CIO Business Intelligence

FEBRUARY 10, 2023

Predictive analytics definition Predictive analytics is a category of data analytics aimed at making predictions about future outcomes based on historical data and analytics techniques such as statistical modeling and machine learning. Financial services: Develop credit risk models. from 2022 to 2028.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

O'Reilly on Data

DECEMBER 10, 2019

We can collect many examples of what we want the program to do and what not to do (examples of correct and incorrect behavior), label them appropriately, and train a model to perform correctly on new inputs. Nor are building data pipelines and deploying ML systems well understood. Instead, we can program by example.

Software 259

Software Machine Learning Risk Data-driven 259

CIO Business Intelligence

AUGUST 25, 2023

But things go awry and when they do, Proctor & Gamble now employs its Hot Melt Optimization platform to catch snags and get the process back on track. The project team explored several algorithms, including training neural network models, and found that the Microsoft AI Rules Engine achieved the best results,” Kietermeyer added.

Predictive Analytics 98

Predictive Analytics IoT Manufacturing Analytics 98

AWS Big Data

MAY 15, 2024

You can use this solution regularly as part of your cost-optimization efforts to safely remove unused EIPs to reduce your costs. By extracting detailed information from CloudTrail and querying it using Athena, this solution streamlines the process of data collection, analysis, and reporting of EIP usage within an AWS account.

Snapshot 86

Snapshot Optimization Data Lake Reporting 86

CIO Business Intelligence

SEPTEMBER 19, 2023

Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. 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

O'Reilly on Data

JULY 28, 2020

If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. You must detect when the model has become stale, and retrain it as necessary. The guardrail metric is a check to ensure that an AI doesn’t make a “mistake.”

Marketing 361

Marketing Experimentation Metrics Testing 361

datapine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

CIO Business Intelligence

MARCH 8, 2023

Enterprises driving toward data-first modernization need to determine the optimal multicloud strategy, starting with which applications and data are best suited to migrate to cloud and what should remain in the core and at the edge. A hybrid approach is clearly established as the optimal operating model of choice.

Manufacturing 102

Manufacturing Business Objectives Cost-Benefit Optimization 102

CIO Business Intelligence

JULY 3, 2023

Data exists in ever larger silos, but real knowledge still resides in employees. But the rise of large language models (LLMs) is starting to make true knowledge management (KM) a reality. These models can extract meaning from digital data at scale and speed beyond the capabilities of human analysts.

Management 105

Management Experimentation Modeling Enterprise 105

Cloudera

APRIL 9, 2021

The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection. The second blog dealt with creating and managing Data Enrichment pipelines. The third video in the series highlighted Reporting and Data Visualization. Data Collection – streaming data.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Rocket-Powered Data Science

JUNE 17, 2022

release enables DevSecOps users to gain more insights from Observability data with Federated Search, with the ability to correlate ops with security alerts, and with Edge Management, all in one platform. My closing thought — Cybersecurity is basically Data Analytics: detection, prediction, prescription, and optimizing for unpredictability.

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

IBM Big Data Hub

APRIL 22, 2024

The platform, created in partnership with Andel Energi in Denmark, uses IoT sensors, AI and the cloud to provide an energy ecosystem for consumers to participate in real-time, intelligent grid optimization. These models also help estimate where carbon is stored, how long it will take to degrade, and more.

IoT 80

IoT Internet of Things Cost-Benefit Reporting 80

CIO Business Intelligence

AUGUST 5, 2022

Enterprises driving toward data-first modernization need to determine the optimal multicloud strategy, starting with which applications and data are best suited to migrate to cloud and what should remain in the core and at the edge. A hybrid approach is clearly established as the optimal operating model of choice.

IT 98

IT Manufacturing Business Objectives Cost-Benefit 98

CIO Business Intelligence

NOVEMBER 1, 2023

There’s indeed a lot of hype around the latest wave of large language models (LLM) and associated tools, yet beneath the noise, there’s a whisper about how the technology will one day become indispensable. One common shortcoming of the basic setup of predictive maintenance is that rare events are underrepresented in the training data.

Enterprise 131

Enterprise Digital Transformation Modeling Interactive 131

O'Reilly on Data

NOVEMBER 13, 2018

Considerations for a world where ML models are becoming mission critical. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in New York last September. As the data community begins to deploy more machine learning (ML) models, I wanted to review some important considerations.

Machine Learning 217

Machine Learning Risk Management Statistics 217

CIO Business Intelligence

JULY 12, 2023

However, some things are common to virtually all types of manufacturing: expensive equipment and trained human operators are always required, and both the machinery and the people need to be deployed in an optimal manner to keep costs down. Moreover, lowering costs is not the only way manufacturers gain a competitive advantage. says Cretella.

Manufacturing 98

Manufacturing Cost-Benefit Data Lake Optimization 98

FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Data Analyst Job Description: Major Tasks and Duties Data analysts collaborate with management to prioritize information needs, collect and interpret business-critical data, and report findings.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

FEBRUARY 8, 2023

As a result, numerous essential concerns like data collecting and reporting, decision-making, and data optimization are being addressed. Challenges for teams include finding effective strategies for using customer data to fuel experience decisions and developing tech evaluation criteria for their organisation.

ROI 98

ROI Measurement Data Processing Strategy 98

CIO Business Intelligence

APRIL 27, 2023

At this time of dynamic business and market changes, uncertainty, and quickly evolving consumption models for IT infrastructure, every IT executive understands the benefits and necessity of network agility. We’ve seen how it can gather and organize telemetry data collected from all parts of a company’s network.

