Business Intelligence Data Strategy Data Warehouse Metadata 
TDAN
APRIL 6, 2021
A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.
CIO Business Intelligence
NOVEMBER 22, 2022
Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.
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CIO Business Intelligence
OCTOBER 13, 2023
Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.
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. Practice proper data hygiene across interfaces.
AWS Big Data
MARCH 10, 2023
However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. The Iceberg table is synced with the AWS Glue Data Catalog.
TDAN
APRIL 19, 2022
Introduction We are living in the age of a data revolution, and more corporations are realizing that to lead—or in some cases, to survive—they need to harness their data wealth effectively.
TDAN
MARCH 19, 2019
Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.
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