Precisely

NOVEMBER 5, 2024

Key Takeaways: Data quality is the top challenge impacting data integrity – cited as such by 64% of organizations. Data trust is impacted by data quality issues, with 67% of organizations saying they don’t completely trust their data used for decision-making.

Data Quality 59

Data Quality Analytics Analytics Data Governance 59

Dataconomy

JUNE 25, 2025

Data warehousing: Understanding the complexities of enterprise strategy enhances effectiveness. Importance of data stewardship Data stewardship is vital for ensuring data quality and reliability, which directly impacts business operations and strategies.

Data Governance 91

Data Governance Data Analyst Data Quality Data Scientist 91

ODSC - Open Data Science

NOVEMBER 29, 2024

Artificial Intelligence (AI) stands at the forefront of transforming data governance strategies, offering innovative solutions that enhance data integrity and security. In this post, let’s understand the growing role of AI in data governance, making it more dynamic, efficient, and secure.

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Data Governance Predictive Analytics AI AI 40

Dataconomy

JUNE 11, 2025

Data catalogs play a pivotal role in modern data management strategies, acting as comprehensive inventories that enhance an organization’s ability to discover and utilize data assets. By providing a centralized view of metadata, data catalogs facilitate better analytics, data governance, and decision-making processes.

Data Governance 91

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Dataversity

DECEMBER 17, 2024

AI solutions have moved from experimental to mainstream, with all the major tech companies and cloud providers making significant investments in […] The post What to Expect in AI Data Governance: 2025 Predictions appeared first on DATAVERSITY.

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Dataversity

DECEMBER 26, 2024

At the heart of this transformation lies data a critical asset that, when managed effectively, can drive innovation, enhance customer experiences, and open […] The post Corporate Data Governance: The Cornerstone of Successful Digital Transformation appeared first on DATAVERSITY.

Data Governance 105

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Dataconomy

JUNE 3, 2025

By understanding their rights and responsibilities, they contribute significantly to an organizations data landscape. This article explores the facets of data citizenship, from data governance policies to ethical dilemmas. What is a data citizen? Organizations must implement robust compliance strategies.

Data Governance 91

Data Governance Business Intelligence Business Intelligence Data Quality 91

Precisely

DECEMBER 9, 2024

Key Takeaways: Interest in data governance is on the rise 71% of organizations report that their organization has a data governance program, compared to 60% in 2023. Data governance is a top data integrity challenge, cited by 54% of organizations second only to data quality (56%).

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Precisely

JANUARY 9, 2025

Each source system had their own proprietary rules and standards around data capture and maintenance, so when trying to bring different versions of similar data together such as customer, address, product, or financial data, for example there was no clear way to reconcile these discrepancies. A data lake!

Data Warehouse 119

Data Warehouse Hadoop Data Lakes Data Governance 119

Dataconomy

JULY 7, 2025

Usability and functionality enhancements To improve usability, organizations implement organized folder structures and searchable data catalogs. Data profiling tools further aid in quality assurance and establish data governance mechanisms. Organizations must implement governance mechanisms to address these issues.

Data Lakes 91

Data Lakes Data Warehouse Hadoop Analytics 91

Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Plan for data quality and governance of AI models from day one.

Analytics 72

Analytics Analytics Data Governance Data Quality 72

Dataconomy

JUNE 23, 2025

DataOps is transforming the way organizations handle and utilize data in today’s fast-paced digital landscape. By integrating Agile methodologies into data practices, DataOps enhances collaboration among cross-functional teams, leading to improved data quality and speed in delivering insights.

DataOps 91

DataOps Data Pipeline Data Quality Data Science 91

Dataversity

MARCH 17, 2025

The amount of data we deal with has increased rapidly (close to 50TB, even for a small company), whereas75% of leaders dont trust their datafor business decision-making.Though these are two different stats, the common denominator playing a role could be data quality.With new data flowing from almost every direction, there must be a yardstick or […] (..)

Data Quality 59

Data Quality Data Governance 59

Precisely

NOVEMBER 18, 2024

Key Takeaways: Data integrity is required for AI initiatives, better decision-making, and more – but data trust is on the decline. Data quality and data governance are the top data integrity challenges, and priorities. Plan for data quality and governance of AI models from day one.

Analytics 59

Analytics Analytics Data Governance Data Quality 59

IBM Data Science in Practice

JANUARY 2, 2025

This step allows users to analyze data quality, create metadata enrichment (MDE), or define data quality rules for thesubset. Running profiling on Microsegment Explanation: Profiling ensures the microsegment aligns with analytical or governance objectives, providing actionable insights for further processing.

SQL 100

SQL Data Quality Data Profiling Data Preparation 100

Dataconomy

JUNE 18, 2025

Managing data volumes Organizations face challenges with increasing data volumes and the complexities of managing diverse data platforms, necessitating robust integration strategies. Data quality issues Inconsistent data can lead to quality issues.

Data Warehouse 91

Data Warehouse Data Silos ETL Big Data 91

Dataversity

APRIL 29, 2025

Yet, many organizations still apply a one-size-fits-all approach to data governance frameworks, using the same rules for every department, use case, and dataset.

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Data Governance AI AI Data Quality 59

Precisely

JANUARY 27, 2025

When you consider that 60% of organizations in our survey say that AI is a key influence on their data programs (up 46% from our 2023 survey), its clear that strategic investments must be made to ensure their data is ready to fuel AIs fullest potential. What are the primary data challenges blocking the path to AI success?

Data Quality 59

Data Quality Data Governance Analytics Analytics 59

Dataversity

DECEMBER 18, 2024

Issues like intellectual property rights, bias, privacy, and liability are central concerns that […] The post AI Technologies and the Data Governance Framework: Navigating Legal Implications appeared first on DATAVERSITY.

