Dataversity

SEPTEMBER 8, 2023

As AI grows more prominent, data initiatives are more important than ever. As the digital age propels us forward, the need for robust DataOps strategies becomes evident. Data Management has never been more critical than today. These strategies, however, are not devoid of challenges.

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Alation

FEBRUARY 3, 2022

The goal of DataOps is to create predictable delivery and change management of data and all data-related artifacts. 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? Parting Words.

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Iguazio

JULY 22, 2024

AI and generative Al can lead to major enterprise advancements and productivity gains. One popular gen AI use case is customer service and personalization. Gen AI chatbots have quickly transformed the way that customers interact with organizations. Another less obvious use case is fraud detection and prevention.

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Becoming Human

MAY 11, 2023

MLOps projects are becoming increasingly popular as companies seek to leverage the power of AI to gain a competitive edge. DevOps and DataOps: DevOps and DataOps are related approaches that emphasize collaboration between software developers and IT operations teams. Both can be useful in implementing MLOps projects.

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Machine Learning Machine Learning DataOps Cloud Computing 78

IBM Journey to AI blog

OCTOBER 22, 2024

Data is the differentiator as business leaders look to utilize their competitive edge as they implement generative AI (gen AI). Leaders feel the pressure to infuse their processes with artificial intelligence (AI) and are looking for ways to harness the insights in their data platforms to fuel this movement.

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Alation

JUNE 21, 2022

Over time, we called the “thing” a data catalog , blending the Google-style, AI/ML-based relevancy with more Yahoo-style manual curation and wikis. ML and DataOps teams). At one level, it makes sense – there is certainly a lot of interest in DataOps today. Thus was born the data catalog. data pipelines) to support.

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DataOps Data Scientist Data Quality Data Pipeline 52

Precisely

FEBRUARY 10, 2023

Advanced analytics and AI/ML continue to be hot data trends in 2023. Read our Report Improving Data Integrity and Trust through Transparency and Enrichment Data trends for 2023 point to the need for enterprises to govern and manage data at scale, using automation and AI/ML technology.

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IBM Journey to AI blog

AUGUST 12, 2024

AIOPs refers to the application of artificial intelligence (AI) and machine learning (ML) techniques to enhance and automate various aspects of IT operations (ITOps). However, they differ fundamentally in their purpose and level of specialization in AI and ML environments.

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Dataconomy

MAY 26, 2023

With all the recent buzz around ChatGPT, industries are looking for ways to leverage generative AI to gain a competitive edge. After all, generative AI is expected to raise the global GDP by 7% or $7 trillion within a 10-year period. Without a clear strategy and solid business case, these investments may only yield small gains.

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Precisely

AUGUST 3, 2023

For example, workflow automation (43%), AI/ ML (41%), and DataOps (31%) are complementary technologies that enable organizations to automate data management and data processes so they can improve data quality even when people and skills are scarce.

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ODSC - Open Data Science

JULY 20, 2023

Popular Machine Learning Libraries, Ethical Interactions Between Humans and AI, and 10 AI Startups in APAC to Follow Demystifying Machine Learning: Popular ML Libraries and Tools In this comprehensive guide, we will demystify machine learning, breaking it down into digestible concepts for beginners, including some popular ML libraries to use.

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Machine Learning Machine Learning AI AI 52

Iguazio

JANUARY 16, 2024

Sense is a talent engagement company whose platform improves the recruitment processes with automation, AI and personalization. Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization including a large number of data and AI professionals.

ML 52

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Precisely

FEBRUARY 9, 2024

In 2023, organizations dealt with more data than ever and witnessed a surge in demand for artificial intelligence use cases – particularly driven by generative AI. It’s easy to see why there’s been an astronomical rise in the usage of generative AI over the past year for consumers and business users alike.

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DataRobot Blog

SEPTEMBER 13, 2022

They develop and continuously optimize AI/ML models , collaborating with stakeholders across the enterprise to inform decisions that drive strategic business value. What data scientists do is directly tied to an organization’s AI maturity level. Driving Innovation with AI: Getting Ahead with DataOps and MLOps.

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IBM Journey to AI blog

SEPTEMBER 5, 2024

Emerging technologies and trends, such as machine learning (ML), artificial intelligence (AI), automation and generative AI (gen AI), all rely on good data quality. To maximize the value of their AI initiatives, organizations must maintain data integrity throughout its lifecycle.

Data Governance 75

Data Governance Data Quality DataOps Artificial Intelligence 75

Iguazio

JANUARY 16, 2024

Sense is a talent engagement platform that improves recruitment processes with automation, AI and personalization. Since AI is a central pillar of their value offering, Sense has invested heavily in a robust engineering organization, including a large number of data and data science professionals. Enabling quick experimentation.

ML 52

ML ML DataOps Data Scientist 52

Alation

JANUARY 25, 2022

AI and ML in action: Auto-suggestions streamline the buildout of business glossaries. Automated Data Orchestration (AKA DataOps). DataOps is the leading process concept in data today. See Gartner’s “ How DataOps Amplifies Data and Analytics Business Value ”). We’ve arrived at the top layer of the fabric!

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Snorkel AI

AUGUST 29, 2023

GPT-3’s generative AI helped unlock additional capacity for me as the Data Science Content Lead here at Snorkel AI. Sometimes it would return a list of tweets with the specified tone followed by the text, such as “Funny: With Snowflake and Snorkel AI, you can label your data faster than you can say ‘DataOps’!

