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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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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

New data is shared with users by updating reporting schema several times a day. The architecture takes purpose-built data warehouses /marts and other forms of aggregation and star views tailored to analyst requirements. The DataOps Platform does not replace a data lake or the data hub.

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The Future of the Data Lakehouse – Open

Cloudera

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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The Future of the Data Lakehouse – Open

CIO Business Intelligence

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

When the tests pass, the orchestration admits the data to a data catalog. New data is shared with users by updating reporting schema several times a day. This delivery takes the form of purpose-built data warehouses/marts and other forms of aggregation and star views tailored to analyst requirements.

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DataOps For Business Analytics Teams

DataKitchen

There’s a recent trend toward people creating data lake or data warehouse patterns and calling it data enablement or a data hub. DataOps expands upon this approach by focusing on the processes and workflows that create data enablement and business analytics.

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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. We use on-demand capacity mode.