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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

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Data Observability and Monitoring with DataOps

DataKitchen

Figure 1: The process of transforming raw data into actionable business intelligence is a manufacturing process. When something goes wrong, you need to know about it as it’s happening to ensure that errors don’t reach customers or business partners. It’s not about data quality . It’s not only about the data.

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Financial Dashboard: Definition, Examples, and How-tos

FineReport

Furthermore, we will introduce some business intelligence solution that excels in simplifying the process of creating and utilizing a financial dashboard effectively. Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses.

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How Tricentis unlocks insights across the software development lifecycle at speed and scale using Amazon Redshift

AWS Big Data

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.