Cloudera

JANUARY 9, 2025

As the AI landscape evolves from experiments into strategic, enterprise-wide initiatives, its clear that our naming should reflect that shift. Thats why were moving from Cloudera Machine Learning to Cloudera AI. This isnt just a new label or even AI washing. Decades ago, it was a moonshot idea, and progress often stalled.

Machine Learning 85

Machine Learning Enterprise Data-driven Modeling 85

Cloudera

JANUARY 7, 2025

As enterprises navigate complex data-driven transformations, hybrid and multi-cloud models offer unmatched flexibility and resilience. Heres a deep dive into why and how enterprises master multi-cloud deployments to enhance their data and AI initiatives. The terms hybrid and multi-cloud are often used interchangeably.

Cost-Benefit 82

Cost-Benefit Optimization Strategy Data-driven 82

O'Reilly on Data

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. There was a lot of uncertainty about stability, particularly at smaller companies: Would the company’s business model continue to be effective? Would your job still be there in a year? Executive Summary.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

Domino Data Lab

AUGUST 6, 2021

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards.

Machine Learning 145

Machine Learning Modeling Testing Data Science 145

DataKitchen

JANUARY 2, 2021

In fact, only 1 in 10 organizations are able to get 75% or more of their AI prototypes into production and it takes 9 months on average to do so. In this report, Gartner outlines recommendations to effectively operationalize AI solutions that involve the core management competencies of ModelOps, DataOps, and DevOps.

Testing 130

Testing Machine Learning Reporting Modeling 130

Cloudera

OCTOBER 23, 2024

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI. It is a critical feature for delivering unified access to data in distributed, multi-engine architectures.

Metadata 84

Metadata Data Lake Dashboards Interactive 84

Cloudera

DECEMBER 17, 2024

Since 5G networks began rolling out commercially in 2019, telecom carriers have faced a wide range of new challenges: managing high-velocity workloads, reducing infrastructure costs, and adopting AI and automation. As with many industries, the future of telecommunications lies in AI and automation.

Enterprise 62

Enterprise Data Architecture Data-driven Optimization 62

datapine

NOVEMBER 19, 2019

The modern world is changing more and more quickly with each passing year. If you don’t pay attention to new changes or keep up the pace, it’s easy to fall behind the times (and the market) while other companies beat you to the punch. The solution? To keep abreast of current changes – at least at a level of basic understanding. Computer Vision.

Technology 279

Technology Internet of Things IT IoT 279

DataRobot Blog

SEPTEMBER 1, 2022

The latest McKinsey Global Survey on AI proves that AI adoption continues to grow and that the benefits remain significant. At the same time, AI remains complex and out of reach for many. For example, a recent IDC study 1 shows that it takes about 290 days on average to deploy a model into production from start to finish.

Metrics 145

Metrics Statistics Modeling Data Science 145

CIO Business Intelligence

JUNE 12, 2024

To help alleviate the complexity and extract insights, the foundation, using different AI models, is building an analytics layer on top of this database, having partnered with DataBricks and DataRobot. Some of the models are traditional machine learning (ML), and some, LaRovere says, are gen AI, including the new multi-modal advances.

Modeling 140

Modeling Testing Cost-Benefit Metadata 140

Cloudera

FEBRUARY 11, 2022

In recent years, Ethical AI has become an area of increased importance to organisations. Advances in the development and application of Machine Learning (ML) and Deep Learning (DL) algorithms, require greater care to ensure that the ethics embedded in previous rule-based systems are not lost. What is A Machine Learning Model .

Machine Learning 97

Machine Learning Sales Data Science Deep Learning 97

IBM Big Data Hub

DECEMBER 16, 2022

Over the last week, millions of people around the world have interacted with OpenAI’s ChatGPT, which represents a significant advance for generative artificial intelligence (AI) and the foundation models that underpin many of these use cases. We’re at an exciting inflection point for AI. The potential is vast.

Uncertainty 112

Uncertainty Metadata Modeling Data Collection 112

Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines. Security & Governance.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

DataRobot Blog

MARCH 16, 2023

One of the most common challenges today in the adoption of AI is that far too many projects do not complete and fail to deliver clear business outcomes. In speaking with hundreds of our customers over the past year, and analyzing projects further, we quickly realized that a new approach to AI was needed.

Experimentation 98

Experimentation Data-driven Modeling Metadata 98

CIO Business Intelligence

FEBRUARY 14, 2023

Titanium Intelligent Solutions, a global SaaS IoT organization, even saved one customer over 15% in energy costs across 50 distribution centers , thanks in large part to AI. Here, I’ll focus on why these three elements and capabilities are fundamental building blocks of a data ecosystem that can support real-time AI.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

Cloudera

AUGUST 20, 2020

Machine Learning (ML) and Artificial Intelligence (AI), while still emerging technologies inside of enterprise organisations, have given some companies the ability to dynamically change their fortunes and reshape the way they are doing business — that is if they are brave enough to experiment and explore the unknown.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

Cloudera

MAY 27, 2021

This blog post was written by Pedro Pereira as a guest author for Cloudera. . An authoritarian regime is manipulating an artificial intelligence (AI) system to spy on technology users. Big data and AI amplify the problem. “If It’s important to be conscious of this reality when creating algorithms and training models.

Machine Learning 119

Machine Learning Big Data Consulting Technology 119

DataRobot

NOVEMBER 16, 2021

Many organizations, including state and local governments, are dipping their toes into machine learning (ML) and artificial intelligence (AI). As we’ve discussed in this blog series, some are already reaping the rewards of AI through increased productivity, cost savings, etc. What is MLOps? Issues with Deployment.

