IBM Big Data Hub

OCTOBER 30, 2023

Real-time analytics on customer data — made possible by DB2’s high-speed processing on AWS — allows the company to offer personalized insurance packages. AI algorithms sift through large datasets to identify fraud risks and streamline claims processing, improving both efficiency and customer satisfaction.

Insurance 78

Insurance Data Warehouse Data-driven Unstructured Data 78

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

Smarten

DECEMBER 3, 2023

Augmented analytics can help the business to improve revenue and to discover product and service opportunities and gain insight into issues to resolve problems before they create risk. Unscrambl highlights a few of the ways major businesses have used analytics to help improve competitive positioning and to solve problems.

Analytics 40

Analytics Cost-Benefit Data Quality Consulting 40

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

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 316

Enterprise Deep Learning Data Governance Risk 316

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk. Humans can’t keep up.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process.

Data Analytics 91

Data Analytics Analytics Data Warehouse Data Lake 91

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. Enrichment typically involves adding demographic, behavioral, and geolocation data.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

OCTOBER 20, 2023

AI platforms assist with a multitude of tasks ranging from enforcing data governance to better workload distribution to the accelerated construction of machine learning models. The best AI platforms typically have various measures in place to ensure that your data, application endpoints and identity are protected.

Machine Learning 71

Machine Learning Manufacturing Cost-Benefit Deep Learning 71

Grooper

AUGUST 19, 2019

Key Language of Applied Analytics. The vocabulary of applied analytics includes words and concepts such as: Key performance indicators (KPIs). Master data management. Data governance. Scoring – i.e. profitability or risk. Structured, semi-structured, and unstructured data. Data pipelines.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

DataRobot

JANUARY 20, 2022

. — Snowflake and DataRobot AI Cloud Platform is built around the need to enable secure and efficient data sharing, the integration of disparate data sources, and the enablement of intuitive operational and clinical predictive analytics. Building data communities. . – Public sector data sharing.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

Alation

JANUARY 27, 2022

People might not understand the data, the data they chose might not be ideal for their application, or there might be better, more current, or more accurate data available. An effective data governance program ensures data consistency and trustworthiness. It can also help prevent data misuse.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Andrew White

JANUARY 11, 2021

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Governance. Would really like to explore this one in debate.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52