Analytics Vidhya

SEPTEMBER 23, 2024

Introduction Ensuring data quality is paramount for businesses relying on data-driven decision-making. As data volumes grow and sources diversify, manual quality checks become increasingly impractical and error-prone.

Data Quality 271

Data Quality Data-driven Data Integration Analytics 271

O'Reilly on Data

DECEMBER 12, 2019

For all the excitement about machine learning (ML), there are serious impediments to its widespread adoption. Residual plots place input data and predictions into a two-dimensional visualization where influential outliers, data-quality problems, and other types of bugs often become plainly visible.

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Machine Learning Modeling Testing Risk Management 276

O'Reilly on Data

JULY 15, 2019

As companies use machine learning (ML) and AI technologies across a broader suite of products and services, it’s clear that new tools, best practices, and new organizational structures will be needed. Machine learning developers are beginning to look at an even broader set of risk factors. Sources of model risk.

Machine Learning 52

Machine Learning Management Enterprise Risk Management 52

DataKitchen

SEPTEMBER 18, 2024

A DataOps Approach to Data Quality The Growing Complexity of Data Quality Data quality issues are widespread, affecting organizations across industries, from manufacturing to healthcare and financial services. 73% of data practitioners do not trust their data (IDC).

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Scorecard Data Quality Measurement Testing 177

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

To improve data reliability, enterprises were largely dependent on data-quality tools that required manual effort by data engineers, data architects, data scientists and data analysts.  With the aim of rectifying that situation, Bigeye’s founders set out to build a business around data observability.

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CIO Business Intelligence

DECEMBER 12, 2024

Confidence from business leaders is often focused on the AI models or algorithms, Erolin adds, not the messy groundwork like data quality, integration, or even legacy systems. Data quality is a problem that is going to limit the usefulness of AI technologies for the foreseeable future, Brown adds.

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IT Data Quality Experimentation Machine Learning 134

KDnuggets

MARCH 10, 2022

Good quality data becomes imperative and a basic building block of an ML pipeline. The ML model can only be as good as its training data.

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Machine Learning Data Quality Modeling IT 158

CIO Business Intelligence

NOVEMBER 18, 2024

In the quest to reach the full potential of artificial intelligence (AI) and machine learning (ML), there’s no substitute for readily accessible, high-quality data. If the data volume is insufficient, it’s impossible to build robust ML algorithms. If the data quality is poor, the generated outcomes will be useless.

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CIO Business Intelligence

APRIL 8, 2025

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

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Data Quality Data-driven Key Performance Indicator Metadata 102

TDAN

APRIL 5, 2022

Regardless of how accurate a data system is, it yields poor results if the quality of data is bad. As part of their data strategy, a number of companies have begun to deploy machine learning solutions.

Machine Learning 98

Machine Learning Data Quality Data Strategy Strategy 98

O'Reilly on Data

MARCH 24, 2020

If you’re basing business decisions on dashboards or the results of online experiments, you need to have the right data. On the machine learning side, we are entering what Andrei Karpathy, director of AI at Tesla, dubs the Software 2.0 Data professionals spend an inordinate amount on time cleaning, repairing, and preparing data.

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Machine Learning Statistics Data Quality Data Collection 364

DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

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Testing Machine Learning Consulting Data Science 300

CIO Business Intelligence

NOVEMBER 27, 2024

Once the province of the data warehouse team, data management has increasingly become a C-suite priority, with data quality seen as key for both customer experience and business performance. But along with siloed data and compliance concerns , poor data quality is holding back enterprise AI projects.

Enterprise 141

Enterprise Data Quality Structured Data Modeling 141

O'Reilly on Data

JUNE 18, 2019

Machine learning solutions for data integration, cleaning, and data generation are beginning to emerge. “AI AI starts with ‘good’ data” is a statement that receives wide agreement from data scientists, analysts, and business owners. Data integration and cleaning. Data unification and integration.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

AWS Big Data

AUGUST 8, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules commonly assess the data based on fixed criteria reflecting the current business state. In this post, we demonstrate how this feature works with an example.

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Data Quality Statistics Visualization Metrics 112

CIO Business Intelligence

JUNE 2, 2022

Recent notable research from the University of Cambridge, enabled by energy efficient HPC, includes a study on transformational machine learning (TML) and another on a robotic approach to reproducing research results. . Teaching Machines to ‘Learn How to Learn’. Just starting out with analytics?

Machine Learning 142

Machine Learning Deep Learning Data Quality Strategy 142

datapine

NOVEMBER 27, 2019

Companies are no longer wondering if data visualizations improve analyses but what is the best way to tell each data-story. 2020 will be the year of data quality management and data discovery: clean and secure data combined with a simple and powerful presentation. 1) Data Quality Management (DQM).

