AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone makes it straightforward for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization so they can discover, use, and collaborate to derive data-driven insights. A new data flow is created on the Data Wrangler console. Choose Create.

Machine Learning 123

Machine Learning Machine Learning Data Governance ML 123

Alation

MAY 27, 2021

For data-driven enterprises, data governance is no longer an option; it’s a necessity. Businesses are growing more dependent on data governance to manage data policies, compliance, and quality. For these reasons, a business’ data governance approach is essential. Data Democratization.

Data Governance 98

Data Governance Data Quality Data Wrangling SQL 98

Pickl AI

JULY 24, 2024

Summary: Data quality is a fundamental aspect of Machine Learning. Poor-quality data leads to biased and unreliable models, while high-quality data enables accurate predictions and insights. What is Data Quality in Machine Learning?

Data Quality 52

Data Quality Machine Learning Machine Learning Clean Data 52

Dataconomy

MARCH 17, 2025

Augmented analytics is revolutionizing how organizations interact with their data. By harnessing the power of machine learning (ML) and natural language processing (NLP), businesses can streamline their data analysis processes and make more informed decisions.

Augmented Analytics 91

Augmented Analytics Analytics Analytics Natural Language Processing 91

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?

Data Governance 96

Data Governance Data Quality Data Silos Analytics 96

Data Science Dojo

AUGUST 24, 2023

While DevOps and MLOps share many similarities, MLOps requires a more specialized set of tools and practices to address the unique challenges posed by data-driven and computationally intensive ML workflows. Data collection and preprocessing The first stage of the ML lifecycle involves the collection and preprocessing of data.

Machine Learning 195

Machine Learning Machine Learning ML ML 195

Alation

NOVEMBER 4, 2021

The practitioner asked me to add something to a presentation for his organization: the value of data governance for things other than data compliance and data security. Now to be honest, I immediately jumped onto data quality. Data quality is a very typical use case for data governance.

Data Governance 94

Data Governance Data Quality ML ML 94

Data Science Blog

JULY 23, 2023

Applications of BI, Data Science and Process Mining grow together More and more all these disciplines are growing together as they need to be combined in order to get the best insights. So while Process Mining can be seen as a subpart of BI while both are using Machine Learning for better analytical results.

Data Science 246

Data Science Azure Power BI Business Intelligence 246

Precisely

SEPTEMBER 19, 2024

Key Takeaways: Data integrity is essential for AI success and reliability – helping you prevent harmful biases and inaccuracies in AI models. Robust data governance for AI ensures data privacy, compliance, and ethical AI use. Proactive data quality measures are critical, especially in AI applications.

Data Governance 78

Data Governance Data Quality AI AI 78

Alation

FEBRUARY 3, 2022

DataOps practices help organizations overcome challenges caused by fragmented teams and processes and delays in delivering data in consumable forms. So how does data governance relate to DataOps? Data governance is a key data management process. Continuous Improvement Applied to Data Governance.

Data Governance 98

Data Governance DataOps Data Quality Machine Learning 98

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.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

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 […].

Data Governance 98

Data Governance Data Quality Cloud Data Artificial Intelligence 98

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.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

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.

Data Governance 69

Data Governance Data Quality Analytics Analytics 69

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.

AWS 84

AWS Data Governance Data Silos SQL 84

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.

Data Quality 74

Data Quality Data Profiling Data Governance Analytics 74

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.

Data Governance 98

Data Governance AI AI Data Quality 98

Alation

MARCH 5, 2021

Data governance defines how data should be gathered and used within an organization. It address core questions, such as: How does the business define data? How accurate must the data be for use? Organizations have much to gain from learning about and implementing a data governance framework.

Data Governance 59

Data Governance Data Quality Big Data Big Data 59

Dataversity

JULY 21, 2022

Despite its many benefits, the emergence of high-performance machine learning systems for augmented analytics over the last 10 years has led to a growing “plug-and-play” analytical culture, where high volumes of opaque data are thrown arbitrarily at an algorithm until it yields useful business intelligence.

Machine Learning 98

Machine Learning Machine Learning Augmented Analytics Business Intelligence 98

Dataversity

MARCH 14, 2022

The post When It Comes to Data Quality, Businesses Get Out What They Put In appeared first on DATAVERSITY. The stakes are high, so you search the web and find the most revered chicken parmesan recipe around. At the grocery store, it is immediately clear that some ingredients are much more […].

Data Quality 98

Data Quality Data Governance Big Data Big Data 98

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.

Data Quality 69

Data Quality Artificial Intelligence Artificial Intelligence Machine Learning 69

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.

Data Quality 52

Data Quality Data Governance ML ML 52

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.

Artificial Intelligence 80

Artificial Intelligence Artificial Intelligence Machine Learning Machine Learning 80

Data Science Dojo

JULY 6, 2023

These tools provide data engineers with the necessary capabilities to efficiently extract, transform, and load (ETL) data, build data pipelines, and prepare data for analysis and consumption by other applications. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineer 195

Data Engineer Data Engineering Data Engineering Data Engineering 195

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.

AWS 115

AWS AI AI Machine Learning 115

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?

Data Governance 52

Data Governance Data Quality Data Observability AI 52

Pickl AI

OCTOBER 19, 2023

Data quality plays a significant role in helping organizations strategize their policies that can keep them ahead of the crowd. Hence, companies need to adopt the right strategies that can help them filter the relevant data from the unwanted ones and get accurate and precise output.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

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.

Data Governance 64

Data Governance Analytics Analytics Machine Learning 64

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.

Data Governance 52

Data Governance Data Quality Big Data Analytics Big Data Analytics 52

DagsHub

AUGUST 23, 2024

Image generated with Midjourney Organizations increasingly rely on data to make business decisions, develop strategies, or even make data or machine learning models their key product. As such, the quality of their data can make or break the success of the company. What is a data quality framework?

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

IBM Journey to AI blog

AUGUST 23, 2023

Because of this, when we look to manage and govern the deployment of AI models, we must first focus on governing the data that the AI models are trained on. This data governance requires us to understand the origin, sensitivity, and lifecycle of all the data that we use. and watsonx.data.

Data Governance 66

Data Governance AI AI Artificial Intelligence 66

Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications.

Data Observability 52

Data Observability Data Quality Data Governance Data Pipeline 52

Alation

JULY 6, 2021

Common Data Governance Challenges. Every enterprise runs into data governance challenges eventually. Issues like data visibility, quality, and security are common and complex. Data governance is often introduced as a potential solution. And one enterprise alone can generate a world of data.

Data Governance 52

Data Governance Data Quality Data Silos Data Profiling 52

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.

Data Quality 52

Data Quality ML ML Machine Learning 52

Alation

MARCH 17, 2021

Key Features of a Machine Learning Data Catalog. Data intelligence is crucial for the development of data catalogs. At the center of this innovation are machine learning data catalogs (MLDCs). Unlike standalone tools, machine learning data catalogs have features like: Data search.

Machine Learning 52

Machine Learning Machine Learning Data Governance Data Quality 52

Data Science Dojo

JANUARY 12, 2023

You can perform analytics with Data Lakes without moving your data to a different analytics system. 4. Additionally, unprocessed, raw data is pliable and suitable for machine learning. Healthcare: Unstructured data is stored in data lakes. References: Data lake vs data warehouse

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

Alation

MAY 31, 2023

The state of data governance is evolving as organizations recognize the significance of managing and protecting their data. With stricter regulations and greater demand for data-driven insights, effective data governance frameworks are critical. What is a data architect?

Data Governance 52

Data Governance Data Quality Data Silos Data Modeling 52