DataKitchen

JULY 22, 2025

But this isn’t just buzzword engineering; this represents how we learned to stop breaking things constantly and started working faster with less risk, fear, and late-night heroics. What is FITT Data Architecture? This approach creates what we refer to as a “copy-paste” data architecture.

Data Architecture 164

Data Architecture Testing Data Quality Cost-Benefit 164

BI-Survey

JULY 10, 2025

At their presentation at this year’s DATA festival in Munich, the team of the Global Legal Entity Identifier Foundation (GLEIF) turned the conversation around. GLEIF takes pride in the quality of this data, even though it’s openly available. Setting the Scene: Who Is GLEIF and What Is a LEI?

Data Quality 52

Data Quality Data-driven Modeling Visualization 52

CIO Business Intelligence

APRIL 8, 2025

Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality. Fragmented systems, inconsistent definitions, legacy infrastructure and manual workarounds introduce critical risks.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

Jen Stirrup

JULY 12, 2025

According to the MIT Technology Review's 2024 Data Integration Survey, organizations with highly fragmented data environments spend up to 67% of their data scientists' time on data collection and preparation rather than on developing and refining AI models. million annually.

Enterprise 89

Enterprise Data Quality Data Governance Business Objectives 89

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. But adoption isn’t always straightforward.

Enterprise 141

Enterprise Data Architecture Unstructured Data Insurance 141

DataKitchen

MARCH 20, 2025

We’ve identified two distinct types of data teams: process-centric and data-centric. Understanding this framework offers valuable insights into team efficiency, operational excellence, and data quality. Process-centric data teams focus their energies predominantly on orchestrating and automating workflows.

Data Quality 164

Data Quality Testing Metrics Management 164

AWS Big Data

DECEMBER 4, 2024

Data teams struggle to find a unified approach that enables effortless discovery, understanding, and assurance of data quality and security across various sources. SageMaker simplifies the discovery, governance, and collaboration for data and AI across your lakehouse, AI models, and applications.

Data Analytics 103

Data Analytics Analytics Data Lake Data Quality 103

CIO Business Intelligence

MARCH 25, 2025

CIOs perennially deal with technical debts risks, costs, and complexities. While the impacts of legacy systems can be quantified, technical debt is also often embedded in subtler ways across the IT ecosystem, making it hard to account for the full list of issues and risks.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

DataKitchen

JULY 8, 2025

The Dual Challenge of Production and Development Testing Test coverage in data and analytics operates across two distinct but interconnected dimensions: production testing and development testing. Production test coverage ensures that data quality remains high and error rates remain low throughout the value pipeline during live operations.

Testing 100

Testing Data Quality Cost-Benefit Manufacturing 100

CIO Business Intelligence

JANUARY 7, 2025

Regardless of the driver of transformation, your companys culture, leadership, and operating practices must continuously improve to meet the demands of a globally competitive, faster-paced, and technology-enabled world with increasing security and other operational risks.

Digital Transformation 143

Digital Transformation Experimentation Cost-Benefit Strategy 143

CIO Business Intelligence

NOVEMBER 18, 2024

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. By partnering with industry leaders, businesses can acquire the resources needed for efficient data discovery, multi-environment management, and strong data protection.

Data-driven 112

Data-driven Machine Learning ROI Uncertainty 112

David Menninger's Analyst Perspectives

MAY 14, 2025

Data governance is integral to an overall data intelligence strategy. Good data governance provides guardrails that enable enterprises to act fast while protecting the business from risks related to regulatory requirements, data-quality issues and data-reliability concerns.

Data Governance 147

Data Governance Data Quality Data-driven Metadata 147

DataKitchen

MAY 17, 2025

The refresh was long past its deadline, the projects key data engineer was on vacation, and I was playing backup. At the moment, I was flying home from a data quality conference. And when we explained what happenedwhy the data was late and what we had caughtthey werent frustrated. No dashboard updates. Where was I?

Data Quality 118

Data Quality Testing Data Warehouse Dashboards 118

CIO Business Intelligence

DECEMBER 11, 2024

The field of data observability has experienced substantial growth recently, offering numerous commercial tools on the market or the option to build a DIY solution using open-source components. This issue will be exacerbated by the future use of AI agents making decisions on behalf of companies based on data.

