Dataversity
APRIL 26, 2022
As most of these business documents contain unstructured data, automated data extraction has become a go-to option for […]. The post Why Automated Data Extraction Matters in the Digital Age appeared first on DATAVERSITY.
Smart Data Collective
OCTOBER 11, 2019
The quest to collect more data can sometimes get in the way of valuable data that provides clear, relatable, and up-to-date information that helps you make critical business decisions. The post Leveraging Big Data With State-Of-The-Art Business Dashboards appeared first on SmartData Collective.
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Domo
MAY 13, 2021
The first step in the data integration roadmap is understanding what you have. “Organizations should start with a data discovery exercise,” says Isaac Sacolick, President of StarCIO and author of the book Driving Digital. ” In the process, reign in dark or unstructured data.
Astera
OCTOBER 10, 2023
Managing data effectively is a multi-layered activity—you must carefully locate it, consolidate it, and clean it to make it usable. One of the first steps in the data management cycle is data mapping. Data mapping is the process of defining how data elements in one system or format correspond to those in another.
Astera
NOVEMBER 28, 2022
But as data complexity and volumes increase, it’s time to look beyond the traditional data ecosystems. In today’s digitized era, organizations must adapt to the evolving data infrastructure needs to keep up with the technological-driven innovations. Does that mean it’s the end of data warehousing?
Astera
MARCH 1, 2024
Digital technology simplifies this step, allowing policyholders to submit their FNOL through digital platforms such as mobile apps or online portals, enhancing accessibility and efficiency. Claim Data Analysis: After the completion of the claims process, the insurer can conduct an in-depth analysis of the claims data.
Astera
APRIL 7, 2023
Enterprise Data Architecture (EDA) is an extensive framework that defines how enterprises should organize, integrate, and store their data assets to achieve their business goals. At an enterprise level, an effective enterprise data architecture helps in standardizing the data management processes.
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