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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Data Quality Automation Data Scientist Data Platform 164

SAS Software

MARCH 14, 2024

Data quality is a cornerstone for integrating large language models (LLMs) into organizations. High-quality data is the lifeblood that ensures the accuracy, relevance, and reliability of the model's outputs. The adage "garbage in, garbage out" holds particularly true here.

Large Language Models 62

Large Language Models Data Quality Generative AI AI 62

SAS Software

APRIL 27, 2023

Data quality: The foundation for trustworthy AI was published on SAS Voices by Reggie Townsend After a pandemic, global supply chain disruptions and resulting economic fragility, executives understandably consider adaptability, durability and how best to operate with a strength of character – all attributes that define resilience.

Data Quality 101

Data Quality AI AI 101

SAS Software

JANUARY 30, 2024

It reflects the immense value of high-quality data and a strategic approach to data management. At the heart of any successful modern enterprise lies a robust data strategy coupled with stringent data quality standards.

Data Quality 62

Data Quality 62

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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Data Quality ETL Machine Learning Data Ingestion 52

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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Data Quality Data Integration Machine Learning Metadata 52

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.

Data Quality 101

Data Quality Big Data Machine Learning 101

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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Data Quality Big Data Data Science Machine Learning 80

Flipboard

FEBRUARY 7, 2023

Follow as we dive into the evolution of personalization, consumer sentiments around data privacy & brand communications efforts, and how data quality can enable brands to reduce CX gaps. Today’s consumers have high expectations for brands, including expectations for highly personalized experiences.

Data Quality 82

Data Quality 82

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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Data Quality ML Natural Language Processing Machine Learning 52

Mlearning.ai

JUNE 10, 2023

Bad Strategies for Implementing Data Quality! Continue reading on MLearning.ai »

Data Quality 52

Data Quality ML Data Science 52

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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Data Quality Software Engineer Big Data Machine Learning 96

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.

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ML Data Quality Data Drift Artificial Intelligence 306

databricks

MAY 30, 2023

Faced with clinician shortages, an aging population, and stagnant health outcomes, the healthcare industry has the potential to greatly benefit from disruptive technologies.

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Data Quality 81

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 291

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 310

Machine Learning Data Quality Data Analysis Algorithm 310

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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AI Chatbots Data Quality Chatbots Large Language Models 293

IBM Journey to AI blog

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

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Data Quality Data Integration Metadata Automation 171

Cassie Kozyrkov

SEPTEMBER 26, 2023

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

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Data Quality Data Science Artificial Intelligence Artificial Intelligence 147

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 184

Cassie Kozyrkov

SEPTEMBER 26, 2023

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

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Data Quality Data Science Artificial Intelligence Artificial Intelligence 147

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 252

Big Data Data Quality AI AI 252

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 284

Machine Learning Algorithm Data Quality Data Science 284

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 259

Deep Learning Data Quality Data Science Neural Network 259

Unite.AI

DECEMBER 23, 2023

Maintaining Data Quality: The execution of any APM strategy can only be as good as the source data used to make conclusions about what needs to be done. Challenges in Implementing Asset Performance Management While organizations do understand the importance of APM strategies, roadblocks can arise during execution.

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Data Quality Big Data Artificial Intelligence Artificial Intelligence 182

IBM Journey to AI blog

DECEMBER 16, 2022

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. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Metadata Data Quality Data Discovery Automation 130

Analytics Vidhya

FEBRUARY 20, 2023

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

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Python Data Quality Data Analysis 284

Analytics Vidhya

NOVEMBER 8, 2023

In the data-driven world […] The post Monitoring Data Quality for Your Big Data Pipelines Made Easy appeared first on Analytics Vidhya. Determine success by the precision of your charts, the equipment’s dependability, and your crew’s expertise. A single mistake, glitch, or slip-up could endanger the trip.

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Data Quality Big Data Python 327

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 Quality Data Science 322

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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Generative AI Data Quality Explainability AI 155

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

Unite.AI

JANUARY 29, 2024

As these smaller models prove their effectiveness, they can be gradually scaled up, maintaining the focus on data quality. This controlled scaling allows for continuous assessment and refinement, ensuring the AI models remain accurate and aligned with the principles of the data-centric approach.

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Generative AI Data Quality AI Modeling AI 204

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 231

Big Data Data Quality Generative AI Large Language Models 231

Pickl AI

OCTOBER 11, 2023

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data. What is Data Observability?

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Data Quality Metadata Automation Data Integration 52

Unite.AI

JULY 31, 2023

AI algorithms learn from data; they identify patterns, make decisions, and generate predictions based on the information they're fed. Consequently, the quality of this training data is paramount. AI's Role in Improving Data Quality While the problem of data quality may seem daunting, there is hope.

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Data Quality Algorithm AI AI 130

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 268

Data Quality Metadata 268

Marktechpost

APRIL 1, 2024

Existing research emphasizes the significance of distributed processing and data quality control for enhancing LLMs. Utilizing frameworks like Slurm and Spark enables efficient big data management, while data quality improvements through deduplication, decontamination, and sentence length adjustments refine training datasets.

Large Language Models 94

Large Language Models ETL Data Ingestion Data Quality 94