Management 111

Management Data Governance Data Science Reporting 111

CIO Business Intelligence

DECEMBER 19, 2024

Key considerations for enterprise decision-makers My recommendations for enterprises and key decision-makers are to consider the following: Data consolidation and governance: Prioritize platforms that can effectively integrate data from diverse sources, ensuring data consistency and accuracy.

Sales 122

Sales Analytics Key Performance Indicator Prescriptive Analytics 122

CIO Business Intelligence

DECEMBER 10, 2024

Align data strategies to unlock gen AI value for marketing initiatives Using AI to improve sales metrics is a good starting point for ensuring productivity improvements have near-term financial impact. When considering the breadth of martech available today, data is key to modern marketing, says Michelle Suzuki, CMO of Glassbox.

Sales 143

Sales Metrics Data-driven Unstructured Data 143

CIO Business Intelligence

NOVEMBER 11, 2024

In today’s fast-paced digital environment, enterprises increasingly leverage AI and analytics to strengthen their risk management strategies. By adopting AI-driven approaches, businesses can better anticipate potential threats, make data-informed decisions, and bolster the security of their assets and operations.

Risk Management 59

Risk Management Risk Management Data-driven 59

DataFloq

JULY 15, 2025

By the end of 2025, the global data size is expected to grow to 181 zettabytes, with 80% of this data being unstructured or semi-structured, making traditional, column-aligned anonymization obsolete. Anonymizing a few columns in such a manner puts the entire landscape at risk.

Data Governance 96

Data Governance Unstructured Data Risk Testing 96

CIO Business Intelligence

JANUARY 9, 2025

Without data that is accurate, comprehensive, and adaptable to every customers intent, businesses risk being left behind. Perhaps most concerning is the increased compliance risk that stems from inconsistent product information. The platform offers tailored solutions for different market segments.

B2B 105

B2B Cost-Benefit Data-driven Sales 105

Timo Elliott

DECEMBER 10, 2024

This dedication extends to their internal operations, where poor data quality was identified as a significant potential risk to product quality, and hence their brand reputation. Impact of Errors : Erroneous data posed immediate risks to operations and long-term damage to customer trust.

Management 52

Management Data Governance Consulting Cost-Benefit 52

CIO Business Intelligence

NOVEMBER 5, 2024

The key is good data quality. New and changing regulations: Governments continue to add environmental sustainability regulations, and organizations must adapt in ways that enable them to comply. have their own additional regulations. Businesses have no choice but to adapt to these new regulations.

Uncertainty 98

Uncertainty Measurement ROI Reporting 98

David Menninger's Analyst Perspectives

MAY 21, 2025

The root cause of the problem came down to data quality. But it is also a risk, because a brilliant recommendation stranded in a dashboard or report is doomed. Forecast accuracy improved a little, but individual win rates did not change much. These AI layers can sit on top of the CRM rather than inside it.

Sales 148

Sales Measurement Data-driven Dashboards 148

CIO Business Intelligence

DECEMBER 17, 2024

To evaluate feasibility, ask: Do we have internal data and skills to support this? What are the associated risks and costs, including operational, reputational, and competitive? Prioritize data quality and security. Work with expert partners Many organizations struggle to ensure successful AI and genAI implementations.

Experimentation 98

Experimentation ROI Data Quality Risk 98

CIO Business Intelligence

NOVEMBER 13, 2024

And we’re at risk of being burned out.” If there are tools that are vetted, safe, and don’t pose security risks, and I can play around with them at my discretion, and if it helps me do my job better — great,” Woolley says. But there’s only so many projects we can meaningfully contribute to, and conversations we can be part of.”

IT 141

IT Consulting ROI Cost-Benefit 141

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 127

Enterprise Cost-Benefit Unstructured Data Data Quality 127

CIO Business Intelligence

DECEMBER 8, 2024

However, with the rise of digital tools, ensuring data security is becoming more crucial than ever. Thats why data quality is crucial. The logic behind AI can be refined, but incorrect data will lead to wrong outcomes, which in healthcare can be critical. Its all about human lives.

