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Deploy and Optimize Your Snowflake Environment Faster With Accelerators

CDW Research Hub

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. One modern data platform solution that provides simplicity and flexibility to grow is Snowflake’s data cloud and platform.

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Enable business users to analyze large datasets in your data lake with Amazon QuickSight

AWS Big Data

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

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Optimize data layout by bucketing with Amazon Athena and AWS Glue to accelerate downstream queries

AWS Big Data

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

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Analyzing the business-case approach Perdue Farms takes to derive value from data

CIO Business Intelligence

But the more challenging work is in making our processes as efficient as possible so we capture the right data in our desire to become a more data-driven business. If your processes aren’t efficient, you’ll capture the wrong data, and you wind up with the wrong insights. How are you populating your data lake?

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Why optimize your warehouse with a data lakehouse strategy

IBM Big Data Hub

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Some use case examples will help.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement. Example Corp.

Data Lake 117
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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.