CIO Business Intelligence

APRIL 25, 2022

Enterprises are betting big on machine learning (ML). According to IDC , 85% of the world’s largest organizations will be using artificial intelligence (AI) — including machine learning (ML), natural language processing (NLP) and pattern recognition — by 2026. So how can enterprises overcome these challenges?

Machine Learning 134

Machine Learning Enterprise Deep Learning Cost-Benefit 134

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 81

Metrics Machine Learning Statistics Risk 81

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. Machine learning adds uncertainty.

Management 333

Management Machine Learning Experimentation Metrics 333

CIO Business Intelligence

JUNE 1, 2022

These supercomputers power exciting innovations in deep learning, disease control, and physics—think bionic eyes, DNA sequencing for infectious disease research, and the study of time crystals. . CSIRO’s Bracewell Delivers Deep Learning, Bionic Vision. Ready to evolve your analytics strategy or improve your data quality?

Deep Learning 104

Deep Learning Snapshot Optimization Data Quality 104

CIO Business Intelligence

MARCH 9, 2022

Taking this a step further, organizations can achieve the holy grail of hybrid cloud with applications and data that can be moved, managed and secured seamlessly across locations to provide the best of both worlds. Cloudera and Dell Technologies for More Data Insights. Just starting out with analytics?

Data-driven 108

Data-driven Analytics Machine Learning Optimization 108

CIO Business Intelligence

JUNE 21, 2022

Real-time big data analytics, deep learning, and modeling and simulation are newer uses of HPC that governments are embracing for a variety of applications. Big data analytics is being used to uncover crimes. Deep learning, together with machine learning, is able to detect cyber threats faster and more efficiently. .

Deep Learning 109

Deep Learning Big Data ROI Software 109

CIO Business Intelligence

JUNE 7, 2022

But only in recent years, with the growth of the web, cloud computing, hyperscale data centers, machine learning, neural networks, deep learning, and powerful servers with blazing fast processors, has it been possible for NLP algorithms to thrive in business environments. Just starting out with analytics?

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Products based on deep learning can be difficult (or even impossible) to develop; it’s a classic “high return versus high risk” situation, in which it is inherently difficult to calculate return on investment.

Marketing 362

Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

JUNE 1, 2022

Racing car design innovation and racing strategy are now dominated by what McLaren engineers call condition-based insights derived from real-time data feeds from hundreds of sensors in cars and the use of digital twins ? and artificial intelligence (AI) and machine learning (ML) technologies. . Just starting out with analytics?

Manufacturing 116

Manufacturing Digital Transformation Predictive Analytics Strategy 116

datapine

AUGUST 14, 2019

Data science tools are used for drilling down into complex data by extracting, processing, and analyzing structured or unstructured data to effectively generate useful information while combining computer science, statistics, predictive analytics, and deep learning. Our Top Data Science Tools.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

CIO Business Intelligence

APRIL 6, 2022

By giving leadership at all levels more timely access to critical data about business operations, businesses can see more of their options, make and automate better decisions, and further improve efficiency to drive higher customer satisfaction and profitability. Ready to evolve your analytics strategy or improve your data quality?

Data mining 70

Data mining Deep Learning Insurance Digital Transformation 70

CIO Business Intelligence

APRIL 11, 2022

The smart city solution incorporates video and sound data inputs from the area, integrated with publicly available, historical data sources, such as crime, weather and social media data. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

IoT 145

IoT Measurement Cost-Benefit Deep Learning 145

CIO Business Intelligence

MARCH 14, 2022

It is also the foundation of predictive analysis, artificial intelligence (AI), and machine learning (ML). Real-time Data Scaling Challenges. Several factors make such scaling difficult: Massive Data Growth: Global data creation is projected to exceed 180 zettabytes by 2025. Just starting out with analytics?

Data Processing 113

Data Processing Optimization Deep Learning Software 113

CIO Business Intelligence

APRIL 11, 2022

Using artificial intelligence (AI) and machine learning, more than 1.9 Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Ready to evolve your analytics strategy or improve your data quality?

Deep Learning 57

Deep Learning Strategy Risk Data Quality 57

CIO Business Intelligence

JANUARY 4, 2023

Moving forward, we will see workflows that are more capable and widely adopted to facilitate edge-core-cloud needs like generating meshes, performing 3D simulations, performing post-simulation data analysis, and feeding data into machine learning models—which support, guide, and in some case replace the need for simulation.

Cost-Benefit 57

Cost-Benefit Machine Learning Modeling Uncertainty 57

Smart Data Collective

AUGUST 26, 2021

Deep learning technology is changing the future of small businesses around the world. A growing number of small businesses are using deep learning technology to address some of their most pressing challenges. New advances in deep learning are integrated into various accounting algorithms.

Deep Learning 95

Deep Learning Finance Cost-Benefit Advertising 95

Sisense

APRIL 15, 2021

Augmented analytics (according to Gartner, which would know), uses technologies “such as machine learning [ML] and AI to assist with data preparation, insight generation, and insight explanation to augment how people explore and analyze data in analytics and BI platforms.” Tools of the AI trade.

