5 ways to use AI and machine learning in dataops
SEPTEMBER 11, 2023
Data wrangling, dataops, data prep, data integration—whatever your organization calls it, managing the operations to integrate and cleanse data is …
DataOps and Scalability: The One-Two Punch for Creating Successful Data Products
Dataversity
MAY 16, 2025
Data products are proliferating in the enterprise, and the good news is that users are consuming data products at an accelerated rate, whether its an AI model, a BI interface, or an embedded dashboard on a website.
DataOps 
52
52 Join 17,000+
professionals
Sign Up for our Newsletter
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Achieving Successful Outcomes: Why AI Must Be Considered an Extension of Data Products
Dataversity
MAY 28, 2025
In many organizations, AI exists as a secret weapon. However, using AI in this limited fashion eliminates the huge potential impact that AI can have across ones business. Its essentially locked away in a box, brought out to work on a limited use case, and then put back into the box.
DataOps 59
59 
The Future Of TechOps With GenAI
DECEMBER 10, 2024
Technology operations (TechOps) is a broad topic that includes AIOps, SecOps, DevOps, FinOps, DataOps and so on. Generative AI (GenAI), armed with large language models (LLMs) and agentic AI, Sandeep Shilawat is a renowned tech innovator, thought leader and strategic advisor in U.S. federal markets.
DataOps 159
159 
Five Important Trends in Big Data Analytics
FEBRUARY 3, 2023
Over the last few years, with the rapid growth of data, pipeline, AI/ML, and analytics, DataOps has become a noteworthy piece of day-to-day business New-age technologies are almost entirely running the world today. Among these technologies, big data has gained significant traction. This concept is …
What Is DataOps? Definition, Principles, and Benefits
Alation
SEPTEMBER 28, 2022
What exactly is DataOps ? This is nothing new, as 74% of respondents indicated that new compliance and regulatory requirements have accelerated the adoption of DataOps (IDC). This is nothing new, as 74% of respondents indicated that new compliance and regulatory requirements have accelerated the adoption of DataOps (IDC).
DataOps 52
52 
Take the Route to AI Success with DataOps and MLOps
DataRobot Blog
AUGUST 16, 2022
If you’ve been keeping up with business literature lately, you know that adopting artificial intelligence (AI) strategies can increase company revenue, improve efficiency, and keep customers happy. If deployment goes wrong, DataOps/MLOps can even help solve the problem. What are companies actually doing today? Survey Questions.
DataOps 52
52 
The Shift from Models to Compound AI Systems
BAIR
FEBRUARY 17, 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.
AI 145
145 
IBM Consulting unveils Center of Excellence for generative AI
IBM Journey to AI blog
MAY 25, 2023
IBM Consulting has established a Center of Excellence for generative AI. It stands alongside IBM Consulting’s existing global AI and Automation practice, which includes 21,000 data and AI consultants who have conducted over 40,000 enterprise client engagements. The CoE is off to a fast start.
AI 114
114 
The Three Things Data Practitioners Struggle With
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.
DataOps 64
64 
How to Ensure Continuous Improvement With Data Governance
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.
Building and Scaling Gen AI Applications with Simplicity, Performance and Risk Mitigation in Mind Using Iguazio (acquired by McKinsey) and MongoDB
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.
AI 132
132 
Supercharge your data strategy: Integrate and innovate today leveraging data integration
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.
Data Silos 102
102 
Unlocking the Power of AI with Implemented Machine Learning Ops Projects
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.
The Audience for Data Catalogs and Data Intelligence
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.
DataOps 52
52 
Big data management
Dataconomy
MAY 26, 2025
Leveraging advanced technologies Utilizing machine learning and AI can significantly enhance data analytics capabilities, providing deeper insights. Innovations on the horizon Anticipated advancements include: AI and machine learning: These technologies are expected to further improve data analysis capabilities.
Big Data 91
91 
Data Trends for 2023
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.
DataOps 52
52 
AIOps vs. MLOps: Harnessing big data for “smarter” ITOPs
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.
Big Data 106
106 
Navigating the path to generative AI success across industries: A Grid Dynamics crawl-walk-run strategy
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.
Data Quality 70
70 
Forging a Data Strategy for Success in Uncertain Times
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.
DataOps 98
98 
Popular Machine Learning Libraries, Ethical Interactions Between Humans and AI, and 10 AI Startups…
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.
How HR Tech Company Sense Scaled their ML Operations using Iguazio
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
52 
Data Integrity Trends for 2024
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.
Data Quality 69
69 
What Do Data Scientists Do? A Guide to AI Maturity, Challenges, and Solutions
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.
9 data governance strategies that will unlock the potential of your business data
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.
How Sense Uses Iguazio as a Key Component of Their ML Stack
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
52 
What Is a Data Fabric and How Does a Data Catalog Support It?
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!
DataOps 52
52 
How GPT helped expand our marketing team’s capacity
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
52 
Authoring custom transformations in Amazon SageMaker Data Wrangler using NLTK and SciPy
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.
AWS 103
103 
How GPT helped expand our marketing team’s capacity
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
52 
How GPT helped expand our marketing team’s capacity
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
52 
Speed Up AI Development by Hiring a Chief Data Officer
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 […].
AI 59
59 
The Shift from Models to Compound AI Systems
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.
AI 40
40 
Alation 2023.1: Easing Self-Service for the Modern Data Stack with Databricks and dbt Labs
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.
DataOps 52
52 
Alation Launches Data Governance App and Supporting Service Offering
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.
How Data Observability Helps to Build Trusted Data
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?
Why Lean Data Management Is Vital for Agile Companies
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.
Data Silos 52
52 
phData Awarded Snowflake 2023 Partner of the Year
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.
DataOps 52
52 
phData Awarded dbt Labs’ 2024 Partner of the Year
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?
DataOps 52
52 
Enterprise Analytics: Key Challenges & Strategies
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.
Analytics 52
52 
What Is Data Observability and Why You Need It?
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.
Automating Model Risk Compliance: Model Monitoring
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.
ML 59
59 
Cloud-Based Data Management Platforms in the Age of Privacy
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.
Navigating Biden’s AI executive order with AI data development
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 111
111 
Let's personalize your content