of engineering report conducted by DBT , 57% of data science professionals cited poor data quality as a predominant issue in their work.

AI Development 162

AI Development AI Developer Data Quality Data Science 162

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.

Automation 189

Automation Data Quality AI AI 189

Analytics Vidhya

MAY 30, 2023

Introduction In the realm of machine learning, the veracity of data holds utmost significance in the triumph of models. Inadequate data quality can give rise to erroneous predictions, unreliable insights, and overall performance.

Machine Learning 325

Machine Learning Data Quality Data Analysis Algorithm 325

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.

Data Quality 127

Data Quality AI AI 127

Unite.AI

NOVEMBER 13, 2024

These trends will elevate the role of data observability in ensuring that organizations can scale their AI initiatives while maintaining high standards for data quality and governance. As organizations increasingly rely on AI to drive business decisions, the need for trustworthy, high-quality data becomes even more critical.

Machine Learning 147

Machine Learning Large Language Models Data Quality Automation 147

Analytics Vidhya

SEPTEMBER 2, 2021

This article was published as a part of the Data Science Blogathon Overview Running data projects takes a lot of time. Poor data results in poor judgments. Running unit tests in data science and data engineering projects assures data quality. You know your code does what you want it to do.

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Python Data Science Data Quality 342

Marktechpost

JULY 11, 2024

In conclusion, AgentInstruct represents a breakthrough in generating synthetic data for AI training. Automating the creation of diverse and high-quality data addresses the critical issues of manual curation and data quality, leading to significant improvements in the performance and reliability of large language models.

Data Quality 112

Data Quality Large Language Models AI Modeling Automation 112

Analytics Vidhya

MARCH 13, 2024

Introduction Whether you’re a fresher or an experienced professional in the Data industry, did you know that ML models can experience up to a 20% performance drop in their first year? Monitoring these models is crucial, yet it poses challenges such as data changes, concept alterations, and data quality issues.

ML 319

ML Data Quality Data Drift Artificial Intelligence 319

AI News

DECEMBER 13, 2023

Phi-2’s achievements are underpinned by two key aspects: Training data quality: Microsoft emphasises the critical role of training data quality in model performance. Phi-2 leverages “textbook-quality” data, focusing on synthetic datasets designed to impart common sense reasoning and general knowledge.

Big Data 341

Big Data Data Quality AI AI 341

Unite.AI

NOVEMBER 29, 2024

The process begins with data ingestion and preprocessing, where prescriptive AI gathers information from different sources, such as IoT sensors, databases, and customer feedback. It organizes it by filtering out irrelevant details and ensuring data quality.

Algorithm 276

Algorithm AI AI Data Ingestion 276

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.

AI Chatbots 305

AI Chatbots Data Quality Chatbots Large Language Models 305

Unite.AI

MARCH 10, 2025

Data Quality: The Foundational Strength of Business-driven AI The success of AI-powered transformation depends on high-quality, well-structured data. Organizations must, therefore, design their AI strategies around their core business objectives, ensuring their data ecosystems support AI-driven decision-making.

AI Modeling 133

AI Modeling Generative AI AI Strategy Data Quality 133

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. Interoperability Problems and Data Quality Issues Data from different sources can often fail to integrate seamlessly.

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Data Quality Algorithm AI AI 317

Unite.AI

DECEMBER 17, 2024

Your organization must also make certain other strategic considerations in order to preserve security and data quality. Its essential to invest in high-quality, secure data infrastructureand ensure that they are trained on accurate and diverse datasets.

Automation 246

Automation Explainability AI AI 246

Analytics Vidhya

DECEMBER 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction In machine learning, the data is an essential part of the training of machine learning algorithms. The amount of data and the data quality highly affect the results from the machine learning algorithms.

Machine Learning 291

Machine Learning Algorithm Data Quality Data Science 291

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.

Automation 269

Automation ChatGPT AI AI 269

Analytics Vidhya

FEBRUARY 20, 2023

Introduction Whenever we talk about building better forecasting models, the first and foremost step starts with detecting.

