Tag: Q/Machine Learning.

Organizations often need to process large volumes of data before serving to business stakeholders. In this blog, we will learn how to leverage Amazon EMR to process data using Apache Spark, the go-to platform for in-memory analytics of large data volume, and connect business intelligence (BI) tool Amazon QuickSight to serve data to end-users. QuickSight […]

A large business intelligence (BI) project with many users and teams and sensitive information demands a multi-faceted security architecture. Such architecture should provide BI administrators and architects with the capability to minimize the amount of information accessible to users. For a straightforward solution to manage Amazon QuickSight user and asset access permissions, you can use […]

Amazon QuickSight is a fast, cloud-native, serverless, business intelligence service that makes it easy to deliver insights to everyone. QuickSight has carefully designed concepts and features that enable analysis builders, such as QuickSight authors, to design content-rich, interactive, and dynamic dashboards to share with dashboard viewers. As authors build an analysis, QuickSight transforms, filters, and […]

October 2023: This post was reviewed and updated to include SPICE setup Amazon QuickSight is a scalable, serverless, embeddable, machine learning-powered business intelligence (BI) service built for the cloud. QuickSight lets you easily create and publish interactive BI dashboards that include Machine Learning-powered insights. QuickSight dashboards can be accessed from any device, and seamlessly embedded […]

Amazon QuickSight is a scalable, serverless, embeddable, machine learning (ML)-powered business intelligence (BI) service built for the cloud that supports identity federation in both Standard and Enterprise editions. Organizations are working towards centralizing their identity and access strategy across all of their applications, including on-premises, third-party, and applications on AWS. Many organizations use Microsoft Azure […]

This blog post is co-written by Glen Douglas and Alex Savchenko from Integrationworx. Enterprises that follow an Agile software development lifecycle (SDLC) process for their dashboard development and deployment typically have distinct environments for development, staging, QA and test, and production. One recommended approach when developing using AWS is to create multiple AWS accounts corresponding […]

Organizations need a consolidated view of their applications, but typically application health status is siloed: end-users complain on social media platforms, operational data coming from application logs is stored on complex monitoring tools, formal ticketing systems track reported issues, and synthetic monitoring data is only available for the tool administrators. In this post, we show […]

NTT DOCOMO is the largest telecom company in Japan. It provides innovative, convenient, and secure mobile services that enable customers to realize smarter lives. More than 73 million customers in Japan connect through its advanced wireless networks, including a nationwide LTE network and one of the world’s most progressive LTE Advanced networks. In addition to […]

Data quality plays an important role while building an extract, transform, and load (ETL) pipeline for sending data to downstream analytical applications and machine learning (ML) models. The analogy “garbage in, garbage out” is apt at describing why it’s important to filter out bad data before further processing. Continuously monitoring data quality and comparing it […]

Every business has a set of key metrics that stakeholders focus on to make the most accurate, data-driven decisions, such as sales per week, inventory turnover rate, daily website visitors, and so on. With threshold-based alerts in Amazon QuickSight, we’re making it simpler than ever for consumers of QuickSight dashboards to stay informed about their […]