Cost-Benefit 98

Cost-Benefit Machine Learning Modeling Data Processing 98

DataRobot Blog

MARCH 8, 2023

Leveraging DataRobot’s JDBC connectors, enterprise teams can work together to train ML models on their data residing in SAP HANA Cloud and SAP Data Warehouse Cloud, as well as have an option to enrich it with data from external data sources. Tune in to learn more. Registration is free for both events.

Enterprise 105

Enterprise Experimentation Machine Learning Data Science 105

Cloudera

JULY 15, 2021

Some of the key points raised during this session included: Pandemic Resiliency and Opportunities to Improve. Low Probability, High Impact Events Readiness. AI and ML’s current State of Play. Modeling that was previously well established – for both commercial and consumer lines – became less reliable.

Risk 100

Risk Optimization Management Insurance 100

Cloudera

AUGUST 17, 2022

CDP One is a new service from Cloudera that is the first data lakehouse SaaS offering with cloud compute, cloud storage, machine learning (ML), streaming analytics, and enterprise grade security built-in. What if you could access all your data and execute all your analytics in one workflow, quickly with only a small IT team?

Analytics 116

Analytics Data-driven Machine Learning Data Science 116

Cloudera

DECEMBER 3, 2021

In part 1 of this blog post, we discussed the need to be mindful of data bias and the resulting consequences when certain parameters are skewed. In 2019, the Gradient institute published a white paper outlining the practical challenges for Ethical AI. An AI system trained on data has no context outside of that data.

Uncertainty 102

Uncertainty Measurement Metrics Risk 102

CIO Business Intelligence

SEPTEMBER 21, 2023

The advent of gen AI changed everything, and the pace of that change is like nothing we’ve seen before. According to McKinsey, gen AI is poised to add up to an annual $4.4 Today’s foundational models are jacks-of-all-trades. But there’s also the downside: the possibility gen AI will take companies down. Everyone wants it.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

CIO Business Intelligence

OCTOBER 13, 2023

Generative AI is quickly changing the landscape of the business world, with rapid adoption rates across nearly every industry. Businesses are turning to gen AI to streamline business processes, develop proprietary AI technology, and reduce manual efforts in order to free up employees to take on more intensive tasks.

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Cloudera

FEBRUARY 8, 2021

The digital revolution is making a deep impact on the automotive industry, offering practically unlimited possibilities for more efficient, convenient, and safe driving and travel experiences in connected vehicles. billion in 2019, and is projected to reach $225.16 billion by 2027, registering a CAGR of 17.1% from 2020 to 2027.

Machine Learning 108

Machine Learning Manufacturing Unstructured Data Data Collection 108

IBM Big Data Hub

OCTOBER 4, 2022

It is well known that Artificial Intelligence (AI) has progressed, moving past the era of experimentation. Today, AI presents an enormous opportunity to turn data into insights and actions, to amplify human capabilities, decrease risk and increase ROI by achieving break through innovations. IBM Global AI Adoption Index 2022.).

Metadata 97

Metadata Risk Management Risk Experimentation 97

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

erwin

DECEMBER 13, 2018

This past year witnessed a data governance awakening – or as the Wall Street Journal called it, a “global data governance reckoning.” So what’s on the horizon for data governance in the year ahead? We’re making the following data governance predictions for 2019: Top 10 Data Governance Predictions for 2019.

Data Governance 91

Data Governance IoT Internet of Things Data-driven 91

Cloudera

JUNE 12, 2024

Of all of the emerging tech of the last two decades, artificial intelligence (AI) is tipping the hype scale, causing organizations from all industries to rethink their digital transformation initiatives asking where it fits in. In truth, the question is usually framed more like, “How are my competitors using AI and GenAI?”

Finance 77

Finance Risk Management Risk Data-driven 77

IBM Big Data Hub

MAY 9, 2023

Today is a revolutionary moment for Artificial Intelligence (AI). After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. The answer is that generative AI leverages recent advances in foundation models.

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

DataRobot Blog

APRIL 29, 2022

With the big data revolution of recent years, predictive models are being rapidly integrated into more and more business processes. When business decisions are made based on bad models, the consequences can be severe. As machine learning advances globally, we can only expect the focus on model risk to continue to increase.

Risk 111

Risk Modeling IT Risk Management 111

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. Data quality is a very typical use case for data governance. For data modelers, value arose from spending less time finding data and more time modeling data.

Data Governance 94

Data Governance Metadata Data Quality Enterprise 94

Cloudera

OCTOBER 11, 2022

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. The article goes on to share insights from experts at Gartner, PwC, John Deere, and Cloudera that shine a light on the critical role that data plays in scaling AI. . This excerpt from the article sums it up:

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

Cloudera

JUNE 6, 2024

This recognition underscores the importance of trusted data when building AI and generative AI (GenAI) models and serves as a testament to the impact that reliable data can have in real world use cases. trillion to US$4.4 trillion to US$4.4

Contextual Data 83

Contextual Data Data Lake Data-driven Risk 83

AWS Big Data

AUGUST 19, 2024

By using AWS Glue to integrate data from Snowflake, Amazon S3, and SaaS applications, organizations can unlock new opportunities in generative artificial intelligence (AI) , machine learning (ML) , business intelligence (BI) , and self-service analytics or feed data to underlying applications.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

Cloudera

APRIL 1, 2024

This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Cloudera

DECEMBER 19, 2023

Earlier this month, I had the opportunity to lead a roundtable discussion at the PSN Government Innovation show ( 2023 Government Innovation Show – Federal – Public Sector Network ) in Washington, DC. As also expected, most had experimented on their own with large language models (LLM) and image generators.

Optimization 91

Optimization Cost-Benefit Unstructured Data Risk 91