Cloudera

AUGUST 12, 2021

The report classified employees’ reasons for leaving into six broad categories such as growth opportunity and job security, demonstrating the importance of using performance data, data collected from voluntary departures and historical data to reduce attrition for strong performers and enhance employees’ well-being.

Data-driven 107

Data-driven Manufacturing Insurance Risk Management 107

IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AIOps is one of the fastest ways to boost ROI from digital transformation investments.

Cost-Benefit 90

Cost-Benefit Insurance Unstructured Data Machine Learning 90

CIO Business Intelligence

MAY 16, 2023

The industries these decision-makers represented include insurance, banking, healthcare and life sciences, government, entertainment, and energy in the U.S. Big Data collection at scale is increasing across industries, presenting opportunities for companies to develop AI models and leverage insights from that data.

Advertising 105

Advertising Recreation/Entertainment Experimentation Enterprise 105

IBM Big Data Hub

APRIL 24, 2024

Rules for handling children’s data might become even stricter if the Kids Online Safety Act (KOSA), currently under consideration in the US Senate, becomes law. Finally, the retailer classifies data based on sensitivity levels and applies appropriate controls to each type. Retention policies should also be limited.

Risk 89

Risk Measurement Data Governance Insurance 89

Smart Data Collective

MAY 6, 2019

It could be that Uber and other companies see a financial imperative in automating their future workforce so that they don’t have to fret about providing insurance and other benefits to a large coterie of human employees.

Management 103

Management Insurance Data Collection Cost-Benefit 103

Smart Data Collective

MAY 29, 2022

What is data analytics? One of the most buzzing terminologies of this decade has got to be “data analytics.” Companies generate unlimited data every day, and there is no end to the data collected over time. Companies need all of this data in a structured manner to improve their decision—making capabilities.

Data Analytics 132

Data Analytics Analytics Strategy Insurance 132

Smart Data Collective

MARCH 23, 2022

Evaluating credit card usage: Most companies will consider credit card usage for identifying theft or fraudulent acts; however, the data can be used for looking at credit limits, interest rates, and collecting debt. Regarding surveys, the basket analysis helps you identify what type of questions you can ask your consumers.

Data mining 120

Data mining Marketing Insurance Data Collection 120

IBM Big Data Hub

SEPTEMBER 28, 2023

Financial tasks evaluated includes: providing sentiment scores for stock and earnings call transcripts, classifying news headlines, extracting credit risk assessments, summarizing financial long-form text and answering financial or insurance-related questions. The synthetic data generator service in watsonx.ai

Testing 95

Testing Finance Enterprise Modeling 95

Smart Data Collective

MARCH 2, 2022

One area of enterprise digital transformation that can be solved with no-code is customer data collection, such as forms and paperwork in insurance and banking. The market for these platforms is growing quickly and there are lots of good options available at different price points.

Data Science 110

Data Science Enterprise Insurance Digital Transformation 110

IBM Big Data Hub

FEBRUARY 23, 2024

Marketing and sales: Conversational AI has become an invaluable tool for data collection. It assists customers and gathers crucial customer data during interactions to convert potential customers into active ones. This data can be used to better understand customer preferences and tailor marketing strategies accordingly.

Enterprise 108

Enterprise Interactive Data-driven Key Performance Indicator 108

Smart Data Collective

DECEMBER 20, 2019

Adoption is certainly ramping up, and the technologies that support IoT are also growing more sophisticated — including big data, cloud computing and machine learning. Reports are especially useful to have during inspections , insurance and liability events, and much more. Enhances Operational Intelligence Support.

IoT 58

IoT Internet of Things Measurement Reporting 58

Sisense

MARCH 3, 2021

Big data in healthcare has the power to improve care, lower costs, and save lives. Healthcare providers are steadily digitizing their internal operations, resulting in mountains of new data being collected daily.

Big Data 98

Big Data Risk Sales Insurance 98

Occam's Razor

MARCH 30, 2017

All this data, across tens of millions of identified signals to deliver a deeply unique message to humans that mattered the most – at scale. We are needed today because data collection is hard. Most humans employed by companies were unable to access data – not intelligent enough or trained enough or simply time pressures.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Domino Data Lab

JULY 22, 2019

You know, companies like telecom and insurance, they don’t really need machine learning.” If you were out five years ago talking in industry about the importance of graphs and graph algorithms and representation of graph data, because most business data ultimately is some form of graph. ” But that changed.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Smart Data Collective

AUGUST 4, 2022

They can also create problems for companies that rely on the connection to collect data. Since data collection is vital to modern healthcare , this can be a huge problem for hospitals and other healthcare service providers. Wi-Fi Problems Create Problems for Data-Driven Healthcare Organizations.

Data-driven 115

Data-driven Modeling Cost-Benefit Insurance 115

Cloudera

SEPTEMBER 4, 2020

In Europe, one of the leading CSPs is using the platform to bring in data from black boxes in connected cars to improve road safety, for assistance, for monitoring and they’re even using data from connected devices to provide targeted insurance offerings based on specific risks of individual drivers.

IoT 92

IoT Machine Learning Optimization Insurance 92

Cloudera

MARCH 18, 2021

From a data management point of view, FRTB’s requirements will require greatly increased quantities of historical data, along with an increased need for analysis and intensive computation against this data. . And there will be expansions on the requirements for managing and monitoring both data lineage and data security.

Risk 55

Risk Machine Learning Risk Management Measurement 55

AWS Big Data

FEBRUARY 21, 2023

SQL Depth Runtime in Seconds Cost per Query in Seconds 14 80 40,000 12 60 30,000 5 30 15,000 3 25 12,500 The hybrid model addresses major issues raised by the data vault and dimensional model approaches that we’ve discussed in this post, while also allowing improvements in data collection, including IoT data streaming.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

Occam's Razor

DECEMBER 12, 2016

I was speaking with a massive national insurance company recently. You got me, I am ignoring all the data layer and custom stuff! But, at the end of the day presence of a Tag Manager communicates to me that the company is serious about data collection and data quality. All that is great. That is what you want.

Analytics 141

Analytics Data-driven Strategy Consulting 141

Domino Data Lab

FEBRUARY 4, 2019

These two points provide a different kind of risk management mechanism which is effective for science, specifically data science. Of course, some questions in business cannot be answered with historical data. Instead they require investment, tooling, and time for data collection. Secondly, because stakeholders.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66