DataRobot

JUNE 16, 2021

Our DataRobot MLOps product has focused on resolving many of the issues with bringing models into production. Additionally, we have recently announced a partnership and integration with Snowflake to expand deployment options by bringing models directly into the database. New in DataRobot MLOps Release 7.1:

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DataRobot Blog

JULY 27, 2022

We combined the resources and expertise of DataRobot MLOps and Algorithmia to achieve the best results. DataRobot AI Cloud platform has an absolutely fantastic training pipeline with AutoML and also has a rock-solid inference system. The Demo: Autoscaling with MLOps. Operationalize ML Faster with MLOps Automation.

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DataRobot

JUNE 29, 2021

Those who watched the vision presentation at the recent AI Experience 2021 event might have noticed that we quietly announced a new MLOps feature called Continuous AI. It’s possibly the most innovative capability we have added to the DataRobot AI platform in some time. Continuous AI = AutoML + MLOps. It asks The Robot.

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DataRobot

JULY 27, 2021

Additionally, we’re announcing our acquisition of Algorithmia , a leader in MLOps. . Every day, I’m more and more inspired by what our customers are accomplishing using DataRobot’s Augmented Intelligence platform. billion models on our cloud platform. An Unprecedented Market Opportunity. I stand by that notion wholeheartedly.

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DataRobot Blog

MARCH 8, 2023

As a result, enterprises can now get powerful insights and predictive analytics from their business data by integrating DataRobot-trained machine learning models into their SAP-specific business processes and applications, while bringing data science and analytics teams and business users closer together for better outcomes.

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DataRobot Blog

MARCH 16, 2023

Today we are unveiling a new cutting-edge integration with Microsoft Azure OpenAI Service. This integration, which leverages the ChatGPT model in Azure OpenAI, provides a conversational AI experience that will allow you to interact with and interpret model results and predictions directly.

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DataRobot Blog

FEBRUARY 28, 2023

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. According to Flexera 1 , 92% of enterprises have a multi-cloud strategy, while 80% have a hybrid cloud strategy.

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DataRobot Blog

JUNE 16, 2022

We’re excited to announce DataRobot’s integration with Apache Airflow , a popular open source orchestration tool and workflow scheduler used by more than 12,000 organizations* across industries like financial services , healthcare , retail , and manufacturing. Integrate DataRobot and Apache Airflow for Retraining and Redeploying Models.

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CIO Business Intelligence

AUGUST 7, 2023

It does not allow for integration of proprietary data and offers the fewest privacy and IP protections. In shaper use cases, CIOs need to integrate existing gen AI models with internal data and systems to work together seamlessly and generate customized results.

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IBM Big Data Hub

NOVEMBER 15, 2023

The watsonx platform, along with other IBM AI applications, libraries and APIs help partners more quickly bring AI-powered commercial software to market , reducing the need for specialized talent and developer resources. Thus, teams can work smarter and move toward better, more integrated business outcomes.

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Domino Data Lab

SEPTEMBER 20, 2022

Domino Data Lab’s Enterprise MLOps platform integrates across NVIDIA’s product line of infrastructure like NVIDIA DGX systems , NVIDIA-Certified Systems from leading OEMs, and the NVIDIA AI Enterprise software suite. We have also helped organizations like Allstate , SCOR , and Topdanmark scale their CoEs.

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DataRobot Blog

MARCH 28, 2022

DataRobot provides a Machine Learning platform that allows data scientists and citizen data scientists to quickly and efficiently prepare, build and evaluate many competing models in order to identify the optimal algorithm to solve the use case. The model can then be deployed, managed, monitored and automatically re-trained by the platform.

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DataRobot Blog

MARCH 17, 2022

release, I’m very pleased to announce that our unique MLOps capability — Continuous AI —is now available to all on-prem customers. Now, all of our MLOps customers have access to the best of both automated machine learning and machine learning operations, with a human in the loop to continually improve models over the full AI/ML lifecycle.

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CIO Business Intelligence

MAY 28, 2022

New partnerships with Oracle, Microsoft Azure and Google Cloud are highlighting Informatica’s strategy to dominate the market for data management products by offering integrations that cut down the time and complexity of data migration, management and engineering tasks. Informatica eyes data management dominance.

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CIO Business Intelligence

MAY 27, 2022

New partnerships with Oracle, Microsoft Azure and Google Cloud are highlighting Informatica’s strategy to dominate the market for data management products by offering integrations that cut down the time and complexity of data migration, management and engineering tasks. Informatica eyes data management dominance.

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DataRobot Blog

OCTOBER 18, 2022

Organizations are looking for AI platforms that drive efficiency, scalability, and best practices, trends that were very clear at Big Data & AI Toronto. Today, his team is using open-source packages without a standardized AI platform. Explore the DataRobot platform today! See DataRobot AI Cloud in Action. Request a Demo.

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DataRobot

MAY 20, 2021

Three sessions from the event sum it up best: Julian Forero and Katy Haynie from Snowflake delivered a powerhouse case for the new opportunities that the DataRobot and Snowflake integration has unlocked. Their session, Expand Your Reach with Data Cloud , explains how this integration drives AI adoption. Request a Demo.

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DataKitchen

MARCH 16, 2023

Gartner attempted to list every metric under the sun in their recent report , “T oolkit: Delivery Metrics for DataOps, Self-Service Analytics, ModelOps, and MLOps, ” published February 7, 2023. It lists forty-five metrics to track across their Operational categories: DataOps, Self-Service, ModelOps, and MLOps. Forty-five metrics!

