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 144

Data Quality Machine Learning Automation Big Data 144

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 102

Data Quality Data Scarcity Automation Natural Language Processing 102

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 »

Data Quality 349

Data Quality Data Science Artificial Intelligence Artificial Intelligence 349

AI News

SEPTEMBER 17, 2024

The survey uncovers a troubling lack of trust in data quality—a cornerstone of successful AI implementation. Only 38% of respondents consider themselves ‘very trusting’ of the data quality and training used in AI systems. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

Data Quality 297

Data Quality Big Data AI AI 297

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 113

Data Quality Large Language Models AI Modeling Automation 113

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 284

ML Data Quality Data Drift Artificial Intelligence 284

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 263

Machine Learning Data Quality Data Analysis Algorithm 263

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.

Data Quality 317

Data Quality Algorithm AI AI 317

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 101

Data Quality AI AI 101

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 304

Big Data Data Quality AI AI 304

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 249

AI Chatbots Data Quality Chatbots Large Language Models 249

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 265

Machine Learning Algorithm Data Quality Data Science 265

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 266

Python Data Science Data Quality 266

Analytics Vidhya

FEBRUARY 20, 2023

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

Python 251

Python Data Quality Data Analysis 251

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.

Data Quality 187

Data Quality AI AI 187

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

FEBRUARY 7, 2024

They are huge, complex, and data-hungry. They also need a lot of data to learn from, which can raise data quality, privacy, and ethics issues. In addition, LLMOps provides techniques to improve the data quality, diversity, and relevance and the data ethics, fairness, and accountability of LLMs.

Machine Learning 294

Machine Learning Large Language Models LLM BERT 294

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 261

AI Strategy Automation Data Quality Big Data 261

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 282

Big Data Data Quality Generative AI Explainability 282

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 292

Big Data Generative AI Explainability AI 292

IBM Journey to AI blog

MAY 9, 2024

At the same time, implementing a data governance framework poses some challenges, such as data quality issues, data silos security and privacy concerns. Data quality issues Positive business decisions and outcomes rely on trustworthy, high-quality data.

ETL 213

ETL Data Quality Automation Metadata 213

IBM Journey to AI blog

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Data Ingestion 222

Data Ingestion Data Integration Data Quality LLM 222

Cassie Kozyrkov

SEPTEMBER 26, 2023

The data quality crisis no one is talking about Continue reading on Medium »

Data Quality 147

Data Quality Data Science Artificial Intelligence Artificial Intelligence 147

Cassie Kozyrkov

SEPTEMBER 26, 2023

The data quality crisis no one is talking about Continue reading on Towards Data Science »

Data Quality 147

Data Quality Data Science Artificial Intelligence Artificial Intelligence 147

IBM Journey to AI blog

MAY 9, 2023

Data: the foundation of your foundation model Data quality matters. An AI model trained on biased or toxic data will naturally tend to produce biased or toxic outputs. When objectionable data is identified, we remove it, retrain the model, and repeat. Data curation is a task that’s never truly finished.

Data Platform 347

Data Platform AI AI Automation 347

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.

Explainability 220

Explainability AI AI LLM 220

IBM Journey to AI blog

NOVEMBER 21, 2023

A schema registry is essentially an agreement of the structure of your data within your Kafka environment. Having a well-managed schema registry is not just a technical necessity but also contributes to the strategic goals of treating data as a valuable product and helps tremendously on your data-as-a-product journey.

Data Quality 292

Data Quality Metadata 292

IBM Journey to AI blog

OCTOBER 22, 2024

The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it.

Data Integration 256

Data Integration ETL Business Intelligence Data Quality 256

Unite.AI

JUNE 19, 2024

Manufacturers must adopt strict cybersecurity practices to protect their data while adhering to regulatory requirements, maintaining trust, and safeguarding their operations. Data Quality and Preprocessing The effectiveness of AI applications in manufacturing heavily depends on the quality of the data fed into the models.

Data Quality 200

Data Quality Data Scientist Machine Learning AI 200

IBM Journey to AI blog

OCTOBER 21, 2024

million annually due to poor data quality. This is where data intelligence solutions prove their worth, by helping to ensure that data is not only abundant but also precise, accessible and governed by quality standards. However, diving into analytics without clear direction can lead to confusion and inefficiency.

Data Quality 218

Data Quality Big Data Data Scientist Artificial Intelligence 218

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 200

Deep Learning Data Science Data Quality Neural Network 200

AI News

DECEMBER 19, 2023

Streambased adds a proprietary acceleration technology layer on top of Kafka that makes the platform suitable for the type of demanding analytics use cases data scientists and other analysts want to perform.

Big Data 300

Big Data Explainability Data Scientist AI 300

Flipboard

NOVEMBER 13, 2024

In the quest to uncover the fundamental particles and forces of nature, one of the critical challenges facing high-energy experiments at the Large Hadron Collider (LHC) is ensuring the quality of the vast amounts of data collected. The new system was deployed in the barrel of the ECAL in 2022 and in the endcaps in 2023.

Algorithm 157

Algorithm Data Quality Machine Learning Neural Network 157

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 …

Generative AI 181

Generative AI Data Quality Explainability AI 181

IBM Journey to AI blog

SEPTEMBER 5, 2024

Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success. Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality.

Metadata 188

Metadata Data Quality Auto-classification DevOps 188

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 169

Data Analysis Data Quality 169