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Combine transactional, streaming, and third-party data on Amazon Redshift for financial services

AWS Big Data

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster. version cluster.

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Financial Dashboard: Definition, Examples, and How-tos

FineReport

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). It is generally advisable to maintain a quick ratio above 100%.

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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

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Standard Metrics Revisited: #6: Daily, Weekly, Monthly Unique Visitors.

Occam's Razor

All web analytics tools have a smattering of metrics and key performance indicators that were created just because someone decided it would be cute to add / subtract / multiply / divide some numbers. You can learn a lot more about Visits and Unique Visitors in this post: Standard Metrics Revisited: #1: Visitors.

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Exploring real-time streaming for generative AI Applications

AWS Big Data

Stream processing, however, can enable the chatbot to access real-time data and adapt to changes in availability and price, providing the best guidance to the customer and enhancing the customer experience. When the model finds an anomaly or abnormal metric value, it should immediately produce an alert and notify the operator.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics: Part 2

AWS Big Data

AWS Glue has made this more straightforward with the launch of AWS Glue job observability metrics , which provide valuable insights into your data integration pipelines built on AWS Glue. However, you might need to track key performance indicators across multiple jobs. Choose Add new data source.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.