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Dataiku

APRIL 19, 2021

Data needs to be valuable, thus of high quality , to drive machine learning model success.

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Data Quality Machine Learning Modeling Management 105

Smart Data Collective

SEPTEMBER 29, 2022

You get the structured information in a machine-readable format, such as JSON. These three steps are performed by OCR in about 3 to 5 seconds observing an ever higher accuracy thanks to machine learning and artificial intelligence than manual extraction. Automated data capture improves your document management and processing.

Data-driven 145

Data-driven Data Quality Optimization Insurance 145

Smart Data Collective

JUNE 22, 2023

Taking the world by storm, artificial intelligence and machine learning software are changing the landscape in many fields. Earlier today, one analysis found that the market size for deep learning was worth $51 billion in 2022 and it will grow to be worth $1.7 Amazon has a very good overview if you want to learn more.

Machine Learning 111

Machine Learning Deep Learning Data Quality Modeling 111

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. Machine learning adds uncertainty.

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Management Machine Learning Experimentation Metrics 363

DataRobot Blog

JULY 21, 2022

Download the Machine Learning Project Checklist. Planning Machine Learning Projects. Machine learning and AI empower organizations to analyze data, discover insights, and drive decision making from troves of data. More organizations are investing in machine learning than ever before.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Why aren’t traditional software tools sufficient?

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Modeling Machine Learning Testing Metrics 257

Smarten

NOVEMBER 26, 2024

If the data is not easily gathered, managed and analyzed, it can overwhelm and complicate decision-makers. Data insight techniques provide a comprehensive set of tools, data analysis and quality assurance features to allow users to identify errors, enhance data quality, and boost productivity.’

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Machine Learning Data Quality Predictive Modeling Metadata 64

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning.

Data Quality 97

Data Quality Statistics Data Lake Visualization 97

CIO Business Intelligence

OCTOBER 30, 2024

AI’s ability to automate repetitive tasks leads to significant time savings on processes related to content creation, data analysis, and customer experience, freeing employees to work on more complex, creative issues. And the results for those who embrace a modern data architecture speak for themselves.

Enterprise 139

Enterprise Data Architecture Unstructured Data Insurance 139

CIO Business Intelligence

JANUARY 5, 2025

Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1] Reliability and security is paramount.

Enterprise 124

Enterprise Cost-Benefit Unstructured Data Data Quality 124

Dataiku

AUGUST 10, 2021

Using machine learning (ML) to predict customer growth, churn, and to find insights in the data is not only a trendy topic, but also something that can bring a lot of value.

Data Quality 105

Data Quality Machine Learning Modeling Management 105

CIO Business Intelligence

AUGUST 2, 2022

Data analytics and business intelligence are critical to every business, but especially important in the energy industry, as information is channeled from consumers and commercial clients related to usage that feeds into AES’ sustainability and services planning. The second is the data quality in our legacy systems. That’s one.

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Data Quality Digital Transformation Machine Learning Predictive Analytics 97

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

AWS Big Data

DECEMBER 4, 2024

Our customers are telling us that they are seeing their analytics and AI workloads increasingly converge around a lot of the same data, and this is changing how they are using analytics tools with their data. Having confidence in your data is key. They aren’t using analytics and AI tools in isolation.

Data Analytics 85

Data Analytics Analytics Data Lake Data Quality 85

AWS Big Data

MAY 23, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules assess the data based on fixed criteria reflecting current business states. We are excited to talk about how to use dynamic rules , a new capability of AWS Glue Data Quality.

Data Quality 100

Data Quality Metrics Data Lake Sales 100

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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Data Quality Modeling Analytics IT 319

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend is a data integration and management software company that offers applications for cloud computing, big data integration, application integration, data quality and master data management.

Management 324

Management Data Warehouse Data Quality Data Integration 324

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”. objective functions, major changes to hyperparameters, etc.)

Management 308

Management Machine Learning Metrics Modeling 308

CIO Business Intelligence

NOVEMBER 4, 2024

Data security, data quality, and data governance still raise warning bells Data security remains a top concern. Respondents rank data security as the top concern for AI workloads, followed closely by data quality. AI applications rely heavily on secure data, models, and infrastructure.

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Marketing Data Quality Data Governance Strategy 128

AWS Big Data

JANUARY 15, 2025

The following requirements were essential to decide for adopting a modern data mesh architecture: Domain-oriented ownership and data-as-a-product : EUROGATE aims to: Enable scalable and straightforward data sharing across organizational boundaries. Eliminate centralized bottlenecks and complex data pipelines.

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