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

CIO Business Intelligence

APRIL 6, 2022

In this way, AIOps frees up decision makers to focus on larger business issues, as well as provides them with clear visual information. There are several factors that can reduce organizational efficiency: Infrastructure: Many IT environments have disparate systems in silos, making it difficult to accelerate the flow of data between systems.

Data mining 67

Data mining Deep Learning Insurance Digital Transformation 67

erwin

MARCH 30, 2020

This data will be collected from organizations such as, the World Health Organization (WHO), the Centers for Disease Control (CDC), and state and local governments across the globe. Privately it will come from hospitals, labs, pharmaceutical companies, doctors and private health insurers. Data lineage to support impact analysis.

Metadata 122

Metadata IT Data Governance Data Quality 122

datapine

MAY 31, 2022

Traditional spreadsheets no longer serve their purpose, there is just too much data to store, manage and analyze. Be it in the form of online BI tools , or an online data visualization system, a company must address where and how to store its data. The next part of our cloud computing risks list involves costs.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

Octopai

JUNE 26, 2020

Steve, the Head of Business Intelligence at a leading insurance company, pushed back in his office chair and stood up, waving his fists at the screen. We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Without metadata, the organization is at risk of making decisions based on the wrong data.”.

Metadata 84

Metadata Data Governance Enterprise Reporting 84

DataRobot Blog

JULY 21, 2022

If there is no forward-looking predictive component to the use case, it can probably be addressed with analytics and visualizations applied to historical data. Inquire whether there is sufficient data to support machine learning. Document assumptions and risks to develop a risk management strategy.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Domino Data Lab

JULY 22, 2019

He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. It involved a lot of work with applied math, some depth in statistics and visualization, and also a lot of communication skills. It’s not going to happen.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109