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As cloud data volumes grow, costs escalate fast. Pentaho Data Optimizer helps organizations control storage and data-driven compute costs by identifying low-value data, automating intelligent tiering, and optimizing data lifecycles across modern cloud platforms, including Snowflake and Databricks.
Cloud storage grows quietly and relentlessly. Cold data, duplicates, and unused datasets accumulate while costs rise month after month.
Whether your data lives in AWS, Azure, or Google Cloud, including platforms like Snowflake and Databricks, Pentaho Data Optimizer gives you clear visibility into what data is actively used, what is rarely accessed, and what is quietly driving unnecessary spend.
With the Pentaho cost calculator, you can estimate potential savings by eliminating unused data, shrinking oversized datasets, and preventing future data sprawl. Many organizations uncover meaningful cost reduction opportunities quickly, without refactoring pipelines or introducing downtime.
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Cost control is not about slowing innovation or limiting access. It is about ensuring data costs stay aligned to its business value, so low-value and unused data never consumes high-cost cloud resources.
Pentaho Data Optimizer continuously evaluates data value across AWS, Azure, and Google Cloud, ensuring that only data that delivers real value uses premium storage and compute.
By bringing visibility and automation to the cloud data lifecycle, Pentaho Data Optimizer lets teams actively manage what data is stored, where it lives, and what it costs, while analytics and AI continue to move fast.
Pentaho helps ensure your AWS, Azure, and Google Cloud environments, including platforms like Snowflake and Databricks, receive high-value, trusted data only. By identifying ROT data early and optimizing data lifecycle policies, you reduce uncontrolled growth and gain clear visibility into how data is actually being used.
Apply consistent optimization policies across AWS, Azure, and Google Cloud, including Snowflake, and Databricks workloads. Storage tiers, retention rules, and lifecycle automation are defined once and enforced everywhere, reducing operational complexity and preventing surprise cost spikes.
Automated, repeatable optimization pipelines reduce manual cleanup, migrations, and cost audits across cloud environments and the data platforms running on them, while maintaining predictable performance for analytics and AI workloads.
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Managing fast-growing cloud data volumes requires more than monitoring spend after the fact.
Pentaho Data Optimizer works across AWS, Azure, and Google Cloud, alongside platforms like Snowflake and Databricks, to reduce complexity, control costs, and ensure analytics and AI workloads run on lean, high-value datasets.