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Automate deployment of an Amazon QuickSight analysis connecting to an Amazon Redshift data warehouse with an AWS CloudFormation template

AWS Big Data

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

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

AWS Big Data

The following are some of the key business use cases that highlight this need: Trade reporting – Since the global financial crisis of 2007–2008, regulators have increased their demands and scrutiny on regulatory reporting. This will be your OLTP data store for transactional data. version cluster. version cluster.

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96 Percent of Businesses Can’t Be Wrong: How Hybrid Cloud Came to Dominate the Data Sector

Cloudera

The amount of data being collected grew, and the first data warehouses were developed. Big Data” became a topic of conversations and the term “Cloud” was coined. . In 2008, Cloudera was born. Brand-new virtualized private network connections allowed users to share access to the same physical infrastructure.

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Simplify and speed up Apache Spark applications on Amazon Redshift data with Amazon Redshift integration for Apache Spark

AWS Big Data

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data. groupBy("qtr").sum("qtysold").select(

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Banking on mainframe-led digital transformation for financial services

IBM Big Data Hub

Banks have the most to gain if they succeed (and the most to lose if they fail) at bringing their mainframe application and data estates up to modern standards of cloud-like flexibility, agility and innovation to meet customer demand.

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New Thinking, Old Thinking and a Fairytale

Peter James Thomas

A decade later, Gartner had some rather sobering thoughts to offer on the same subject: Gartner predicted that through 2008, about 60% of organizations that outsource customer-facing functions will see client defections and hidden costs that outweigh any potential cost savings. And reduced costs aren’t guaranteed […].

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Delivering Data Security Across Your Organization

Sisense

If you just felt your heartbeat quicken thinking about all the data your company produces, ingests, and connects to every day, then you won’t like this next one: What are you doing to keep that data safe? Data security is one of the defining issues of the age of AI and Big Data. Understanding Your Users.