Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Examples: (1-3) All those applications shown in the definition of Machine Learning. (4)

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Digital Transformation 110

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 110

CIO Business Intelligence

JULY 5, 2022

BI focuses on descriptive analytics, data collection, data storage, knowledge management, and data analysis to evaluate past business data and better understand currently known information. Whereas BI studies historical data to guide business decision-making, business analytics is about looking forward.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Smart Data Collective

AUGUST 2, 2022

This figure is expected to grow as more companies recognize the potential and decide to increase the resources they dedicate to machine learning and predictive analytics tools. They have also used machine learning to automate the transportation of important materials. Big data.

Software 141

Software Machine Learning B2B Manufacturing 141

datapine

NOVEMBER 19, 2019

An important part of artificial intelligence comprises machine learning, and more specifically deep learning – that trend promises more powerful and fast machine learning. An exemplary application of this trend would be Artificial Neural Networks (ANN) – the predictive analytics method of analyzing data.

Technology 279

Technology Internet of Things IT IoT 279

Cloudera

FEBRUARY 8, 2021

To accomplish this, ECC is leveraging the Cloudera Data Platform (CDP) to predict events and to have a top-down view of the car’s manufacturing process within its factories located across the globe. . Having completed the Data Collection step in the previous blog, ECC’s next step in the data lifecycle is Data Enrichment.

Manufacturing 118

Manufacturing Data Warehouse Sales Predictive Analytics 118

Smart Data Collective

APRIL 22, 2020

This moment in history is unlike any other — and the value of data in ending it resembles nothing we’ve yet seen. Combining the coronavirus and big data may prove just how valuable artificial intelligence and other major technologies can be. This process is known as drug-target interaction (DTI) prediction.

Big Data 140

Big Data Machine Learning Risk Interactive 140

DataRobot Blog

MARCH 8, 2023

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

Enterprise 105

Enterprise Experimentation Machine Learning Data Science 105

Smart Data Collective

JUNE 8, 2023

The introduction of data collection and analysis has revolutionized the way teams and coaches approach the game. Liam Fox, a contributor for Forbes detailed some of the ways that data analytics is changing the NFL. Big data will become even more important in the near future.

Data Analytics 105

Data Analytics Analytics Data Collection Statistics 105

Smart Data Collective

OCTOBER 16, 2023

Smart devices use sensors to collect data and upload it to the Internet. Examples include CCTV records, automated vacuum cleaners, weather station data, and other sensor-generated data. All in all, big data refers to massive data collections obtained from various sources.

Big Data 124

Big Data IoT Cost-Benefit Advertising 124

Smart Data Collective

JULY 9, 2023

Collecting Relevant Data for Conversion Rate Optimization Here is some vital data that e-commerce businesses need to collect to improve their conversion rates. Identifying Key Metrics for Conversion Rate Optimization Data collection and analysis are both essential processes for optimizing your conversion rate.

Optimization 97

Optimization Data Analytics Analytics Data-driven 97

Cloudera

SEPTEMBER 22, 2022

To me, this means that by applying more data, analytics, and machine learning to reduce manual efforts helps you work smarter. To make a long story short: this exciting approach enables you to more quickly utilize these data sources to help with your underwriting. Step two: expand machine learning and AI.

Analytics 102

Analytics Insurance IoT Risk 102

datapine

JANUARY 6, 2022

Qualitative data, as it is widely open to interpretation, must be “coded” so as to facilitate the grouping and labeling of data into identifiable themes. Predictive analysis: As its name suggests, the predictive analysis method aims to predict future developments by analyzing historical and current data.

Visualization 246

Visualization Dashboards Cost-Benefit Measurement 246

Smart Data Collective

AUGUST 26, 2021

These data-driven predictions also tend to be surprisingly accurate. Simply put, it involves a diverse array of tech innovations, from artificial intelligence and machine learning to the internet of things (IoT) and wireless communication networks. So, what’s behind the stellar transformation of weather technology?

Forecasting 133

Forecasting Data Analytics Analytics Internet of Things 133

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

CIO Business Intelligence

APRIL 12, 2022

This includes contextual insights, predictive analytics, and anomaly detection for all your apps, along with a topology view of the infrastructure supporting these apps. Relevant datasets: There is no AI without relevant data – lots of relevant data. AIOps can be designed ground-up with data collection at its heart.

Digital Transformation 145

Digital Transformation B2B Enterprise IoT 145

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

CIO Business Intelligence

JULY 20, 2023

From big fashion brands to staples and grocery stores, every retailer is looking to apply algorithms to improve the bottom line, especially in the areas of omnichannel retailing, demand forecasting, and predictive analytics. Moreover, investing more time with a product increases their familiarity with your brand.

Technology 75

Technology Forecasting Advertising Machine Learning 75

Cloudera

DECEMBER 14, 2020

CDP is the next generation big data solution that manages and secures the end-to-end data lifecycle – collecting, enriching, processing, analyzing, and predicting with their streaming data – to drive actionable insights and data-driven decision making. Why upgrade to CDP now?

