Cloudera

MAY 9, 2024

In fact, Gartner predicts the AI software market will grow from $124 billion in 2022 to $297 billion in 2027. First, we need to help customers get AI models based on trusted data into production faster than ever. Let’s take a deeper dive into how these capabilities accelerate your AI initiatives and support data democratization.

Dashboards 70

Dashboards Machine Learning Data-driven Visualization 70

O'Reilly on Data

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. Identifying the problem. Agreeing on metrics.

Marketing 362

Marketing Experimentation Metrics Testing 362

AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. In previous posts, we demonstrated how you can use the automatic model training capability of Redshift ML to train classification and regression models.

Modeling 101

Modeling Data Warehouse Machine Learning Recreation/Entertainment 101

CIO Business Intelligence

MAY 15, 2024

If Act One of digital transformation was building applications—for example, building omnichannel customer experiences—then Act Two is adding GenAI. Its core capability—using large language models (LLMs) to create content, whether it’s code or conversations—can introduce a whole new layer of engagement for organizations.

Cost-Benefit 76

Cost-Benefit Risk Modeling Digital Transformation 76

O'Reilly on Data

MAY 14, 2020

This role includes everything a traditional PM does, but also requires an operational understanding of machine learning software development, along with a realistic view of its capabilities and limitations. Whether or not that’s how your organization works, every AI PM must consider how their products relate to these phases.

Management 363

Management Experimentation B2B Machine Learning 363

CIO Business Intelligence

JUNE 14, 2023

Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications. If you’re looking to get an edge on a data analytics career, certification is a great option.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

IBM Big Data Hub

NOVEMBER 29, 2023

As all businesses strive to adopt a best-in-class approach for AI tools, let’s discuss best practices for how your company can leverage AI to enhance your real-time event processing use cases. AI and event processing: a two-way street An event-driven architecture is essential for accelerating the speed of business.

Unstructured Data 90

Unstructured Data Data-driven ROI Machine Learning 90

IBM Big Data Hub

APRIL 18, 2024

Imagine a world where machines aren’t confined to pre-programmed tasks but operate with human-like autonomy and competence. AGI, sometimes referred to as strong AI , is the science-fiction version of artificial intelligence (AI), where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility.

Cost-Benefit 94

Cost-Benefit Modeling Manufacturing Interactive 94

CIO Business Intelligence

MAY 1, 2024

Gen AI takes us from single-use models of machine learning (ML) to AI tools that promise to be a platform with uses in many areas, but you still need to validate they’re appropriate for the problems you want solved, and that your users know how to use gen AI effectively.

Cost-Benefit 142

Cost-Benefit Metrics Insurance Measurement 142

IBM Big Data Hub

NOVEMBER 29, 2023

With the emergence of new advances and applications in machine learning models and artificial intelligence, including generative AI, generative adversarial networks, computer vision and transformers, many businesses are seeking to address their most pressing real-world data challenges using both types of synthetic data: structured and unstructured.

Metrics 86

Metrics Machine Learning Risk Statistics 86

AWS Big Data

MARCH 21, 2024

However, it can be challenging to set up a Kafka cluster along with other data processing components that scale automatically depending on your application’s needs. In this post, we explain how you can use some of these services, including MSK Serverless , to build a serverless data platform to meet your real-time needs.

Data Lake 100

Data Lake Management Modeling Optimization 100

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Place?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

DataRobot Blog

AUGUST 3, 2022

How can you save time in understanding the impact of language when working with text in ML models ? With tens of thousands of Text AI projects, DataRobot has helped organizations unlock insights from text and generate predictions with text models—from assisting with customer support ticket triage to predicting real estate sale prices.

Machine Learning 105

Machine Learning Optimization Deep Learning Modeling 105

Rocket-Powered Data Science

OCTOBER 16, 2020

First, we heard how Big Data, Data Science, Machine Learning (ML) and Advanced Analytics would have the honor to be the technologies that would cure cancer, end world hunger and solve the world’s biggest challenges. We build models to test our understanding, but these models are not “one and done.”

Digital Transformation 142

Digital Transformation Experimentation Data Strategy Strategy 142

Cloudera

NOVEMBER 19, 2021

We are excited by the endless possibilities of machine learning (ML). We recognise that experimentation is an important component of any enterprise machine learning practice. Organizations need to usher their ML models out of the lab (i.e., COPML accounts for the fact that true production machine learning (i.e.,

Machine Learning 120

Machine Learning Modeling Experimentation IT 120

DataRobot

NOVEMBER 1, 2021

Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions. How disruptive would it be?

Machine Learning 98

Machine Learning Manufacturing Predictive Modeling Optimization 98

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

IBM Big Data Hub

APRIL 22, 2024

Sustainability strategy, data and reporting Using data and AI to drive your sustainability strategy while meeting reporting requirements In speaking with our clients around the world, we found that sustainability remains a priority on their agendas. This Earth Day, we are calling for action to conserve our scarcest resource: the planet.

IoT 83

IoT Internet of Things Cost-Benefit Reporting 83

IBM Big Data Hub

FEBRUARY 13, 2024

Remember how cool it felt when you first held a smartphone in your hand? Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Automate tedious, repetitive tasks.