Digital Transformation 69

Digital Transformation Data-driven Technology Machine Learning 69

DataFloq

JUNE 24, 2025

The Limits of Real-World Data Using actual customer data in compliance testing environments comes with obvious risks , privacy violations, regulatory scrutiny, audit red flags, and restricted access due to GDPR or internal policies. Risk scoring models often rely on static, backward-looking data.

Testing 70

Testing Data Quality Risk Data-driven 70

CIO Business Intelligence

FEBRUARY 26, 2025

If they want to make certain decisions faster, we will build agents in line with their risk tolerance. D&B is not alone in worrying about the risks of AI agents. Starting with small, discrete use cases helps reduce the risks, says Roger Haney, CDWs chief architect. Ours is totally automated. Thats where were seeing success.

IT 142

IT Enterprise Interactive Data Quality 142

erwin

DECEMBER 9, 2024

And do you have the transparency and data observability built into your data strategy to adequately support the AI teams building them? Will the new creative, diverse and scalable data pipelines you are building also incorporate the AI governance guardrails needed to manage and limit your organizational risk?

Metadata 52

Metadata Data Quality Sales Modeling 52

Cloudera

NOVEMBER 13, 2024

This guarantees data quality and automates the laborious, manual processes required to maintain data reliability. Robust Data Catalog: Organizations can create company-wide consistency with a self-creating, self-updating data catalog.

Metadata 90

Metadata Management Data Governance Data-driven 90

DataKitchen

FEBRUARY 17, 2025

No Python, No SQL Templates, No YAML: Why Your Open Source Data Quality Tool Should Generate 80% Of Your Data Quality Tests Automatically As a data engineer, ensuring data quality is both essential and overwhelming. But theres a growing problemdata quality testing is becoming an unsustainable burden.

Data Quality 187

Data Quality Testing Scorecard Data-driven 187

CIO Business Intelligence

MAY 21, 2025

Sufficiently accessible and accurate tools could deliver operational improvements and revenue, as well as optimized costs and reduced risks in many areas of business decision making. Patterns of language use, topics of interest, or just the user profile can be enough to risk re-identifying individual.

Statistics 112

Statistics Testing Modeling Risk 112

CIO Business Intelligence

NOVEMBER 19, 2024

They are often unable to handle large, diverse data sets from multiple sources. Another issue is ensuring data quality through cleansing processes to remove errors and standardize formats. Staffing teams with skilled data scientists and AI specialists is difficult, given the severe global shortage of talent.

Analytics 101

Analytics Cost-Benefit Finance Data-driven 101

CIO Business Intelligence

OCTOBER 16, 2024

Edge computing can reduce latency, lower cost, and lower data exposure risks.” By leveraging AI and edge computing, we could effectively de-risk some complex operational decisions by establishing machine decisions with clear and predictable boundaries.” One key benefit is bringing reliability to the edge.

Cost-Benefit 143

Cost-Benefit Manufacturing Data-driven Optimization 143

CIO Business Intelligence

OCTOBER 29, 2024

Data is the engine that powers the corporate decisions we make; from the personalized customer experiences we create to the internal processes we activate and the AI-powered breakthroughs we innovate. Reliance on this invaluable currency brings substantial risks that could severely impact an enterprise.

Enterprise 134

Enterprise Broadcasting Risk Sales 134

DataFloq

JULY 21, 2025

Through an immersive case study focused on enhancing donor engagement, we reveal how even small organisations can harness DataOps to fuel agility, trust, and data-driven impact. As the digital world rapidly changes, data is increasingly being viewed both as an important asset and a potential risk. Introduction: Why DataOps Now?

Analytics 70

Analytics Data-driven Cost-Benefit Data Quality 70

CIO Business Intelligence

JANUARY 30, 2025

These changes can expose businesses to risks and vulnerabilities such as security breaches, data privacy issues and harm to the companys reputation. It also includes managing the risks, quality and accountability of AI systems and their outcomes. Organizations need to have a data governance policy in place.

Testing 93

Testing Metrics Cost-Benefit Modeling 93