Big Data 71

Big Data Data-driven Data Collection Data Warehouse 71

Data Science 101

OCTOBER 31, 2019

Data mining is the process of discovering these patterns among the data and is therefore also known as Knowledge Discovery from Data (KDD). Strong patterns, if found, will likely generalize to make accurate predictions on future data. Machine learning provides the technical basis for data mining.

Data mining 77

Data mining KDD Data Science Forecasting 77

Cloudera

MARCH 18, 2021

There will be an increased volume of data storage required, due to the longer history needed by the ES approach to risk measurement. And there will be expansions on the requirements for managing and monitoring both data lineage and data security. Expanded requirements for a centralized and secure single view of risk data. .

Machine Learning 55

Machine Learning Risk Risk Management Measurement 55

IBM Big Data Hub

SEPTEMBER 6, 2023

AI marketing is the process of using AI capabilities like data collection, data-driven analysis, natural language processing (NLP) and machine learning (ML) to deliver customer insights and automate critical marketing decisions. What is AI marketing?

Marketing 78

Marketing Technology Advertising Machine Learning 78

IBM Big Data Hub

JUNE 14, 2023

With IoT devices and sensors collecting data from machines, equipment and assembly lines, AI-powered algorithms can quickly process and analyze inputs to identify patterns and trends, helping manufacturers understand how production processes are performing.

Manufacturing 71

Manufacturing Technology Internet of Things Cost-Benefit 71

IBM Big Data Hub

FEBRUARY 14, 2024

Using machine learning (ML), AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions. See what’s ahead AI can assist with forecasting.

Cost-Benefit 82

Cost-Benefit Insurance Machine Learning Unstructured Data 82

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 82

Data Strategy Strategy Data Warehouse Prescriptive Analytics 82

IBM Big Data Hub

FEBRUARY 23, 2024

Machine learning (ML) and deep learning (DL) form the foundation of conversational AI development. Predictive analytics integrates with NLP, ML and DL to enhance decision-making capabilities, extract insights, and use historical data to forecast future behavior, preferences and trends.

Enterprise 95

Enterprise Interactive Data-driven Key Performance Indicator 95

Jedox

JULY 23, 2019

One of the biggest challenges of automation (Robotic Process Automation) and artificial intelligence/machine learning technologies is our current mindset. AI-based machine learning and predictive analytics will start to give us more powerful crystal balls. Once cleansed, its possible to enrich the data.

Technology 52

Technology Forecasting Finance Data-driven 52

FineReport

MARCH 24, 2024

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

IBM Big Data Hub

AUGUST 7, 2023

It offers enhanced capabilities to analyze complex and large volumes of comprehensive recruitment data to accurately forecast enrollment rates at study, indication, and country levels. AI models can be designed to detect anomalies in real-time site performance data.

Optimization 55

Optimization Forecasting Data-driven Statistics 55

FineReport

JULY 18, 2022

Most data analysts are very familiar with Excel because of its simple operation and powerful data collection, storage, and analysis. Key features: Excel has basic features such as data calculation which is suitable for simple data analysis. Its core product Qlik Sense can connect data from numerous data sources.

Forecasting 52

Forecasting Dashboards Statistics Visualization 52

datapine

AUGUST 29, 2022

James Warren, on the other part, is a successful analytics architect with a background in machine learning and scientific computing. 5) Data Analytics Made Accessible, by Dr. Anil Maheshwari. Best for : the new intern who has no idea what data science even means.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

SEPTEMBER 19, 2023

Rolls-Royce has also found use for AI in predictive maintenance to improve the efficiency of jet engines and reduce the amount of carbon their planes produce, while also streamlining maintenance schedules through predictive analytics. Artificial Intelligence, Chatbots, IT Strategy, Predictive Analytics

Enterprise 141

Enterprise Cost-Benefit Optimization Deep Learning 141

datapine

JANUARY 31, 2022

They used the data collected to build a logistic-regression and unsupervised learning models, so as to determine the potential relationship between drivers and outcomes. 5) Find improvement opportunities through predictions. A great way to illustrate the operational benefits of business intelligence.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

CIO Business Intelligence

JANUARY 6, 2025

AI and Machine Learning will drive innovation across the government, healthcare, and banking/financial services sectors, strongly focusing on generative AI and ethical regulation. Data sovereignty and local cloud infrastructure will remain priorities, supported by national cloud strategies, particularly in the GCC.

IoT 81

IoT Digital Transformation Data-driven Machine Learning 81

Jet Global

MAY 1, 2023

Use the experts in analytics to add value to your product. Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. Diagnostic Analytics: No longer just describing. Predictive Analytics: If x, then y (e.g.,

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MARCH 28, 2025

They make use of some of the robust machine learning and artificial intelligence algorithms to help flexible modelling, predictive analytics, seamless integrations, etc. However, these tools are more of data aggregation and data collection solutions than effective planning aids.

Enterprise 52

Enterprise Metrics Reporting Data Collection 52