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How Ruparupa gained updated insights with an Amazon S3 data lake, AWS Glue, Apache Hudi, and Amazon QuickSight

AWS Big Data

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

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The Future of the Data Lakehouse – Open

CIO Business Intelligence

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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The Future of the Data Lakehouse – Open

Cloudera

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

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Amazon Redshift announcements at AWS re:Invent 2023 to enable analytics on all your data

AWS Big Data

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Improve healthcare services through patient 360: A zero-ETL approach to enable near real-time data analytics

AWS Big Data

This means you can seamlessly combine information such as clinical data stored in HealthLake with data stored in operational databases such as a patient relationship management system, together with data produced from wearable devices in near real-time. To get started with this feature, see Querying the AWS Glue Data Catalog.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Streaming data facilitates the constant flow of diverse and up-to-date information, enhancing the models’ ability to adapt and generate more accurate, contextually relevant outputs. With a file system sink connector, Apache Flink jobs can deliver data to Amazon S3 in open format (such as JSON, Avro, Parquet, and more) files as data objects.

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How Can Manufacturing Data Help Your Organization?

Sisense

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. How data enhances product development.