Precisely

JANUARY 9, 2025

Artificial Intelligence (AI) is all the rage, and rightly so. Which of course led to the adoption of data quality software as part of a data warehousing environment with the goal of executing rules to profile cleanse, standardize, reconcile, enrich, and monitor the data entering the DW to ensure it was fit for purpose.

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Precisely

SEPTEMBER 19, 2024

Robust data governance for AI ensures data privacy, compliance, and ethical AI use. Proactive data quality measures are critical, especially in AI applications. Using AI systems to analyze and improve data quality both benefits and contributes to the generation of high-quality data.

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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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Precisely

JANUARY 4, 2024

This was made resoundingly clear in the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, which surveyed over 450 data and analytics professionals globally. 70% who struggle to trust their data say data quality is the biggest issue.

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Data Quality Data Governance Analytics Analytics 75

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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Precisely

JANUARY 16, 2024

If your data quality is low or if your data assets are poorly governed, then you simply won’t be able to use them to make good business decisions. What are the biggest trends in data governance for 2024? Without Data Governance, AI Remains a Huge Liability Everyone’s talking about AI.

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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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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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Data Quality Data Governance Analytics Analytics 74

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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Precisely

SEPTEMBER 30, 2024

Key Takeaways By deploying technologies that can learn and improve over time, companies that embrace AI and machine learning can achieve significantly better results from their data quality initiatives. Here are five data quality best practices which business leaders should focus.

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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

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

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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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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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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Precisely

JANUARY 23, 2023

As enterprises forge ahead with a host of new data initiatives, data quality remains a top concern among C-level data executives. In its Data Integrity Trends report , Corinium found that 82% of respondents believe data quality concerns represent a barrier to their data integration projects.

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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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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 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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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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AWS Machine Learning Blog

APRIL 3, 2025

Data governance challenges Maintaining consistent data governance across different systems is crucial but complex. OMRONs data strategyrepresented on ODAPalso allowed the organization to unlock generative AI use cases focused on tangible business outcomes and enhanced productivity.

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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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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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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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Data Science Blog

JULY 23, 2023

It advocates decentralizing data ownership to domain-oriented teams. Each team becomes responsible for its Data Products , and a self-serve data infrastructure is established. This enables scalability, agility, and improved data quality while promoting data democratization.

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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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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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