Data Governance 59

Data Governance Artificial Intelligence Artificial Intelligence AI 59

Dataversity

APRIL 7, 2025

In Aprils Book of the Month, were looking at Bob Seiners Non-Invasive Data Governance Unleashed: Empowering People to Govern Data and AI.This is Seiners third book on non-invasive data governance (NIDG) and acts as a companion piece to the original.

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Data Governance Data Quality 52

Dataconomy

JUNE 10, 2025

Data collection Gathering data from diverse sources is essential, ensuring integration from various platforms to get a comprehensive view. Data quality assurance Implementing profiling and cleansing methods preserves data accuracy, ensuring that the insights drawn are reliable.

Analytics 91

Analytics Analytics Big Data Analytics Big Data Analytics 91

Dataconomy

DECEMBER 17, 2024

Define data needs : Specify datasets, attributes, granularity, and update frequency. Address data governance : Ensure requirements include compliance with regulations like GDPR or CCPA. Key questions to ask: What data sources are required? Are there any data gaps that need to be filled?

Data Quality 91

Data Quality Power BI Data Engineering Data Engineering 91

Dataconomy

MARCH 17, 2025

Key features of augmented analytics A variety of features distinguish augmented analytics from traditional data analytics models. Smart data preparation Automated data cleaning is a crucial part of augmented analytics. It involves processes that improve data quality, such as removing duplicates and addressing inconsistencies.

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The Data Administration Newsletter

JULY 2, 2025

Let’s face it — data governance has never been just about ownership and stewardship. As Jonathan Reichental notes in “Data Governance for Dummies,” it touches everything from metadata and architecture to integration, privacy, and BI.

Data Governance 52

Data Governance Data Quality Business Intelligence Business Intelligence 52

Precisely

APRIL 24, 2025

Can our teams confidently find and access data without needing IT intervention ? The problem: Lack of data ownership and accountability Without clear ownership, data quality and compliance suffer. Are our compliance tasks integrated into our day-to-day governance activities ? Feel familiar?

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Data Governance Data Quality Analytics Analytics 64

The Data Administration Newsletter

JUNE 4, 2025

Data governance has long been the backbone of responsible data management, ensuring that organizations maintain high standards in data quality, security, and compliance. According to Jonathan Reichental in Data Governance for Dummies, the scope of governance extends well beyond data ownership and stewardship.

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Data Governance Data Quality AI AI 52

Dataversity

JANUARY 30, 2025

In the next decade, companies that capitalize on revenue data will outpace competitors, making it the single most critical asset for driving growth, agility, and market leadership.

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Data Governance Data Quality 52

AWS Machine Learning Blog

NOVEMBER 13, 2024

Unified model governance architecture ML governance enforces the ethical, legal, and efficient use of ML systems by addressing concerns like bias, transparency, explainability, and accountability. Prepare the data to build your model training pipeline.

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Dataversity

NOVEMBER 25, 2024

The emergence of artificial intelligence (AI) brings data governance into sharp focus because grounding large language models (LLMs) with secure, trusted data is the only way to ensure accurate responses. So, what exactly is AI data governance?

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Data Governance Artificial Intelligence Artificial Intelligence AI 52

Pickl AI

JANUARY 12, 2025

However, there are also challenges that businesses must address to maximise the various benefits of data-driven and AI-driven approaches. Data quality : Both approaches’ success depends on the data’s accuracy and completeness. How do We Integrate Data-driven and AI-driven Models?

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Dataconomy

JUNE 16, 2025

Data mapping complexity Developing robust mapping strategies for the new database organization is necessary to ensure data integrity and usability. Governance issues Implementing a data governance plan is essential for maintaining data quality throughout the migration process.

Database 91

Database AWS Data Governance Data Quality 91

AWS Machine Learning Blog

APRIL 3, 2025

Data governance challenges Maintaining consistent data governance across different systems is crucial but complex. The company aims to integrate additional data sources, including other mission-critical systems, into ODAP. The following diagram shows a basic layout of how the solution works.

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AWS Data Governance Data Silos SQL 89

Dataconomy

JUNE 11, 2025

Benefits of data dignity Data dignity offers several benefits that can enhance the relationship between users and companies regarding data usage. Greater data control: Users would retain ownership and determine how their data is used.

Data Governance 91

Data Governance Data Quality AI AI 91

Dataversity

JUNE 5, 2025

We are at the threshold of the most significant changes in information management, data governance, and analytics since the inventions of the relational database and SQL. At the core, though, little has changed.The basic […] The post Mind the Gap: AI-Driven Data and Analytics Disruption appeared first on DATAVERSITY.

Analytics 96

Analytics Analytics Data Governance SQL 96

Dataversity

DECEMBER 2, 2024

In the AI era, organizations are eager to harness innovation and create value through high-quality, relevant data. Gartner, however, projects that 80% of data governance initiatives will fail by 2027. This statistic underscores the urgent need for robust data platforms and governance frameworks.

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Data Governance AI AI Data Quality 52

Precisely

JUNE 19, 2025

I shared exciting news about the latest advancements in our Precisely Data Integrity Suite – innovations designed to help businesses like yours accelerate AI, enhance analytics , and scale your overall data-driven transformation. They’ve seen firsthand how critical data governance and quality are to driving outcomes.

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AI AI Data Governance Analytics 72

AWS Machine Learning Blog

NOVEMBER 7, 2024

Here you also have the data sources, processing pipelines, vector stores, and data governance mechanisms that allow tenants to securely discover, access, andthe data they need for their specific use case. At this point, you need to consider the use case and data isolation requirements.

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