IBM Big Data Hub

JANUARY 15, 2024

As an insurance company integrating technology into the new development landscape, BoB-Cardif Life Insurance Co., As an insurance company integrating technology into the new development landscape, BoB-Cardif Life Insurance Co.,

Digital Transformation 66

Digital Transformation Insurance Optimization ROI 66

Decision Management Solutions

NOVEMBER 13, 2018

80% of data and analytics leaders with global life insurance and property & casualty carriers surveyed by McKinsey reported that their analytics investments are not delivering high impact. This was the leading obstacle to high impact analytics, outscoring even poor data quality or a lack of strategic support or alignment.

Insurance 40

Insurance Analytics Modeling Visualization 40

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Unlike ingestion processes, data can be transformed as per business rules before loading.

Analytics 96

Analytics Data Warehouse Data Lake Metadata 96

AWS Big Data

AUGUST 14, 2023

When are data products deprecated, and who is accountable for the consequences to their consumers? How do we define “risk” and “value” in the context of data products, and how can we measure this? Whose responsibility is it to justify the existence of a given data product?

Management 98

Management Risk Measurement Optimization 98

CIO Business Intelligence

FEBRUARY 28, 2024

So by using the company’s data, a general-purpose language model becomes a useful business tool. I’m seeing it across all industries,” says Khan, “from high tech and banking all the way to agriculture and insurance.” Then there’s the hard work of collecting and prepping data. It’s a challenge to actually monitor and control.”

IT 131

IT Consulting Modeling Enterprise 131

Peter James Thomas

AUGUST 12, 2018

This piece was prompted by both Olaf’s question and a recent article by my friend Neil Raden on his Silicon Angle blog, Performance management: Can you really manage what you measure? These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

Statistics 49

Statistics Metrics Data Quality Measurement 49

Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CIO Business Intelligence

JULY 3, 2023

Interoperability within CareSource is achieved through a variety of ways: Health Information Exchange (HIE), direct connections to provider EHR systems, and partnerships with multiple companies to deliver critical information in the areas of clinical, claims, social determinant, and formulary data to our patients through secure means.

IT 52

IT Measurement Insurance Interactive 52

DataRobot

JUNE 1, 2021

In an earlier post, I shared the four foundations of trusted performance in AI : data quality, accuracy, robustness and stability, and speed. Industries such as banking and credit, insurance, healthcare and biomedicine, hiring and employment, and housing are often tightly regulated. Meeting Regulatory Expectations.

Uncertainty 52

Uncertainty Machine Learning Advertising Risk 52

Sisense

OCTOBER 29, 2020

“For example, is it OK if a fleet of AVs collect license plate data to track down a vehicle that’s involved in an Amber Alert? What if this data is also used for open warrants? For insurance company premiums? Makers of AVs will need to determine what acceptable and safe data use is before implementing these technologies.

Machine Learning 90

Machine Learning Data Collection Cost-Benefit Advertising 90

CIO Business Intelligence

MARCH 7, 2024

Firewall capability for AI security: Enhance security measures by providing firewall capabilities to safeguard against potential AI-related vulnerabilities. Patricia was previously the CISO at Markel Insurance, Freddie Mac, Symantec, and Unisys, and her insights have always been extremely valuable to her peers.

Digital Transformation 72

Digital Transformation Machine Learning Risk Testing 72

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

Alation

AUGUST 26, 2021

As lakes of data become oceans, locating that which is trustworthy and reliable grows more difficult — and important. Indeed, as businesses attempt to scale AI and BI programs, small issues around data quality can transmogrify into massive challenges. Data quality. Data governance. Data profiling.

Metadata 64

Metadata Data Governance Dashboards Software 64

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. These systems should collectively maintain data quality, integrity, and security, so the organization can use data effectively and efficiently. Why Is Data Governance in Healthcare Important?

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

Alation

FEBRUARY 13, 2020

What’s going on with the whole data at the center? One is that idea of the center and the other is your point about data quality and data trust. The other thing in terms of that data quality and data trustworthiness has been a differentiator. Aaron : Absolutely. You hit on two key themes for us.

ROI 52

ROI Data-driven Finance Data Quality 52

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. See Roadmap for Data Literacy and Data-Driven Business Transformation: A Gartner Trend Insight Report and also The Future of Data and Analytics: Reengineering the Decision, 2025.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

O'Reilly on Data

OCTOBER 22, 2020

banking, insurance, etc.), It’s also a good indirect measure of training data quality: a team that does not know where their data originated is likely to not know other important details about the data as well. .” Why it’s useful: How can you truly know what is good without also knowing what is bad?

Consulting 363

Consulting Risk Cost-Benefit Modeling 363

Occam's Razor

DECEMBER 12, 2016

I was speaking with a massive national insurance company recently. Data quality plays a role into this. And, most of the time, regardless of the size of the size of the company, you only know your code is not working post-launch when data is flowing in (not!). You got me, I am ignoring all the data layer and custom stuff!

Analytics 142

Analytics Data-driven Strategy Consulting 142

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

CIO Business Intelligence

FEBRUARY 5, 2025

Half of CFOs say they plan to cut AI funding if it doesnt show measurable ROI within a year, according to a global survey from accounts payable automation firm Basware, which included 400 CFOs and finance leaders. This requires not only selecting the right projects but also clearly defining how success can be measured.

Cost-Benefit 117

Cost-Benefit ROI Metrics Measurement 117

AWS Big Data

OCTOBER 24, 2024

Maintaining regulatory compliance HCLS organizations are subject to a range of industry-specific regulations and standards, such as Good Practices (GxP) and HIPAA, that ensure data quality, security, and privacy.

Data Warehouse 111

Data Warehouse Business Objectives Data-driven Management 111