datapine

SEPTEMBER 29, 2022

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

O'Reilly on Data

MARCH 18, 2020

The update sheds light on what AI adoption looks like in the enterprise— hint: deployments are shifting from prototype to production—the popularity of specific techniques and tools, the challenges experienced by adopters, and so on. By contrast, AI adopters are about one-third more likely to cite problems with missing or inconsistent data.

Enterprise 349

Enterprise Deep Learning Data Governance Risk 349

O'Reilly on Data

APRIL 19, 2021

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. The biggest problems in this year’s survey are lack of skilled people and difficulty in hiring (19%) and data quality (18%). Bad data yields bad results at scale.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

CIO Business Intelligence

OCTOBER 23, 2024

Here, CIO Patrick Piccininno provides a roadmap of his journey from data with no integration to meaningful dashboards, insights, and a data literate culture. You ’re building an enterprise data platform for the first time in Sevita’s history. Second, the manual spreadsheet work resulted in significant manual data entry.

Enterprise 119

Enterprise Dashboards KPI Data Lake 119

O'Reilly on Data

NOVEMBER 28, 2023

In enterprises, we’ve seen everything from wholesale adoption to policies that severely restrict or even forbid the use of generative AI. Few nonusers (2%) report that lack of data or data quality is an issue, and only 1.3% Developers are learning how to find quality data and build models that work.

Enterprise 342

Enterprise Testing Modeling Reporting 342

David Menninger's Analyst Perspectives

NOVEMBER 19, 2024

Maintaining quality and trust is a perennial data management challenge, the importance of which has come into sharper focus in recent years thanks to the rise of artificial intelligence (AI).  With the aim of rectifying that situation, Bigeye’s founders set out to build a business around data observability.

Data Quality 130

Data Quality Dashboards Data-driven Software 130

O'Reilly on Data

SEPTEMBER 24, 2018

If this dirty data proliferates and propagates to other systems, we open Pandora’s box of unintended consequences. The DataOps team needs to watch out for data issues and fix them before they get copied around. These data quality issues bring a new level of potential problems for real-time systems.

Enterprise 258

Enterprise Big Data Data Quality Unstructured Data 258

CIO Business Intelligence

NOVEMBER 4, 2024

research firm Vanson Bourne to survey 650 global IT, DevOps, and Platform Engineering decision-makers on their enterprise AI strategy. The Nutanix State of Enterprise AI Report highlights AI adoption, challenges, and the future of this transformative technology. AI applications rely heavily on secure data, models, and infrastructure.

Marketing 128

Marketing Data Quality Data Governance Digital Transformation 128

TDAN

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 Enterprise Metadata Data Strategy 114

O'Reilly on Data

JULY 15, 2019

Regulators behind SR 11-7 also emphasize the importance of data—specifically data quality , relevance , and documentation. While models garner the most press coverage, the reality is that data remains the main bottleneck in most ML projects. Gary Kazantsev on how “Data science makes an impact on Wall Street”.

Machine Learning 52

Machine Learning Management Enterprise Risk Management 52

CIO Business Intelligence

MARCH 25, 2025

Accenture reports that the top three sources of technical debt are enterprise applications, AI, and enterprise architecture. These areas are considerable issues, but what about data, security, culture, and addressing areas where past shortcuts are fast becoming todays liabilities?

Risk 123

Risk Cost-Benefit Data-driven Digital Transformation 123

CIO Business Intelligence

MARCH 13, 2024

But hearing those voices, and how to effectively respond, is dictated by the quality of data available, and understanding how to properly utilize it. “We We know in financial services and in a lot of verticals, we have a whole slew of data quality challenges,” he says. Traditionally, AI data quality has been a challenge.”

Data Quality 105

Data Quality Digital Transformation Enterprise Marketing 105

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. DBT (Data Build Tool) — A command-line tool that enables data analysts and engineers to transform data in their warehouse more effectively. DataOps is a hot topic in 2021.

Testing 300

Testing Machine Learning Consulting Data Science 300

CIO Business Intelligence

FEBRUARY 26, 2025

Agentic AI was the big breakthrough technology for gen AI last year, and this year, enterprises will deploy these systems at scale. According to a January KPMG survey of 100 senior executives at large enterprises, 12% of companies are already deploying AI agents, 37% are in pilot stages, and 51% are exploring their use.

IT 141

IT Enterprise Interactive Data Quality 141

CIO Business Intelligence

SEPTEMBER 17, 2024

CIOs often have a love-hate relationship with enterprise architecture. On the one hand, enterprise architects play a key role in selecting platforms, developing technical capabilities, and driving standards.

Enterprise 145

Enterprise Digital Transformation Cost-Benefit Risk 145

CIO Business Intelligence

DECEMBER 10, 2024

According to AI at Wartons report on navigating gen AIs early years, 72% of enterprises predict gen AI budget growth over the next 12 months but slower increases over the next two to five years. A second area is improving data quality and integrating systems for marketing departments, then tracking how these changes impact marketing metrics.

Sales 143

Sales Metrics Data-driven Unstructured Data 143

O'Reilly on Data

JUNE 18, 2019

A recent O’Reilly survey found that those with mature AI practices (as measured by how long they’ve had models in production) cited “Lack of data or data quality issues” as the main bottleneck holding back further adoption of AI technologies. The problem is even more magnified in the case of structured enterprise data.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

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. It takes days for data engineers to identify and implement data quality rules.

Data Quality 98

Data Quality Statistics Data Lake Visualization 98

AWS Big Data

OCTOBER 9, 2024

Some customers build custom in-house data parity frameworks to validate data during migration. Others use open source data quality products for data parity use cases. This takes away important person hours from the actual migration effort into building and maintaining a data parity framework.

