AWS Big Data Blog

Tag: Amazon Quicksight

Visualize AWS Cloudtrail Logs using AWS Glue and Amazon Quicksight

Being able to easily visualize AWS CloudTrail logs gives you a better understanding of how your AWS infrastructure is being used. It can also help you audit and review AWS API calls and detect security anomalies inside your AWS account. To do this, you must be able to perform analytics based on your CloudTrail logs. […]

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Amazon QuickSight Adds Support for Combo Charts and Row-Level Security

We are excited to announce support for two new features in Amazon QuickSight: 1) Combo charts, the first visual type in QuickSight to support dual-axis visualization, and 2) Row-Level Security, which allows access control over data at the row level based on the user who is accessing QuickSight. Together, these features enable you to present […]

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Use Amazon QuickSight Federated Single Sign-On with Amazon Cognito User Pools

AWS recently released federated single sign-on to Amazon QuickSight, as announced on the Amazon QuickSight Now Supports Federated Single Sign-On Using SAML 2.0 post. However, SAML 2.0 is not the only way to federate users for Amazon QuickSight. Amazon Cognito user pools are full-fledged identity providers (IdP) that you can use to maintain a user […]

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Build a Schema-On-Read Analytics Pipeline Using Amazon Athena

A robust analytics platform is critical for an organization’s success. However, an analytical system is only as good as the data that is used to power it. Wrong or incomplete data can derail analytical projects completely. Moreover, with varied data types and sources being added to the analytical platform, it’s important that the platform is […]

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Amazon QuickSight Now Allows Users to Create Analyses from Dashboards and Import Custom Date Formats

Today, we are excited to announce two new features in QuickSight that will allow increased flexibility in your interactions with visualizations and data. Create analyses from dashboards When we launched Amazon QuickSight in November 2016, it enabled users to quickly and easily create analyses and dashboards from their data. Analyses allows business users to slice […]

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Query and Visualize AWS Cost and Usage Data Using Amazon Athena and Amazon QuickSight

If you’ve ever wondered if a serverless alternative existed for consuming and querying your AWS Cost and Usage report data, then wonder no more. The answer is yes, and this post both introduces you to that solution and illustrates the simplicity and effortlessness of deploying it. This solution leverages AWS serverless technologies Amazon Athena, AWS […]

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Unite Real-Time and Batch Analytics Using the Big Data Lambda Architecture, Without Servers!

The Big Data Lambda Architecture seeks to provide data engineers and architects with a scalable, fault-tolerant data processing architecture and framework using loosely coupled, distributed systems. At a high level, the Lambda Architecture is designed to handle both real-time and historically aggregated batched data in an integrated fashion. It separates the duties of real-time and […]

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Amazon QuickSight Now Supports Search, Filter Groups, and Amazon S3 Analytics Connector

Today, I’m excited to share information about some new features in Amazon QuickSight. First, you can now search for datasets, analyses, and dashboards in Amazon QuickSight using the unified search box, making it faster and easier to find and access your data. Next, you can now create filter groups with multiple filter conditions that are […]

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Analyzing Salesforce Data with Amazon QuickSight

Salesforce Sales Cloud is a powerful platform for managing customer data. One of the key functions that the platform provides is the ability to track customer opportunities. Opportunities in Salesforce are used to track revenue, sales pipelines, and other activities from the very first contact with a potential customer to a closed sale. Amazon QuickSight […]

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Harmonize, Query, and Visualize Data from Various Providers using AWS Glue, Amazon Athena, and Amazon QuickSight

Have you ever been faced with many different data sources in different formats that need to be analyzed together to drive value and insights?  You need to be able to query, analyze, process, and visualize all your data as one canonical dataset, regardless of the data source or original format. In this post, I walk […]

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