Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

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Precisely

JANUARY 27, 2025

In 2025, its more important than ever to make data-driven decisions, cut costs, and improve efficiency especially in the face of major challenges due to higher manufacturing costs, disruptive new technologies like artificial intelligence (AI), and tougher global competition. In fact, its second only to data quality.

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IBM Journey to AI blog

MAY 9, 2024

The healthcare industry faces arguably the highest stakes when it comes to data governance. For starters, healthcare organizations constantly encounter vast (and ever-increasing) amounts of highly regulated personal data. healthcare, managing the accuracy, quality and integrity of data is the focus of data governance.

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Dataversity

APRIL 18, 2022

Since the data from such processes is growing, data controls may not be strong enough to ensure the data is qualitative. That’s where Data Quality dimensions come into play. […]. The post Data Quality Dimensions Are Crucial for AI appeared first on DATAVERSITY.

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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.

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Dataversity

MAY 8, 2023

As I’ve been working to challenge the status quo on Data Governance – I get a lot of questions about how it will “really” work. In 2019, I wrote the book “Disrupting Data Governance” because I firmly believe […] The post Dear Laura: How Will AI Impact Data Governance? appeared first on DATAVERSITY.

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IBM Journey to AI blog

SEPTEMBER 5, 2024

The best way to build a strong foundation for data success is through effective data governance. Access to high-quality data can help organizations start successful products, defend against digital attacks, understand failures and pivot toward success.

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Dataversity

JUNE 14, 2022

The post Data Governance at the Edge of the Cloud appeared first on DATAVERSITY. With that, I’ve long believed that for most large cloud platform providers offering managed services, such as document editing and storage, email services and calendar […].

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IBM Data Science in Practice

APRIL 26, 2024

Photo by Tim van der Kuip on Unsplash In the era of digital transformation, enterprises are increasingly relying on the power of artificial intelligence (AI) to unlock valuable insights from their vast repositories of data. Within this landscape, Cloud Pak for Data (CP4D) emerges as a pivotal platform.

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Dataversity

JULY 7, 2023

But the widespread harnessing of these tools will also soon create an epic flood of content based on unstructured data – representing an unprecedented […] The post Navigating the Risks of LLM AI Tools for Data Governance appeared first on DATAVERSITY.

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Dataversity

JULY 12, 2024

A large language model (LLM) is a type of artificial intelligence (AI) solution that can recognize and generate new content or text from existing content. It is estimated that by 2025, 50% of digital work will be automated through these LLM models.

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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.

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IBM Journey to AI blog

JUNE 12, 2023

Companies rely heavily on data and analytics to find and retain talent, drive engagement, improve productivity and more across enterprise talent management. However, analytics are only as good as the quality of the data, which must be error-free, trustworthy and transparent. What is data quality? million each year.

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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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Dataversity

JANUARY 13, 2025

Data has become a driving force behind change and innovation in 2025, fundamentally altering how businesses operate. Across sectors, organizations are using advancements in artificial intelligence (AI), machine learning (ML), and data-sharing technologies to improve decision-making, foster collaboration, and uncover new opportunities.

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Precisely

FEBRUARY 26, 2025

If pain points like these ring true for you, theres great news weve just announced significant enhancements to our Precisely Data Integrity Suite that directly target these challenges! Then, youll be ready to unlock new efficiencies and move forward with confident data-driven decision-making.

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Dataversity

APRIL 1, 2024

This reliance has spurred a significant shift across industries, driven by advancements in artificial intelligence (AI) and machine learning (ML), which thrive on comprehensive, high-quality data.

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Data Science Dojo

OCTOBER 10, 2023

The emergence of Artificial Intelligence in every field is reflected by the rise of its worth in the global market. The global market for artificial intelligence (AI) was worth USD 454.12 The global market for artificial intelligence (AI) was worth USD 454.12 billion by 2032. billion by 2032.

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IBM Journey to AI blog

AUGUST 23, 2023

The recent success of artificial intelligence based large language models has pushed the market to think more ambitiously about how AI could transform many enterprise processes. However, consumers and regulators have also become increasingly concerned with the safety of both their data and the AI models themselves.

