As more companies are leveraging the Data Lake to run their warehouse workloads, we’re seeing many companies move to an Open Data Lakehouse stack. The Open Data Lakehouse brings the reliability and performance of the Data Warehouse together with the flexibility and simplicity of the Data Lake, enabling data warehouse workloads to run on the data lake.
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It’s not always about the numbers; it’s more about how you present them in an easily understandable way. Not everything can go into a pie chart, and not everything looks right in a line graph. That’s why it’s crucial to know the best principles of data visualization.
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awscloud.com
Fanatics, a popular sports apparel website and fan gear merchandiser, needed to ingest terabytes of data from multiple historical and streaming sources transactional, e-commerce, and back-office systems to a data lake on Amazon S3. Once ingested, the data would be analyzed to better identify, predict, and fulfill customer needs related to the products Fanatics offers in over 300 online and offline stores.
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Amazon Web Services, Inc
The number of sources generating continuous, streaming data has exploded in recent years. From website clickstream data to telemetry data from Internet of Things (IoT) devices, the variety, volume, and velocity of data continues to increase. In response, businesses are evolving their analytics approach from batch to real time, and turning to new tools to deliver actionable insights in seconds instead of hours or days. With AWS, you can easily and cost-effectively collect, process, and analyze real-time streaming data at any scale, so you can learn what your applications and customers are doing right now—and respond immediately.
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