Smart Data Collective

JANUARY 8, 2021

Data governance is going to be one of the most crucial things in the future as we work towards more adoption of artificial intelligence and machine learning. A huge component of artificial intelligence is machine learning. This will only work if they have access to that unlimited data.

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Data Science Dojo

FEBRUARY 13, 2025

With rapid advancements in machine learning, generative AI, and big data, 2025 is set to be a landmark year for AI discussions, breakthroughs, and collaborations. Machine Learning & AI Applications Discover the latest advancements in AI-driven automation, natural language processing (NLP), and computer vision.

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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. He supports enterprise customers migrate and modernize their workloads on AWS cloud.

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Machine Learning Machine Learning Data Governance ML 111

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. ZenML is intended to be a highly extensible and adaptable MLOps framework.

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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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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.

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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.

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Data Science Dojo

JANUARY 13, 2023

In this blog, we will share the list of leading data science conferences across the world to be held in 2023. This will help you to learn and grow your career in data science, AI and machine learning. Top data science conferences 2023 in different regions of the world 1.

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insideBIGDATA

OCTOBER 3, 2023

However, the increasing complexity of the data landscape is making it a huge challenge to provide users and applications with fast access required, while ensuring regulatory compliance.

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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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Data Governance Data Quality Cloud Data Artificial Intelligence 98

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

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Data Quality Data Governance ETL Data Observability 98

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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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.

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Flipboard

NOVEMBER 14, 2023

Modern data quality practices leverage advanced technologies, automation, and machine learning to handle diverse data sources, ensure real-time processing, and foster collaboration across stakeholders.

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Data Quality Data Governance Machine Learning Machine Learning 143

Alation

JANUARY 20, 2022

In Ryan’s “9-Step Process for Better Data Quality” he discussed the processes for generating data that business leaders consider trustworthy. To be clear, data quality is one of several types of data governance as defined by Gartner and the Data Governance Institute. Frequency of data?

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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.

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Machine Learning Machine Learning Augmented Analytics Business Intelligence 98

Flipboard

DECEMBER 17, 2024

Build responsible AI applications with Guardrails Amazon Bedrock Guardrails provides configurable safeguards to help safely build generative AI

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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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Data Governance Data Quality DataOps Artificial Intelligence 75

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.

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Dataconomy

DECEMBER 25, 2024

Predictive healthcare analytics refers to the use of advanced data analytics techniques, such as artificial intelligence, machine learning, data mining, and statistical modeling, to forecast future health outcomes based on historical data. What is predictive healthcare analytics?

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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 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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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.

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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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Data Science Dojo

NOVEMBER 15, 2023

Attendees will learn about key LLM strategies, proven techniques, and real-world examples of how LLMs are being used to transform data processes. Bhatti is a hands-on practitioner of machine learning and has extensive experience in applying AI to solve real-world problems. Registration will open in November 2023.

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Towards AI

NOVEMBER 4, 2024

In this blog, we’ll unpack the differences between data and AI governance, examining the new factors leaders must consider when designing their AI governance programs. What makes AI governance different from data governance?

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AI AI Data Governance Artificial Intelligence 122

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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Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

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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? What is Data Quality in Machine Learning?

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Precisely

SEPTEMBER 15, 2023

Data governance is no trivial undertaking. When executed correctly, data governance transitions businesses from guesswork to data-informed strategies. For those who follow the right roadmap on their data governance journey, the payoff can be enormous.

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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?

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Precisely

AUGUST 29, 2024

Data observability continuously monitors data pipelines and alerts you to errors and anomalies. Data governance ensures AI models have access to all necessary information and that the data is used responsibly in compliance with privacy, security, and other relevant policies. stored: where is it located?

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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

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AWS Machine Learning Blog

JUNE 5, 2023

Data is the foundation for machine learning (ML) algorithms. One of the most common formats for storing large amounts of data is Apache Parquet due to its compact and highly efficient format. In this post, we show you how to import Parquet data to Canvas from Athena, where Lake Formation enables data governance.

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The Data Administration Newsletter

JUNE 6, 2023

Data privacy and security matter. Given this, it will be a big deal if machine learning can make them easier to implement. So, how do CIOs and other security thought leaders think machine learning applies to privacy and security?

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Machine Learning Machine Learning Data Governance 52

DagsHub

FEBRUARY 29, 2024

Introduction Machine learning models learn patterns from data and leverage the learning, captured in the model weights, to make predictions on new, unseen data. Data, is therefore, essential to the quality and performance of machine learning models. million per year.

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How to Learn Machine Learning

APRIL 23, 2023

Companies use Machine Learning to make their processes smooth, fast, and convenient. However, there are barriers to machine learning, and the journey to adopting these kind of projects can be challenging. The extraction of data is another thing to consider. These phases are essential for having good data.

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