Enterprise Data Warehouses: Definition and Guide
An enterprise data warehouse is critical to the long-term viability of your business.
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An enterprise data warehouse is critical to the long-term viability of your business.
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Real-world success stories illustrate the benefits of a modern data stack, from lower engineering costs to greater data literacy.
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With a modern data stack, Ziff Davis centralizes Google Analytics 360 and ad data to gain insights into paid search performance.
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Learn how data integration allows your organization to maintain all of its data in a single environment, so your team has a comprehensive view of business operations and customer interactions.
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Consider these comparisons before you try to build your own data pipeline
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With Fivetran handling ELT, the company's engineers can focus on data science and machine learning projects.
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With a modern data stack, Branch Insurance joins data from its transactional database and apps to visualize acquisition cost and lifetime value in real time.
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With Fivetran, Snowflake and dbt, Autodesk Construction Services builds a uniform data architecture for its many acquisitions.
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Intercom uses Fivetran to centralize Zuora data into Redshift and join it with product, marketing, sales and other data for reports and dashboards.
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With Fivetran and Snowflake, nonprofit agency Copyright migrates its databases to the cloud, decommissions legacy platforms, and reduces costs.
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With Alooma, schema changes required back-end maintenance, but Fivetran connectors automatically adapt to schema and API changes.
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Learn how Autodesk achieves faster data pipelines with Snowflake and Fivetran.
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With Fivetran, Snowflake, dbt and Looker, Spendesk saves engineering resources, improves the analyst function and introduces a self-service data desk.
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