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.

Data Quality 98

Data Quality Data Governance ETL Data Observability 98

Tableau

SEPTEMBER 23, 2021

If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? We’re all trying to use more data to make decisions, but constantly face roadblocks and trust issues related to data governance. . A data governance framework.

Data Governance 102

Data Governance Analytics Analytics Tableau 102

Data Science Dojo

JUNE 5, 2023

Data governance : Establishing robust data governance practices is crucial for ensuring responsible AI. Non-profit organizations should have clear policies for data collection, storage, and usage. These guidelines should address issues such as bias, privacy, transparency, and accountability.

AI 332

AI AI Data Governance Data Scientist 332

Tableau

SEPTEMBER 23, 2021

If we asked you, “What does your organization need to help more employees be data-driven?” where would “better data governance” land on your list? We’re all trying to use more data to make decisions, but constantly face roadblocks and trust issues related to data governance. . A data governance framework.

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Data Governance Analytics Analytics Tableau 97

IBM Journey to AI blog

SEPTEMBER 5, 2024

Everything is data—digital messages, emails, customer information, contracts, presentations, sensor data—virtually anything humans interact with can be converted into data, analyzed for insights or transformed into a product. Managing this level of oversight requires adept handling of large volumes of data.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

Data Science Dojo

MARCH 24, 2023

The goal of MLOps is to ensure that models are reliable, secure, and scalable, while also making it easier for data scientists and engineers to develop, test, and deploy ML models. Here are some of the key best practices: Start with a solid data management strategy : A solid data management strategy is the foundation of MLOps.

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Machine Learning Machine Learning ML ML 195

Data Science Dojo

MARCH 24, 2023

The goal of ML Ops is to ensure that models are reliable, secure, and scalable, while also making it easier for data scientists and engineers to develop, test, and deploy ML models. Here are some of the key best practices: Start with a solid data management strategy : A solid data management strategy is the foundation of ML Ops.

Machine Learning 195

Machine Learning Machine Learning ML ML 195

Alation

SEPTEMBER 7, 2021

In the previous blog , we discussed how Alation provides a platform for data scientists and analysts to complete projects and analysis at speed. In this blog we will discuss how Alation helps minimize risk with active data governance. But governance is a time-consuming process (for users and data stewards alike).

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Data Governance Data Scientist Data Quality Data Profiling 59

Precisely

FEBRUARY 12, 2024

Read our eBook Data Governance 101 Read this eBook to learn about the challenges associated with data governance and how to operationalize solutions. Read Common Data Challenges in Telecommunications As natural innovators, telecommunications firms have been early adopters of advanced analytics.

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Data Governance Analytics Analytics Machine Learning 64

Alation

DECEMBER 15, 2021

Yet high-volume collection makes keeping that foundation sound a challenge, as the amount of data collected by businesses is greater than ever before. An effective data governance strategy is critical for unlocking the full benefits of this information. Data governance requires a system.

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Data Governance Data Quality Analytics Analytics 52

Data Science Dojo

JANUARY 12, 2023

Through data crawling, cataloguing, and indexing, they also enable you to know what data is in the lake. To preserve your digital assets, data must lastly be secured. To comprehend and transform raw, unstructured data for any specific business use, it typically takes a data scientist and specialized tools.

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Data Lakes Data Warehouse Hadoop Machine Learning 221

Pickl AI

APRIL 14, 2023

In this blog, we are going to discuss more on What are Data platforms & Data Governance. Key Highlights As our dependency on data increases, so does the need to have defined governance policies also rises. Here comes the role of Data Governance. Thus reducing the risk and misuse of data.

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Data Governance Data Quality Analytics Analytics 52

Alation

JULY 21, 2021

I’m pleased to share that Alation has been named a data governance leader in the new report, The Forrester Wave : Data Governance Solutions, Q3 2021. This recognition from Forrester is gratifying, as it aligns with the success our customers are having with Alation and their data governance programs.

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Data Governance Data Analyst Data Scientist Machine Learning 52

IBM Data Science in Practice

APRIL 26, 2024

In this blog, we explore how the introduction of SQL Asset Type enhances the metadata enrichment process within the IBM Knowledge Catalog , enhancing data governance and consumption. Data Stewardship : Data stewards can utilize dynamic views for metadata enrichment, profiling, and data governance activities.

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SQL Data Quality Data Governance Data Scientist 130

AWS Machine Learning Blog

OCTOBER 20, 2023

Data and governance foundations – This function uses a data mesh architecture for setting up and operating the data lake, central feature store, and data governance foundations to enable fine-grained data access.

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ML ML AWS Data Lakes 132

SAS Software

DECEMBER 9, 2024

In 2012, Harvard Business Review declared the data scientist the sexiest job of the 21st century. Heres what we knew at the time: big data was (and still is to this day) an enormous opportunity to make new discoveries. In the data and AI era Will data engineering reign supreme?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

IBM Journey to AI blog

FEBRUARY 26, 2024

The financial services industry has been in the process of modernizing its data governance for more than a decade. But as we inch closer to global economic downturn, the need for top-notch governance has become increasingly urgent. Trust and data governance Data governance isn’t new, especially in the financial world.

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Data Pipeline Data Engineering Data Engineering Data Engineering 112

Dataconomy

APRIL 6, 2023

Data democratization is a term that has been gaining traction in recent years, referring to the process of making data more accessible and usable for a wider range of people. Essentially, it involves removing barriers to accessing and using data so that it is no longer the exclusive domain of data scientists and other experts.

