Cloudera

FEBRUARY 15, 2024

From stringent data protection measures to complex risk management protocols, institutions must not only adapt to regulatory shifts but also proactively anticipate emerging requirements, as well as predict negative outcomes.

Insurance 85

Insurance Data Architecture Risk Management Risk 85

CIO Business Intelligence

MAY 8, 2024

This article focuses on how these advancements are paving the way for data integration for the years to come in this ever-so-dynamic technological era. AI-powered data integration One of the most promising advancements in data integration is the integration of artificial intelligence (AI) and machine learning (ML) technologies.

Data Integration 52

Data Integration IoT Cost-Benefit Data Quality 52

Grooper

AUGUST 19, 2019

Choosing the right analytics solution isn't easy. Successfully navigating the 20,000+ analytics and business intelligence solutions on the market requires a special approach. Read on to learn how data literacy, information as a second language, and insight-driven analytics take digital strategy to a new level.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Cloudera

OCTOBER 28, 2021

I’ve had the pleasure to participate in a few Commercial Lines insurance industry events recently and as a prior Commercial Lines insurer myself, I am thrilled with the progress the industry is making using data and analytics. Commercial Lines truly is an “uber industry” with respect to data. Another example is fleet management.

Insurance 95

Insurance Risk Unstructured Data Data-driven 95

AWS Big Data

MARCH 25, 2024

Streaming data facilitates the constant flow of diverse and up-to-date information, enhancing the models’ ability to adapt and generate more accurate, contextually relevant outputs. For building such a data store, an unstructured data store would be best. This use case fits very well in the streaming analytics domain.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

Sisense

OCTOBER 6, 2020

The challenge comes when the data becomes huge and fast-changing. Why is quantitative data important? Quantitative data is often viewed as the bedrock of your business intelligence and analytics program because it can reveal valuable insights for your organization. Advanced technology and new approaches are needed.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52