Management 98

Management Internet of Things Cost-Benefit Uncertainty 98

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Cloudera

FEBRUARY 8, 2021

The goal is to define, implement and offer a data lifecycle platform enabling and optimizing future connected and autonomous vehicle systems that would train connected vehicle AI/ML models faster with higher accuracy and delivering a lower cost.

Machine Learning 108

Machine Learning Manufacturing Unstructured Data Modeling 108

DataRobot Blog

MARCH 8, 2023

Every modern enterprise has a unique set of business data collected as part of their sales, operations, and management processes. Additionally, DataRobot data scientists and support teams have a proven record of success working with thousands of customers on tens of thousands of AI use cases across a wide range of industries.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

CIO Business Intelligence

APRIL 1, 2022

“There is no need to pre-process data, train or hypertune machine learning models, nor load balance or manually provision your infrastructure to handle unpredictable traffic spikes. These are machine learning algorithms; the more data collected the better the results,” she said. We do it all for you automatically.”.

IT 111

IT Machine Learning Cost-Benefit Data Collection 111

CIO Business Intelligence

JUNE 5, 2023

They are connected industrial and Internet of Things (IoT) experiences that drive optimization of operational productivity and flexibility without compromising security. In manufacturing and supply chain operations, a unified experience can facilitate real-time data collection, inventory management, and logistics tracking.

Internet of Things 97

Internet of Things Cost-Benefit Manufacturing IoT 97

IBM Big Data Hub

FEBRUARY 23, 2024

DL models can improve over time through further training and exposure to more data. When a user sends a message, the system uses NLP to parse and understand the input, often by using DL models to grasp the nuances and intent. Marketing and sales: Conversational AI has become an invaluable tool for data collection.

Enterprise 100

Enterprise Interactive Data-driven Key Performance Indicator 100

IBM Big Data Hub

FEBRUARY 7, 2024

2 For example, some are turning to software solutions that can more easily capture, manage and report ESG data. Circular economy: When waste is a resource Waste not, want not: the circular economy model, which aims to minimize unnecessary waste and make the most of resources, is booming. trillion in economic benefits by 2030.

Reporting 93

Reporting Internet of Things Cost-Benefit Data-driven 93

AWS Big Data

JULY 13, 2023

Vega Cloud’s platform is based on the FinOps Foundation’s best practices and removes the confusion behind the business value of cloud services and accelerates strategic decisions while maintaining cost optimization. The AWS pay-as-you-go pricing model allowed Vega Cloud to hit the ground running and scale with real-time demand.

Cost-Benefit 82

Cost-Benefit Dashboards Optimization Visualization 82

CIO Business Intelligence

APRIL 29, 2022

In this new era the role of humans in the development process also changes as they morph from being software programmers to becoming ‘data producers’ and ‘data curators’ – tasked with ensuring the quality of the input. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’

Data Governance 145

Data Governance IT Risk Data Lake 145

Smart Data Collective

APRIL 20, 2022

Companies that utilize data analytics to make the most of their business model will have an easier time succeeding with Amazon. One of the best ways to create a profitable business model with Amazon involves using data analytics to optimize your PPC marketing strategy.

Data Quality 115

Data Quality Analytics Testing Sales 115

Smart Data Collective

APRIL 5, 2022

Companies working on AI technology can use it to improve scalability and optimize the decision-making process. This feature helps automate many parts of the data preparation and data model development process. This significantly reduces the amount of time needed to engage in data science tasks. Neptune.ai.

Cost-Benefit 123

Cost-Benefit Machine Learning Data Science Unstructured Data 123

O'Reilly on Data

JUNE 18, 2019

There has been a significant increase in our ability to build complex AI models for predictions, classifications, and various analytics tasks, and there’s an abundance of (fairly easy-to-use) tools that allow data scientists and analysts to provision complex models within days. Data integration and cleaning.

Machine Learning 255

Machine Learning Data Quality Statistics Modeling 255

IBM Big Data Hub

FEBRUARY 14, 2024

Other uses include Netflix offering viewing recommendations powered by models that process data sets collected from viewing history; LinkedIn uses ML to filter items in a newsfeed, making employment recommendations and suggestions on who to connect with; and Spotify uses ML models to generate its song recommendations.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

CIO Business Intelligence

JANUARY 9, 2023

What they found—an innovative way to model healthcare data—is saving the company an estimated $150M annually and enabling its medical professionals to provide accurate and effective care path recommendations in real time. Graphs can make previously unavailable connections from disparate data spread across many different platforms.

Analytics 104

Analytics Cost-Benefit Visualization Risk 104

IBM Big Data Hub

SEPTEMBER 20, 2023

The new wave of AI, with foundational models provided by generative AI, could represent the new major opportunity to put AI to work for governments. For example, public sector agencies can make better use of data by migrating certain technology systems to the cloud and infuse it with AI.

Cost-Benefit 105

Cost-Benefit Digital Transformation Technology Modeling 105

Insight

MARCH 27, 2019

DeepAugment is an AutoML tool focusing on data augmentation. It utilizes Bayesian optimization for discovering data augmentation strategies tailored to your image dataset. Introduction Data is the most critical piece of AI applications. Collecting additional data is not always possible and can be expensive.

Optimization 75

Optimization Cost-Benefit Modeling Strategy 75

IBM Big Data Hub

MAY 26, 2023

Cloud computing offers the potential to redefine and personalize customer relationships, transform and optimize operations, improve governance and transparency, and expand business agility and capability. Leading life science companies are leveraging cloud for innovation around operational, revenue and business models.

Consulting 77

Consulting Cost-Benefit Optimization Machine Learning 77