Python 291

Python Data Quality Data Analysis 291

Unite.AI

JANUARY 1, 2025

Teams with varied backgrounds are better at spotting blind spots in data and designing systems that work for a broader range of users. The Bottom Line AI has incredible potential, but its effectiveness depends on its data quality. Inclusive teams lead to better outcomes, making AI brighter and fairer.

AI 182

AI AI Algorithm Large Language Models 182

Analytics Vidhya

DECEMBER 28, 2022

Choosing the best appropriate activation function can help one get better results with even reduced data quality; hence, […]. Introduction In deep learning, the activation functions are one of the essential parameters in training and building a deep learning model that makes accurate predictions.

Deep Learning 277

Deep Learning Data Science Data Quality Neural Network 277

Unite.AI

FEBRUARY 1, 2025

Let us look at how Allen AI built this model: Stage 1: Strategic Data Selection The team knew that model quality starts with data quality. But here is the key insight: they did not just aggregate data – they created targeted datasets for specific skills like mathematical reasoning and coding proficiency.

AI Developer 262

AI Developer AI Development AI Modeling Data Quality 262

Analytics Vidhya

AUGUST 28, 2024

Introduction Managing databases often means dealing with duplicate records that can complicate data analysis and operations. Whether you’re cleaning up customer lists, transaction logs, or other datasets, removing duplicate rows is vital for maintaining data quality.

Data Analysis 248

Data Analysis Data Quality 248

Unite.AI

JANUARY 27, 2025

Enterprise-wide AI adoption faces barriers like data quality, infrastructure constraints, and high costs. While Cirrascale does not offer Data Quality type services, we do partner with companies that can assist with Data issues. How does Cirrascale address these challenges for businesses scaling AI initiatives?

Deep Learning 162

Deep Learning Data Quality ML Engineer Data Scientist 162

Unite.AI

JANUARY 2, 2025

AI has the opportunity to significantly improve the experience for patients and providers and create systemic change that will truly improve healthcare, but making this a reality will rely on large amounts of high-quality data used to train the models. Why is data so critical for AI development in the healthcare industry?

AI Modeling 306

AI Modeling Algorithm AI Tools AI Development 306

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.

Big Data 333

Big Data Data Quality Generative AI Explainability 333

AI News

SEPTEMBER 27, 2024

First is clear alignment of the data strategy with the business goals, making sure the technology teams are working on what matters the most to the business. Second, is data quality and accessibility, the quality of the data is critical. Poor data quality will lead to inaccurate insights.

AI Strategy 299

AI Strategy Automation Data Quality Big Data 299

Unite.AI

SEPTEMBER 23, 2024

From technical limitations to data quality and ethical concerns, it’s clear that the journey ahead is still full of obstacles. Additionally, as data quality improves and companies develop more robust data-sharing practices, AI systems will become better equipped to make groundbreaking discoveries.

Generative AI 294

Generative AI Data Quality AI AI 294

IBM Journey to AI blog

JANUARY 23, 2023

Simply put, data governance is the process of establishing policies, procedures, and standards for managing data within an organization. It involves defining roles and responsibilities, setting standards for data quality, and ensuring that data is being used in a way that is consistent with the organization’s goals and values.

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Data Quality AI AI 187

AI News

MAY 3, 2024

“Managing dynamic data quality, testing and detecting for bias and inaccuracies, ensuring high standards of data privacy, and ethical use of AI systems all require human oversight,” he said.

Big Data 320

Big Data Generative AI Explainability AI 320

Unite.AI

MARCH 14, 2025

Add in common issues like poor data quality, scalability limits, and integration headaches, and its easy to see why so many GenAI PoCs fail to move forward. Beyond the Hype: The Reality of GenAI PoCs GenAI adoption is clearly on the rise, but the true success rate of PoCs remains unclear.

Automation 113

Automation Data Quality LLM Generative AI 113