KDnuggets

MARCH 23, 2023

This article highlights the significance of ensuring high-quality data and presents six key dimensions for measuring it. These dimensions include Completeness, Consistency, Integrity, Timelessness, Uniqueness, and Validity.

Data Quality 306

Data Quality Data Engineer Data Engineering Data Engineering 306

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.

Data Quality 259

Data Quality AI AI Big Data 259

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.

Data Quality 416

Data Quality AI AI Analytics 416

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.

AI 368

AI Data Quality AI Big Data 368

Towards AI

OCTOBER 31, 2024

Data analytics has become a key driver of commercial success in recent years. The ability to turn large data sets into actionable insights can mean the difference between a successful campaign and missed opportunities. Flipping the paradigm: Using AI to enhance data quality What if we could change the way we think about data quality?

Data Quality 122

Data Quality Analytics Analytics Clean Data 122

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.

Data Quality 221

Data Quality ML ML Artificial Intelligence 221

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.

Python 342

Python Data Science Data Quality Data Engineer 342

The Data Administration Newsletter

NOVEMBER 20, 2024

Data quality issues continue to plague financial services organizations, resulting in costly fines, operational inefficiencies, and damage to reputations. Key Examples of Data Quality Failures — […]

Data Quality 120

Data Quality Data Silos Data Governance 120

The Data Administration Newsletter

MAY 4, 2022

Getting to great data quality need not be a blood sport! This article aims to provide some practical insights gained from enterprise master data quality projects undertaken within the past […].

Data Quality 114

Data Quality 114

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 Machine Learning Algorithm Data Quality 291

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.

Data Quality 114

Data Quality AI AI Data Governance 114

Analytics Vidhya

DECEMBER 28, 2022

This article was published as a part of the Data Science Blogathon. Choosing the best appropriate activation function can help one get better results with even reduced data quality; hence, […].

Deep Learning 277

Deep Learning Deep Learning Data Quality Data Science 277

insideBIGDATA

OCTOBER 12, 2024

The solution ensures that AI models are developed using secure, compliant, and well-documented data.

AI 365

AI AI Data Quality Data Governance 365

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.

Big Data 243

Big Data Big Data Data Quality AI 243

Precisely

JANUARY 9, 2024

Data can only deliver business value if it has high levels of data integrity. That starts with good data quality, contextual richness, integration, and sound data governance tools and processes. This article focuses primarily on data quality. How can you assess your data quality?

Data Quality 98

Data Quality Database Data Governance Analytics 98

Dataversity

NOVEMBER 6, 2023

This is my monthly check-in to share with you the people and ideas I encounter as a data evangelist with DATAVERSITY. This month we’re talking about Data Quality (DQ). Read last month’s column here.)

Data Quality 119

Data Quality Data Governance 119

Smart Data Collective

SEPTEMBER 29, 2022

Find out in this article how your company can benefit from the use of OCR. This article reveals all! The post Data-Driven Companies Leverage OCR for Optimal Data Quality appeared first on SmartData Collective. Even so, it takes time and can quickly become an obstacle to the smooth running of your business.

Data Quality 142

Data Quality Big Data Big Data Artificial Intelligence 142

Dataversity

OCTOBER 25, 2023

In fact, it’s been more than three decades of innovation in this market, resulting in the development of thousands of data tools and a global data preparation tools market size that’s set […] The post Why Is Data Quality Still So Hard to Achieve? appeared first on DATAVERSITY.

Data Quality 104

Data Quality Data Preparation Algorithm Data Silos 104

Dataversity

FEBRUARY 13, 2023

The key to being truly data-driven is having access to accurate, complete, and reliable data. In fact, Gartner recently found that organizations believe […] The post How to Assess Data Quality Readiness for Modern Data Pipelines appeared first on DATAVERSITY.

Data Pipeline 98

Data Pipeline Data Quality Data Silos Data Governance 98

Dataversity

APRIL 1, 2024

This reliance has spurred a significant shift across industries, driven by advancements in artificial intelligence (AI) and machine learning (ML), which thrive on comprehensive, high-quality data.

Data Quality 69

Data Quality Artificial Intelligence Artificial Intelligence Machine Learning 69

Dataversity

JULY 12, 2024

At their core, LLMs are trained on large amounts of content and data, and the architecture […] The post RAG (Retrieval Augmented Generation) Architecture for Data Quality Assessment appeared first on DATAVERSITY. It is estimated that by 2025, 50% of digital work will be automated through these LLM models.

Data Quality 64

Data Quality Artificial Intelligence Artificial Intelligence AI 64

insideBIGDATA

OCTOBER 31, 2023

In this contributed article, Lior Gavish, CTO and Co-Founder of Monte Carlo, outlines some of the ways companies can erase themselves from ever appearing in these bad data horror stories, ranging from simple tips to bolster governance within their organization, to tools and best practices that will save data teams the time, hassle, and headache that (..)