Data Quality 111

Data Quality Data Lake Data Warehouse Metrics 111

AWS Big Data

DECEMBER 4, 2024

.” – Lee Slezak, SVP of Data and Analytic, Lennar Unified governance: Meet your enterprise security needs with built-in data and AI governance When it comes to data and AI governance, discipline equals freedom. Having confidence in your data is key. The tools to transform your business are here.

Data Analytics 101

Data Analytics Analytics Data Lake Data Quality 101

Octopai

JULY 11, 2022

And when business users don’t complain, but you know the data isn’t good enough to make these types of calls wisely, that’s an even bigger problem. How are you, as a data quality evangelist (if you’re reading this post, that must describe you at least somewhat, right?), Tie data quality directly to business objectives.

Data Quality 98

Data Quality Strategy Business Objectives Sales 98

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

Data Quality 111

Data Quality Data Governance Data Lake Testing 111

Smarten

NOVEMBER 26, 2024

Today, organizations look to data and to technology to help them understand historical results, and predict the future needs of the enterprise to manage everything from suppliers and supplies to new locations, new products and services, hiring, training and investments. But too much data can also create issues.

Data Quality 64

Data Quality Machine Learning Predictive Modeling Metadata 64

Alation

JANUARY 20, 2022

Several weeks ago (prior to the Omicron wave), I got to attend my first conference in roughly two years: Dataversity’s Data Quality and Information Quality Conference. Ryan Doupe, Chief Data Officer of American Fidelity, held a thought-provoking session that resonated with me. Step 2: Data Definitions.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

IBM Big Data Hub

MAY 9, 2023

We can use foundation models to quickly perform tasks with limited annotated data and minimal effort; in some cases, we need only to describe the task at hand to coax the model into solving it. But these powerful technologies also introduce new risks and challenges for enterprises.

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

CIO Business Intelligence

AUGUST 14, 2024

Between building gen AI features into almost every enterprise tool it offers, adding the most popular gen AI developer tool to GitHub — GitHub Copilot is already bigger than GitHub when Microsoft bought it — and running the cloud powering OpenAI, Microsoft has taken a commanding lead in enterprise gen AI.

Enterprise 136

Enterprise Cost-Benefit Experimentation Modeling 136

DataKitchen

JANUARY 25, 2022

There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex. Ensuring that data is available, secure, correct, and fit for purpose is neither simple nor cheap.

Consulting 244

Consulting Testing Data Lake Data Quality 244

CIO Business Intelligence

APRIL 4, 2024

Some prospective projects require custom development using large language models (LLMs), but others simply require flipping a switch to turn on new AI capabilities in enterprise software. “AI You need to understand what data sits where, how it’s linked to something else, what the quality is, the lineage, and where else it’s being used.”

Enterprise 134

Enterprise Cost-Benefit Forecasting Sales 134

CIO Business Intelligence

APRIL 11, 2024

In a cloud market dominated by three vendors, once cloud-denier Oracle is making a push for enterprise share gains, announcing expanded offerings and customer wins across the globe, including Japan , Mexico , and the Middle East. Oracle is helped by the fact that it has two offerings for enterprise applications, says Thompson.

Enterprise 124

Enterprise IT Data Processing Strategy 124

Cloudera

MARCH 3, 2022

Whether the enterprise uses dozens or hundreds of data sources for multi-function analytics, all organizations can run into data governance issues. Bad data governance practices lead to data breaches, lawsuits, and regulatory fines — and no enterprise is immune. . Everyone Fails Data Governance.

Data Governance 100

Data Governance Enterprise Data Quality Metadata 100

Smarten

APRIL 25, 2024

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics? There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data.

Data Quality 64

Data Quality Analytics Machine Learning Visualization 64

CIO Business Intelligence

MAY 3, 2022

Last year, Dow took a bold step to make better use of its data. With a goal of eliminating isolated islands of data and making better use of business intelligence as an enterprise asset, the company launched an internal organization that seamlessly integrated IT and the company’s global business units under one umbrella.

Data Quality 96

Data Quality Machine Learning Business Objectives Business Intelligence 96

O'Reilly on Data

NOVEMBER 19, 2024

A generalized, unbundled workflow A more accountable approach to GraphRAG is to unbundle the process of knowledge graph construction, paying special attention to data quality. Link the extracted entities to their respective text chunks.

Unstructured Data 318

Unstructured Data Structured Data Statistics Modeling 318

Octopai

JUNE 30, 2022

Establishing a single, enterprise-wide source of truth? Increasing data quality and accuracy? Why are data catalog use cases so downright… predictable? Here are three ways enterprises can leverage their data catalogs that don’t make the standard lists. The data catalog as an HR tool? Yeah, yeah.

Enterprise 96

Enterprise Data-driven Data Quality Data Lake 96

Cloudera

NOVEMBER 13, 2024

We are excited to announce the acquisition of Octopai , a leading data lineage and catalog platform that provides data discovery and governance for enterprises to enhance their data-driven decision making. This guarantees data quality and automates the laborious, manual processes required to maintain data reliability.

Metadata 90

Metadata Management Data Governance Data-driven 90

CIO Business Intelligence

NOVEMBER 13, 2024

There’s already more low-quality AI content flooding search results, and this can hurt employees looking for information both on the public web and in enterprise knowledge repositories. According to ZipRecruiter, the average starting salary for an entry-level US data scientist in October was $165,000 per year.

IT 141

IT Consulting ROI Cost-Benefit 141