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Domino Data Lab

JULY 28, 2021

In this article, we will provide an overview of the three overlapping components of data science, the importance of communication and collaboration, and how the Domino Data Lab MLOps platform can help improve the speed and efficiency of your team. Once data is acquired, it can then be integrated into the data science lifecycle.

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DataRobot Blog

MAY 5, 2022

DataRobot’s already market-leading AutoML, AutoTS, and MLOps products will only be able to drive more value after fully unlocking the power of data-agnostic AI. In the increasingly interoperable universe of AI/ML, plug-and-play integrations with best-in-class solutions have the power to drastically improve the efficiency of ML teams.

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IBM Big Data Hub

APRIL 28, 2022

You can enhance this by appending master data management (MDM) and MLOps capabilities to the data fabric, which creates a true end-to-end data solution accessible by every division within your enterprise. Consequently, a data fabric self-manages and automates data discovery, governance and consumption, which enables.

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Domino Data Lab

AUGUST 6, 2021

This usually involves training, but in some cases modification to the platform or the user interface may be required. Using Enterprise MLOps to Drive DSLC Adoption. Access to Domino’s Enterprise MLOps Platform is just a few clicks away. To evaluate it for yourself, register for a free 2-week trial.

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CIO Business Intelligence

MAY 16, 2022

HPE GreenLake brings the benefits of a cloud experience — specifically hardware, software, orchestration, metering, and billing — serving as a unified edge-to-cloud platform that brings end-to-end visibility to a decentralized data estate.

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Jen Stirrup

SEPTEMBER 30, 2021

Although CRISP-DM is not perfect , the CRISP-DM framework offers a pathway for machine learning using AzureML for Microsoft Data Platform professionals. What does this mean for the Microsoft Data Platform Professional? How can we can adopt a mindshift from Business Intelligence to advanced analytics using Azure ML? Data Preparation.

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AWS Big Data

AUGUST 2, 2023

Do you ever find yourself grappling with multiple defect logging mechanisms, scattered project management tools, and fragmented software development platforms? Create a resource named git-data with a POST method, integrate it with the Lambda function git-webhook-handler created in the previous step, and deploy the REST API.

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DataRobot

JUNE 9, 2021

release, DataRobot announced the release of Portable Prediction Servers, allowing organizations to bring any DataRobot model closer to their production data as well as integrate into already existing pipelines and applications. To help combat this problem, in the DataRobot 6.3 Availability. release, going live June 15, 2021.

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DataRobot

MAY 14, 2021

DataRobot’s core mission has always been to unleash the full potential of human and machine intelligence, and we strongly believe that our Augmented Intelligence platform converges the best that humans and machines have to offer. Continuous AI enables our MLOps customers to set up multiple retraining policies on their production models.

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CIO Business Intelligence

MAY 26, 2022

This is where MLOps comes in. MLOps — machine learning operations — is a set of best practices, frameworks, and tools that help companies manage data, models, deployment, monitoring, and other aspects of taking a theoretical proof-of-concept AI system and putting it to work. The evolution of MLOps.

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CIO Business Intelligence

MAY 28, 2022

This is where MLOps comes in. MLOps — machine learning operations — is a set of best practices, frameworks, and tools that help companies manage data, models, deployment, monitoring, and other aspects of taking a theoretical proof-of-concept AI system and putting it to work. The evolution of MLOps.

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DataKitchen

APRIL 13, 2021

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . 100% of your DataOps needs in one end-to-end platform. Testing and Data Observability. Sandbox Creation and Management.

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CIO Business Intelligence

FEBRUARY 28, 2024

And this doesn’t include the gen AI that’s now being embedded into platforms like Office 365, Google Docs, and Salesforce. Building enterprise-grade gen AI platforms is like shooting at a moving target, and AI progress is developing at a much faster rate than they can adapt. “It

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AWS Big Data

MARCH 30, 2023

Another option is to use AWS Step Functions , which is a serverless workflow service that integrates with EMR on EKS and EventBridge to build event-driven workflows. By using ACK controllers to create and configure different AWS services, developers can perform all data plane operations without leaving the Kubernetes platform.

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O'Reilly on Data

OCTOBER 13, 2020

Working together, this post-production development team should embrace continuous delivery principles, and prioritize the integration of any additional necessary instrumentation that was not already implemented during the model development process. Deciding what investment to make in MLOps tooling is an inherently complex task.

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Domino Data Lab

JULY 15, 2021

As new team members with varying backgrounds are added, as new sources of data are made available from different platforms, or new deliverables are required from stakeholders, allegiance to a specific camp becomes counterproductive. Integrated Development Environments (IDEs). The Domino Enterprise MLOps Platform.

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IBM Big Data Hub

JANUARY 17, 2023

Data integration. As part of a data fabric, IBM’s data integration capability creates a roadmap that helps organizations connect data from disparate data sources, build data pipelines, remediate data issues, enrich data quality, and deliver integrated data to multicloud platforms. Data science and MLOps.

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DataRobot Blog

SEPTEMBER 30, 2022

How do you track the integrity of a machine learning model in production? Tracking integrity is important: more than 84% of data scientists do not trust the model once it is in production. This is due to lack of holistic visibility into the model operations (or MLOps ) system. Model Observability can help. Drift Over Time.

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DataRobot Blog

MARCH 16, 2023

To deliver on this new approach, one that we are calling Value-Driven AI , we set out to design new and enhanced platform capabilities that enable customers to realize value faster. Today, we want to share what we learned and established as the key requirements for an AI Platform to consistently deliver value from investments in AI.

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