Remove Dashboards Remove Data Transformation Remove Measurement Remove Snapshot
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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.

Big Data 275
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How SafetyCulture scales unpredictable dbt Cloud workloads in a cost-effective manner with Amazon Redshift

AWS Big Data

A source of unpredictable workloads is dbt Cloud , which SafetyCulture uses to manage data transformations in the form of models. SafetyCulture also successfully ran its dbt project with all seeds, models, and snapshots materialized into the serverless instance via run commands from the dbt Cloud IDE and dbt Cloud CI jobs.

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

AWS Big Data

Key performance indicators (KPIs) of interest for a call center from a near-real-time platform could be calls waiting in the queue, highlighted in a performance dashboard within a few seconds of data ingestion from call center streams. Visualize KPIs of call center performance in near-real time through OpenSearch Dashboards.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly on Data

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. To manage the dynamism, we can resort to taking snapshots that represent immutable points in time: of models, of data, of code, and of internal state.

IT 346
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How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

AWS Big Data

Initially, Tricentis defines these dashboards and charts to enable insight on test runs, test traceability with requirements, and many other pre-defined use cases that can be valuable to customers. As the files are created, another process is triggered to load the data from each customer on their schema or table on Amazon Redshift.