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Data Governance Data Silos Data Analysis Data Analysis 118

IBM Journey to AI blog

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

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AI AI Data Scientist Data Governance 93

The Data Administration Newsletter

JANUARY 3, 2023

Have you ever considered the value of data? Let me ask you a question: Where does data typically start? Data usually begins somewhere in a hard drive, warehouse, NAS (network-attached storage), server or some other system that can store data. When data is collected and stored, it […].

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Data Scientist Big Data Big Data Data Governance 52

The Data Administration Newsletter

OCTOBER 17, 2023

Where exactly within an organization does the primary responsibility lie for ensuring that a data pipeline project generates data of high quality, and who exactly holds that responsibility? Who is accountable for ensuring that the data is accurate? Is it the data engineers? The data scientists?

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Data Pipeline Data Quality Data Governance Data Analyst 52

Alation

JULY 19, 2021

Folks who work closely with data, like analysts, data scientists, and IT teams, rely on metadata to give them crucial context for how to use a given asset. Today, metadata is extremely helpful in classifying, describing, and providing critical information about digital data. Administrative information.

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Data Governance Machine Learning Machine Learning Artificial Intelligence 105

Data Science Dojo

OCTOBER 10, 2023

The speaker is Andrew Madson, a data analytics leader and educator. The event is for anyone interested in learning about generative AI and data storytelling, including business leaders, data scientists, and enthusiasts. 360 curates’ content and learning paths to suit virtually every IT role and team configuration.

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AI AI Data Observability Artificial Intelligence 243

Data Science Dojo

JANUARY 13, 2023

Women in Data Science (WiDS) – California, United States Women in Data Science (WiDS) is an annual conference held at Stanford University, California, United States and other locations worldwide. The conference is focused on the representation, education, and achievements of women in the field of data science.

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ODSC - Open Data Science

JANUARY 9, 2024

This will become more important as the volume of this data grows in scale. Data Governance Data governance is the process of managing data to ensure its quality, accuracy, and security. Data governance is becoming increasingly important as organizations become more reliant on data.

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Data Engineer Data Engineering Data Engineering Data Engineering 97

The Data Administration Newsletter

OCTOBER 5, 2021

Data is the raw material for any type of analytics – whether it is related to historical analysis presented in reports and dashboards by business analysts, or predictive analysis that involves building a model by data scientists that anticipates an event or behavior that has not yet occurred.

Data Science 69

Data Science Data Scientist Analytics Analytics 69

IBM Journey to AI blog

OCTOBER 21, 2024

Fragmented data stacks, combined with the promise of generative AI, amplify productivity pressure and expose gaps in enterprise readiness for this emerging technology. While turning data into meaningful intelligence is crucial, users such as analysts and data scientists are increasingly overwhelmed by vast quantities of information.

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Data Governance Data Quality Analytics Analytics 87

Alation

JULY 15, 2022

And, while change at large organisations is tough, data leaders would be wise to reframe such transformations as business opportunities rather than burdens. The business opportunity: Data governance exposes inefficiency. However, these manual steps weren’t transparent until active data governance required it.

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Data Governance Data Quality Data Scientist 89

Dataconomy

SEPTEMBER 4, 2023

Understand what insights you need to gain from your data to drive business growth and strategy. Best practices in cloud analytics are essential to maintain data quality, security, and compliance ( Image credit ) Data governance: Establish robust data governance practices to ensure data quality, security, and compliance.

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AWS Machine Learning Blog

OCTOBER 2, 2024

However, a more holistic organizational approach is crucial because generative AI practitioners, data scientists, or developers can potentially use a wide range of technologies, models, and datasets to circumvent the established controls. The second level is to set guardrails around the framework for each use case.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

With SageMaker MLOps tools, teams can easily train, test, troubleshoot, deploy, and govern ML models at scale to boost productivity of data scientists and ML engineers while maintaining model performance in production. Data Management – Efficient data management is crucial for AI/ML platforms.

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ML ML AWS AI 121

IBM Journey to AI blog

AUGUST 2, 2023

Built on IBM’s Cognitive Enterprise Data Platform (CEDP), Wf360 compiles data from more than 30 sources and now delivers monthly insights to HR leaders 23 days earlier than before. Data quality is critical for data governance.

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Data Quality Data Governance Analytics Analytics 73

IBM Journey to AI blog

JULY 24, 2024

By providing access to a wider pool of trusted data, it enhances the relevance and precision of AI models, accelerating innovation in these areas. IBM watsonx.data enhances this approach with built-in data governance features, such as having a single point of entry and robust access control.

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Data Governance Data Warehouse Data Preparation Analytics 69

Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

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Big Data Big Data Data Engineer Data Engineering 91

Flipboard

APRIL 22, 2025

Depending on the implementations complexity, you might need new positions like data scientists, machine learning engineers or specialists. Invest in tech (and training) To truly harness AI’s potential, focus on bringing in new talent and continuously training existing employees.

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AI AI Data Governance Data Scientist 116

Alation

NOVEMBER 16, 2021

Data Governance is growing essential. Data growth, shrinking talent pool, data silos – legacy & modern, hybrid & cloud, and multiple tools – add to their challenges. They often lack guidance into how to prioritize curation and data documentation efforts.

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Data Governance Data Scientist SQL Data Silos 52

The MLOps Blog

JUNE 27, 2023

Some popular end-to-end MLOps platforms in 2023 Amazon SageMaker Amazon SageMaker provides a unified interface for data preprocessing, model training, and experimentation, allowing data scientists to collaborate and share code easily. Check out the Kubeflow documentation.

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Machine Learning Machine Learning ML ML 134