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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries. According to studies, 92% of data leaders say their businesses saw measurable value from their data and analytics investments.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

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How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

AWS Big Data

While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source. Automated data integrity High data integrity is a fundamental design principle of Tricentis Analytics.

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“You Complete Me,” said Data Lineage to DataOps Observability.

DataKitchen

To capture a more complete picture of the data’s journey, it is important to have a DataOps Observability system in place. Data lineage is static and often lags by weeks or months. Data lineage is often considered static because it is typically based on snapshots of data and metadata taken at a specific time.

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