Data Lake Data Transformation Data Warehouse Finance 
Jet Global
MAY 9, 2024
The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.
AWS Big Data
DECEMBER 21, 2023
To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.
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CIO Business Intelligence
FEBRUARY 16, 2023
“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. That step, primarily undertaken by developers and data architects, established data governance and data integration.
Jet Global
FEBRUARY 23, 2024
This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.
IBM Big Data Hub
OCTOBER 16, 2023
Positive curation means adding items from certain domains, such as finance, legal and regulatory, cybersecurity, and sustainability, that are important for enterprise users. It also lets you choose the right engine for the right workload at the right cost, potentially reducing your data warehouse costs by optimizing workloads.
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