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Precisely

AUGUST 29, 2024

Key Takeaways Data quality ensures your data is accurate, complete, reliable, and up to date – powering AI conclusions that reduce costs and increase revenue and compliance. Data observability continuously monitors data pipelines and alerts you to errors and anomalies. What does “quality” data mean, exactly?

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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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Precisely

AUGUST 8, 2023

Data governance is rapidly shifting from a leading-edge practice to a must-have framework for today’s enterprises. Although the term has been around for several decades, it is only now emerging as a widespread practice, as organizations experience the pain and compliance challenges associated with ungoverned data.

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Precisely

FEBRUARY 12, 2024

Here are some of the key trends and challenges facing telecommunications companies today: The growth of AI and machine learning: Telecom companies use artificial intelligence and machine learning (AI/ML) for predictive analytics and network troubleshooting. Data integration and data integrity are lacking.

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Dataversity

SEPTEMBER 18, 2023

The current wave of AI is creating new ways of working, and research suggests that business leaders feel optimistic about the potential for measurable productivity and customer service improvements, as well as transformations in the way that […] The post Data Governance in the Age of Generative AI appeared first on DATAVERSITY.

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Pickl AI

JANUARY 12, 2025

Introduction Are you struggling to decide between data-driven practices and AI-driven strategies for your business? Besides, there is a balance between the precision of traditional data analysis and the innovative potential of explainable artificial intelligence. These changes assure faster deliveries and lower costs.

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AWS Machine Learning Blog

AUGUST 21, 2024

A new data flow is created on the Data Wrangler console. Choose Get data insights to identify potential data quality issues and get recommendations. In the Create analysis pane, provide the following information: For Analysis type , choose Data Quality And Insights Report. For Target column , enter y.

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Dataversity

SEPTEMBER 16, 2024

Public sector agencies increasingly see artificial intelligence as a way to reshape their operations and services, but first, they must have confidence in their data. Accurate information is crucial to delivering essential services, while poor data quality can have far-reaching and sometimes catastrophic consequences.

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Alation

AUGUST 5, 2021

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

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Dataversity

JANUARY 8, 2021

More and more companies want to use artificial intelligence (AI) in their organization to improve operations and performance. The post Good AI in 2021 Starts with Great Data Quality appeared first on DATAVERSITY. Achieving good AI is a whole other story.

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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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Dataversity

MARCH 11, 2025

As artificial intelligence reshapes our world, an environmental crisis is building in its digital wake. Data center power demand is projected tosurge 160% by 2030, potentially generating up to $149 billion in social costs, including resource depletion, environmental impact, and public health.

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Precisely

SEPTEMBER 18, 2024

Businesses around the world are facing major challenges due to higher manufacturing costs, disruptive new technologies like artificial intelligence (AI), and tougher global competition. This means it’s more important than ever to make data-driven decisions, cut costs, and improve efficiency. You’re not alone.

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Dataversity

SEPTEMBER 18, 2024

Artificial Intelligence (AI) has earned a reputation as a silver bullet solution to a myriad of modern business challenges across industries. From improving diagnostic care to revolutionizing the customer experience, many industries and organizations have experienced the true transformational power of AI.

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Precisely

APRIL 25, 2024

Jean-Paul sat down for an interview where we discussed his background as a former CDO, the challenges he faced, and how he developed his unique perspective and data governance expertise. After starting my career in banking IT, I turned to consulting, and more specifically to Business Intelligence (BI) in 2004.

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IBM Journey to AI blog

OCTOBER 21, 2024

These platforms function as sophisticated ecosystems, facilitating the collection, analysis, interpretation and actionable implementation of insights from diverse data sources. Companies are investing heavily in big data and artificial intelligence (AI) to unlock these benefits. million annually due to poor data quality.

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IBM Journey to AI blog

JULY 9, 2024

Strong data governance is foundational to robust artificial intelligence (AI) governance. Companies developing or deploying responsible AI must start with strong data governance to prepare for current or upcoming regulations and to create AI that is explainable, transparent and fair.

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Alation

JULY 19, 2021

This requires a metadata management solution to enable data search & discovery and data governance, both of which empower access to both the metadata and the underlying data to those who need it. In today’s world, metadata management best practices call for a data catalog. Administrative information.

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