Analytics 98

Analytics Data Science Modeling Machine Learning 98

CIO Business Intelligence

APRIL 4, 2022

Their legacy databases could not analyze the volumes of data fast enough to block fraudulent activities without negatively impacting their responsiveness. . Deep link analytics combined with real-time analysis and machine learning provide a robust platform for detecting and preventing fraud.

Technology 52

Technology Deep Learning Cost-Benefit Data Quality 52

Cloudera

NOVEMBER 15, 2021

Here we briefly describe some of the challenges that data poses to AI. Data annotation. Abundance of data has been one of the main facilitators of the AI boom of the last decade. Deep Learning, a subset of AI algorithms, typically requires large amounts of human annotated data to be useful. Data curation.

Unstructured Data 93

Unstructured Data Recreation/Entertainment Structured Data Reporting 93

CIO Business Intelligence

MAY 16, 2022

The data gathered from cameras and sensors as part of a computer vision system, along with machine learning, make it easier to find missing persons and to identify people who are not allowed to be in a venue. Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics?

Recreation/Entertainment 102

Recreation/Entertainment Broadcasting Cost-Benefit Advertising 102

DataRobot Blog

MAY 26, 2022

Validating Modern Machine Learning (ML) Methods Prior to Productionization. Validating Machine Learning Models. Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution.

Risk 52

Risk Modeling Metrics Business Objectives 52

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. .

Testing 300

Testing Machine Learning Consulting Data Quality 300

O'Reilly on Data

JUNE 19, 2019

A look at the landscape of tools for building and deploying robust, production-ready machine learning models. Our surveys over the past couple of years have shown growing interest in machine learning (ML) among organizations from diverse industries. Why aren’t traditional software tools sufficient?

Modeling 193

Modeling Machine Learning Testing Metrics 193

Smarten

APRIL 19, 2024

The value of an AI-focused analytics solution can only be fully realized when a business has ensured data quality and integration of data sources, so it will be important for businesses to choose an analytics solution and service provider that can help them achieve these goals.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

Cloudera

OCTOBER 1, 2022

These companies face a unique set of data governance challenges regarding infrastructure and compliance on local, national, and international levels. Some organizations are choosing to confront these challenges with the help of tools like machine learning (ML) and artificial intelligence (AI) to automate, streamline, and scale compliance. .

Data Governance 77

Data Governance Strategy Enterprise Machine Learning 77

AWS Big Data

MARCH 1, 2023

The inability to accurately find and analyze data from disparate sources represents a potential efficiency killer for everyone from data scientists, medical researchers, academics, to financial and government analysts. Taylor McNally is a Deep Learning Architect at Amazon Machine Learning Solutions Lab.

Data Lake 86

Data Lake Deep Learning Modeling Interactive 86

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. Be aware that machine learning often involves working on something that isn’t guaranteed to work.

Management 110

Management Machine Learning Experimentation Metrics 110

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 117

Data Lake Unstructured Data Data Warehouse Data Quality 117

Ontotext

MAY 22, 2023

This is the case with the so-called intelligent data processing (IDP), which uses a previous generation of machine learning. Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

DataRobot Blog

DECEMBER 15, 2022

AI-powered Time Series Forecasting may be the most powerful aspect of machine learning available today. By simplifying Time Series Forecasting models and accelerating the AI lifecycle, DataRobot can centralize collaboration across the business—especially data science and IT teams—and maximize ROI. AI Experience 2022 Recordings.

Forecasting 81

Forecasting Modeling ROI Machine Learning 81

CIO Business Intelligence

JANUARY 31, 2023

These changes bring new challenges, but advancements in IT automation, artificial intelligence (AI) and machine learning (ML), and edge-computing capabilities will play a key role. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

Deep Learning 109

Deep Learning Cost-Benefit Data-driven Manufacturing 109

CIO Business Intelligence

APRIL 12, 2022

In addition, safety is a key requirement across rail, water, air, and roadways, often requiring split-second decisions that can often be enhanced by machine learning. Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI).

IT 70

IT Cost-Benefit IoT Machine Learning 70

CIO Business Intelligence

MARCH 22, 2022

Business units can bring in their own data, and access the superset of data aggregated from all the other different sources. . Becoming data-driven and automating with AI and machine learning (ML) algorithms can seem overwhelming. Ready to evolve your analytics strategy or improve your data quality?

Analytics 113

Analytics Key Performance Indicator Data Warehouse Data-driven 113

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

DataRobot Blog

DECEMBER 20, 2022

DataRobot combines these datasets and data types into one training dataset used to build machine learning models. You can understand the data and model’s behavior at any time. Activation Maps allows DataRobot users to see which part of various images the machine learning model is using for making predictions.

Management 59

Management Machine Learning Optimization Modeling 59

CIO Business Intelligence

MAY 30, 2024

It has been around since the 1950s with machine learning. Using data and algorithms to imitate the way humans learn came into the scene in the 1980s, and this further evolved to deep learning in the 2000s. Data quality is the cornerstone of effective AI deployment.

Data Quality 103

Data Quality Key Performance Indicator Digital Transformation Management 103