Enterprise 123

Enterprise Modeling Testing Data-driven 123

DataRobot

JULY 16, 2021

The first is trust in the performance of your AI/machine learning model. The second is trust in the operations of your AI system. The third is trust in the ethics of your workflow, both to design the AI system and how it is used to inform your business process. How large is the data set?

Machine Learning 98

Machine Learning Uncertainty Modeling Measurement 98

IBM Big Data Hub

FEBRUARY 23, 2024

NLP translates the user’s words into machine actions, enabling machines to understand and respond to customer inquiries accurately. Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development.

Enterprise 103

Enterprise Interactive Data-driven Key Performance Indicator 103

Smart Data Collective

SEPTEMBER 24, 2021

Machine Learning is a branch of Artificial Intelligence that works by giving computers the ability to learn without being explicitly programmed. As technology advances, machine learning will have more opportunities to help businesses engage with their customers and improve the overall customer experience.

Machine Learning 122

Machine Learning Marketing Modeling Sales 122

CIO Business Intelligence

MAY 12, 2022

Predictive analysis tools have an answer. But sometimes can often be more than enough if the prediction can help your enterprise plan better, spend more wisely, and deliver more prescient service for your customers. What are predictive analytics tools? Top predictive analytics tools compared. Are they right?

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

SEPTEMBER 19, 2023

To gain a better understanding of how companies are putting AI to practical use, consultancy Deloitte surveyed 2,620 global business leaders, across 13 countries, as part of its Fueling the AI Transformation report. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand.

Enterprise 141

Enterprise Cost-Benefit Optimization Deep Learning 141

CIO Business Intelligence

OCTOBER 5, 2023

As chief digital and technology officer at CBRE, Davé recognized early that the commercial real estate industry was ripe for AI and machine learning enhancements, and he and his team have tested countless use cases across the enterprise ever since. And those experiments have paid off.

Experimentation 125

Experimentation Strategy Machine Learning Interactive 125

CIO Business Intelligence

JUNE 25, 2023

After being “awed” by OpenAI’s GPT model acing the AP Bio exam, the model was asked a non-technical question: “What do you say to a father with a sick child?” Fine-tuning models that run “on top” of foundation models requires less data, costs less, and can be completed quickly. This metaphor can help on two fronts.

Finance 108

Finance Uncertainty Strategy Modeling 108

IBM Big Data Hub

DECEMBER 5, 2023

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications. trillion on retail businesses through 2029. trillion in that year.

Unstructured Data 94

Unstructured Data Cost-Benefit Experimentation Machine Learning 94

AWS Big Data

AUGUST 7, 2023

Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift. With Redshift ML, you can take advantage of Amazon SageMaker , a fully managed ML service, without learning new tools or languages.

Forecasting 86

Forecasting Data Warehouse Machine Learning Modeling 86

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects.

Machine Learning 136

Machine Learning Data Science Data Lake Modeling 136

CIO Business Intelligence

FEBRUARY 14, 2023

To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making. DataStax Real-time data and decisioning First, a few quick definitions. Improved recommendations for online transactions.

Data Strategy 114

Data Strategy Strategy Machine Learning Data-driven 114

IBM Big Data Hub

APRIL 13, 2023

After developing a machine learning model, you need a place to run your model and serve predictions. If your company is in the early stage of its AI journey or has budget constraints, you may struggle to find a deployment system for your model.

Modeling 88

Modeling Statistics Machine Learning Testing 88

CIO Business Intelligence

MAY 26, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. Is there a model that can provide the necessary results? How can it be built? How can it be trained? This is where MLOps comes in. The evolution of MLOps.

Machine Learning 144

Machine Learning Modeling Data-driven Dashboards 144

CIO Business Intelligence

APRIL 12, 2022

Slowdowns caused by system disruption and complexities in your IT environment are more than an operational headache. It comes down to how much time individual stakeholders spend on reactive vs. proactive tasks. AI-powered operations – or AIOps – can change the value of time for your business. Proactive time builds momentum.

Digital Transformation 144

Digital Transformation B2B Enterprise IoT 144

CIO Business Intelligence

JANUARY 2, 2024

In 2024, these pressures will drive businesses increasingly to ask: How can I increase sales without raising overhead? How can I create year-round stability for sourcing, inventory, restocking, and order management? Retailers that embrace AI will be the first to achieve higher sales and better brand connections, now and in the future.

Sales 120

Sales Advertising Key Performance Indicator Optimization 120

CIO Business Intelligence

MAY 28, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. Is there a model that can provide the necessary results? How can it be built? How can it be trained? This is where MLOps comes in. The evolution of MLOps.

Machine Learning 134

Machine Learning Modeling Data-driven Dashboards 134

DataRobot

DECEMBER 20, 2021

We collect more and more diverse data types, and we’re not always sure how we can turn this data into real value. Image recognition is one of the most relevant areas of machine learning. Image recognition is one of the most relevant areas of machine learning. Deep learning makes the process efficient.

Visualization 97

Visualization Deep Learning Machine Learning Modeling 97

Cloudera

OCTOBER 29, 2020

Over the past months, we’ve been busy innovating and optimizing how teams across the lifecycle work together. DV gives everyone across the data lifecycle the ability to present data analytics and machine learning models in meaningful ways. Accelerate Collaboration Across The Lifecycle.

Visualization 106

Visualization Machine Learning Dashboards Data Warehouse 106