AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

Data Quality 96

Data Quality Statistics Data Lake Visualization 96

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

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. Cost management and containment.

Risk 237

Risk Cost-Benefit Business Intelligence Data-driven 237

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 74

Analytics Data Warehouse Data Lake Metadata 74

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. Outline clear metrics to measure success. Not every project needs machine learning.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

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. As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. measuring value, prioritizing (where to start), and data literacy?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

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 Data-driven Machine Learning 66