Data Quality 284

Data Quality Big Data Big Data 284

Dataversity

AUGUST 1, 2024

Welcome to the latest edition of Mind the Gap, a monthly column exploring practical approaches for improving data understanding and data utilization (and whatever else seems interesting enough to share). Last month, we explored the rise of the data product. This month, we’ll look at data quality vs. data fitness.

Data Quality 59

Data Quality Data Governance 59

Flipboard

JUNE 15, 2023

This article is part of a VB special issue. Read the full series here: Building the foundation for customer data quality. The rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies is pushing the boundaries of what can be achieved in marketing, customer experience …

Artificial Intelligence 123

Artificial Intelligence Artificial Intelligence Data Quality Machine Learning 123

The Data Administration Newsletter

SEPTEMBER 18, 2024

As organizations rush headlong into digital transformation initiatives, a critical factor often gets overlooked: data quality.

Data Quality 52

Data Quality Data Governance 52

Dataversity

SEPTEMBER 16, 2024

Public sector agencies increasingly see artificial intelligence as a way to reshape their operations and services, but first, they must have confidence in their data. Accurate information is crucial to delivering essential services, while poor data quality can have far-reaching and sometimes catastrophic consequences.

Data Quality 52

Data Quality Artificial Intelligence Artificial Intelligence AI 52

The Data Administration Newsletter

DECEMBER 4, 2024

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

Data Quality 52

Data Quality AI AI Artificial Intelligence 52

The Data Administration Newsletter

FEBRUARY 21, 2024

Many Data Governance or Data Quality programs focus on “critical data elements,” but what are they and what are some key features to document for them? A critical data element is any data element in your organization that has a high impact on your organization’s ability to execute its business strategy.

Data Governance 105

Data Governance Data Quality 105

Dataversity

NOVEMBER 7, 2022

Data quality issues have been a long-standing challenge for data-driven organizations. Even with significant investments, the trustworthiness of data in most organizations is questionable at best. Gartner reports that companies lose an average of $14 million per year due to poor data quality.

Data Observability 97

Data Observability Data Quality Data Governance 97

Smart Data Collective

APRIL 5, 2022

Drone surveyors must also know how to gather and use data properly. They will need to be aware of the potential that data can bring to entities using drones. Indiana Lee discussed these benefits in an article for Drone Blog. You will also want to know how to harvest the data that you get.

Data Quality 121

Data Quality Big Data Big Data Analytics 121

Dataversity

SEPTEMBER 25, 2023

In an era where large language models (LLMs) are redefining AI digital interactions, the criticality of accurate, high-quality, and pertinent data labeling emerges as paramount. That means data labelers and the vendors overseeing them must seamlessly blend data quality with human expertise and ethical work practices.

Data Quality 104

Data Quality AI AI Data Governance 104

Data Science Dojo

OCTOBER 10, 2023

The event is for anyone interested in learning about generative AI and data storytelling, including business leaders, data scientists, and enthusiasts. Data storytelling is the process of using data to communicate a story in a way that is engaging and informative.

AI 243

AI AI Artificial Intelligence Artificial Intelligence 243

The Data Administration Newsletter

NOVEMBER 20, 2024

In my last article, “The Shift from Syntactic to Semantic Data Curation and What It Means for Data Quality” published in the August 2024 issue of this newsletter, I argued how the adoption of generative AI will change the focus and scope of data quality management (DQM).

Data Quality 52

Data Quality AI AI 52

Data Science Connect

JULY 26, 2023

A recent article on Fagenwasanni.com explores the global implications of this phenomenon and how it is reshaping the future of telecommunications. In this article, we delve deeper into the key insights from the original piece to understand the significant impact of IoT on data scientists and the world at large.

Internet of Things 130

Internet of Things Data Scientist Big Data Big Data 130

Dataversity

JANUARY 19, 2024

Do you know the costs of poor data quality? Below, I explore the significance of data observability, how it can mitigate the risks of bad data, and ways to measure its ROI. Data has become […] The post Putting a Number on Bad Data appeared first on DATAVERSITY.

Data Observability 72

Data Observability Data Quality Data Governance 72

Data Science Dojo

OCTOBER 9, 2023

However, collecting and labeling real-world data can be costly, time-consuming, and inaccurate. Synthetic data offers a solution to these challenges. Scalability: Easily generate synthetic data for large-scale projects. Accuracy: Synthetic data can match real data quality.

Machine Learning 195

Machine Learning Machine Learning Data Quality 195

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. Both approaches aim to improve data quality and enable accurate analysis.

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ETL Data Quality Data Warehouse Database 97