AWS Big Data
DECEMBER 8, 2023
More and more of FanDuel’s community of analysts and business users looked for comprehensive data solutions that centralized the data across the various arms of their business. Their individual, product-specific, and often on-premises data warehouses soon became obsolete.
CIO Business Intelligence
JUNE 23, 2023
According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.
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Ontotext
FEBRUARY 12, 2024
This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. However, data mesh is not about introducing new technologies.
IBM Big Data Hub
JANUARY 5, 2023
The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.
Jet Global
SEPTEMBER 4, 2020
Now, instead of making a direct call to the underlying database to retrieve information, a report must query a so-called “data entity” instead. Each data entity provides an abstract representation of business objects within the database, such as, customers, general ledger accounts, or purchase orders. Data Lakes.
BI-Survey
FEBRUARY 17, 2020
However, effectively using data needs to be learned. Companies using multiple systems for various purposes tend to have complex technology landscapes with highly specialized silo solutions. It is therefore vital that data is subject to some form of overarching control, which should be guided by a data strategy.
AWS Big Data
MARCH 7, 2023
This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. Data lakes are more focused around storing and maintaining all the data in an organization in one place.
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