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The Data Warehouse is Dead, Long Live the Data Warehouse, Part I

Data Virtualization

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

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Load data incrementally from transactional data lakes to data warehouses

AWS Big Data

Data lakes and data warehouses are two of the most important data storage and management technologies in a modern data architecture. Data lakes store all of an organization’s data, regardless of its format or structure. Various data stores are supported in AWS Glue; for example, AWS Glue 4.0

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Salesforce debuts Zero Copy Partner Network to ease data integration

CIO Business Intelligence

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

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The Data Warehouse is Dead, Long Live the Data Warehouse, Part II

Data Virtualization

Reading Time: 4 minutes My previous post explained that, in my mind, the data lakehouse differs hardly at all from the traditional data warehouse architectural design pattern (ADP). It consists largely of the application of new cloud-based technology to the same requirements and constraints.

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ETL vs ELT: Data Integration Showdown

KDnuggets

Extract-Transform-Load vs Extract-Load-Transform: Data integration methods used to transfer data from one source to a data warehouse. Their aims are similar, but see how they differ.

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5 modern challenges in data integration and how CIOs can overcome them

CIO Business Intelligence

The growing volume of data is a concern, as 20% of enterprises surveyed by IDG are drawing from 1000 or more sources to feed their analytics systems. Data integration needs an overhaul, which can only be achieved by considering the following gaps. Heterogeneous sources produce data sets of different formats and structures.

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Modernizing the Data Warehouse: Challenges and Benefits

BI-Survey

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. They are opting for cloud data services more frequently.