DataOps 52

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Snorkel AI

AUGUST 29, 2023

GPT-3’s generative AI helped unlock additional capacity for me as the Data Science Content Lead here at Snorkel AI. Sometimes it would return a list of tweets with the specified tone followed by the text, such as “Funny: With Snowflake and Snorkel AI, you can label your data faster than you can say ‘DataOps’!

DataOps 52

DataOps Python Artificial Intelligence Artificial Intelligence 52

Snorkel AI

AUGUST 29, 2023

GPT-3’s generative AI helped unlock additional capacity for me as the Data Science Content Lead here at Snorkel AI. Sometimes it would return a list of tweets with the specified tone followed by the text, such as “Funny: With Snowflake and Snorkel AI, you can label your data faster than you can say ‘DataOps’!

DataOps 52

DataOps Python Artificial Intelligence Artificial Intelligence 52

Dataversity

JUNE 23, 2021

The post Speed Up AI Development by Hiring a Chief Data Officer appeared first on DATAVERSITY. A position once laser-focused on regulatory compliance is today one of the most strategic enterprise decision-makers. As companies plan for a rebound from the pandemic, the CDO […].

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AWS Machine Learning Blog

APRIL 17, 2023

In other words, companies need to move from a model-centric approach to a data-centric approach.” – Andrew Ng A data-centric AI approach involves building AI systems with quality data involving data preparation and feature engineering. AWS AI services easily integrate with your applications to address many common use cases.

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BAIR

FEBRUARY 18, 2024

This is enforced with the `more` excerpt separator. --> AI caught everyone’s attention in 2023 with Large Language Models (LLMs) that can be instructed to perform general tasks, such as translation or coding, just by prompting. In this post, we analyze the trend toward compound AI systems and what it means for AI developers.

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AI AI DataOps Data Pipeline 40

Alation

APRIL 4, 2023

Troubleshooting data issues , for an exploding number of disjointed systems and tools, breaks self-service for data users and creates gaps in visibility for dataOps. Building data pipelines is challenging, and complex requirements (as well as the separation of many sources) leads to a lack of trust.

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Alation

SEPTEMBER 14, 2021

Stewardship Workbench: This feature uses AI and ML to automate the discovery of candidate data stewards based on who is actually using data. Given this, data governance should be a key enabler of DataOps. It improves governance processes and makes DataOps processes less constraining upon organizations.

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Precisely

SEPTEMBER 18, 2023

Data observability is a key element of data operations (DataOps). It enables a big-picture understanding of the health of your organization’s data through continuous AI/ML-enabled monitoring – detecting anomalies throughout the data pipeline and preventing data downtime. Why is data observability so important?

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Pickl AI

DECEMBER 11, 2024

By leveraging AI and automation, organisations optimise operations and maintain competitive advantage in fast-changing markets. AI and automation optimise data processes, improving accuracy and efficiency. AI-driven tools also facilitate predictive analytics, enabling businesses to make proactive decisions.

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phData

JUNE 26, 2023

We’re constantly diving into our customer’s challenges and finding innovative ways to help solve them through custom data and AI solutions, often centered around Snowflake. Through our work, phData has boasted a 98 percent average renewal rate for phData Elastic Operations, DataOps, and MLOps.

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phData

OCTOBER 8, 2024

Throughout our work, phData has boasted a 98 percent average renewal rate for phData Elastic Operations, DataOps, and MLOps. Here at phData, our goal is to be the world leader in delivering data & AI services and products on a modern data platform using best-of-breed technology. What’s Next for phData and dbt?

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DataOps Data Modeling Data Models SQL 52

Alation

OCTOBER 12, 2021

DataOps. … Nowadays, machine learning , AI, and augmented reality analytics are speeding up this process, so that collection and analysis are always on. Data engineering. Analytics forecasting. Linear programming. The field has modernized rapidly in recent years. One step followed the other.

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Precisely

DECEMBER 12, 2023

Data observability is a foundational element of data operations (DataOps). The best data observability tools incorporate AI to identify and prioritize potential issues. For a data scientist building machine learning models for an important AI initiative, data observability helps set the stage for long-term success.

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Data Observability Data Quality Data Pipeline Machine Learning 52

DataRobot Blog

JUNE 27, 2022

Driving Innovation with AI: Getting Ahead with DataOps and MLOps. The post Automating Model Risk Compliance: Model Monitoring appeared first on DataRobot AI Cloud. BARC INDUSTRY ANALYST REPORT. Download now.

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ML ML Machine Learning Machine Learning 59

Dataversity

FEBRUARY 4, 2021

Click to learn more about author Keith D. Currently, many businesses are using public clouds to do their Data Management. Data Management platforms (DMPs) started becoming popular during the late 1990s and the early 2000s.

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Snorkel AI

OCTOBER 31, 2023

government to address the safety, transparency, and use of AI in the near future. As AI takes a larger role in all of our lives, those are important concerns to consider. They also represent difficult challenges that require an acute focus on data that is used to train the AI itself and how it is prepared, managed, and applied.

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AI AI DataOps Data Governance 111

Snorkel AI

OCTOBER 31, 2023

government to address the safety, transparency, and use of AI in the near future. As AI takes a larger role in all of our lives, those are important concerns to consider. They also represent difficult challenges that require an acute focus on data that is used to train the AI itself and how it is prepared, managed, and applied.

AI 103

AI AI DataOps Data Governance 103

Snorkel AI

OCTOBER 31, 2023

government to address the safety, transparency, and use of AI in the near future. As AI takes a larger role in all of our lives, those are important concerns to consider. They also represent difficult challenges that require an acute focus on data that is used to train the AI itself and how it is prepared, managed, and applied.

AI 52

AI AI DataOps Data Governance 52