AWS Partner Network (APN) Blog

Tag: Business Intelligence

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Accelerate Modernization on AWS with Cognizant Data and Intelligence Toolkit-Migration Studio

As data sources are becoming increasingly varied and data volume increases multifold, traditional data platforms can prevent organizations from analyzing data at scale and turning that information into tangible business insights. Cognizant Data and Intelligence Toolkit-Migration Studio streamlines the modernization journey with a suite of pre-built accelerators that can simplify and speed up every stage of migration, including discovery, ETL, business intelligence reports migration, and validation.

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Leveraging Amazon Transcribe and Amazon QuickSight to Extract Business Intelligence from Call Center Data

Many organizations record calls which are potential gold mines of rich insights about customer satisfaction, customer churn, competitive intelligence, service issues, agent performance, and campaign effectiveness. However, the sheer volume of phone calls exceeds a contact center’s ability to review and analyze them in order to glean those valuable insights. Learn how SourceFuse used custom microservices development to design a call center solution for a healthcare customer.

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Aligning Business Intelligence and AI/ML with a Data Mesh Platform on AWS

Data mesh is emerging as a paradigm for generating data-driven value and is gaining real-world adoption within industries like financial services and automotive. Learn about the user journeys of two types of data consumers in a mesh platform: business intelligence and data scientists. Explore how BI and AI/ML overlap within a set of data domains, and how a platform architecture further enables the desired experiences within a data mesh.

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Data Warehousing and Business Intelligence for VMware Cloud on AWS

One of the biggest advantages of VMware Cloud on AWS is that it can readily integrate with other AWS services. That gives you countless ways to elevate your workloads. If you’re amassing data in your databases over time and are looking for novel ways to glean fresh insights out of it, using Amazon Redshift and Amazon QuickSight is an easy and accessible way to achieve it. This post describes how to get more out of existing data residing inside your databases running in VMware Cloud on AWS.

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Securely Querying Your Data Lake with Ahana Presto and AWS Lake Formation

Ahana provides a fully managed and easy-to-use service for running Presto on AWS, and customers like Metropolis use Ahana to query data in their Amazon S3-based data lake for business intelligence, ad-hoc analytics, and reporting. Learn how Metropolis uses AWS Lake Formation and Ahana to build a data lake that allows their analysts and data scientists to develop a simple, hands-free parking experience for their customers.

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Using Databricks SQL on Photon to Power Your AWS Lake House

Databricks SQL is a dedicated workspace for data analysts that comprises a native SQL editor, drag-and-drop dashboards, and built-in connectors for all major business intelligence tools as well as Photon. In this post, Volker Tjaden, an APN Ambassador from Databricks, shares the technical capabilities of Databricks SQL and walks through two examples: ingesting, querying, and visualizing AWS CloudTrail log data, and building near real-time dashboards on data coming from Amazon Kinesis.

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Using AtScale and Amazon Redshift to Build a Modern Analytics Program with a Lake House

There has been a lot of buzz about a new data architecture design pattern called a Lake House. A Lake House approach integrates a data lake with the data warehouse and all of the purpose-built stores so customers no longer have to take a one-size-fits-all approach and are able to select the storage that best suits their needs. Learn how to couple Amazon Redshift with a semantic layer from AtScale to deliver fast, agile, and analysis-ready data to business analysts and data scientists.

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AI-Driven Analytics on AWS Using Tableau and Amazon SageMaker

Organizations that have foresight into their business have a competitive advantage. Advanced analytics that enable foresight have historically required scarce resources to develop predictive models using techniques like machine learning. Traditionally, this is a difficult endeavor, but recent progress in ML automation has made democratization of ML a possibility. Learn about the value of augmenting analytics with ML through the Amazon SageMaker for Tableau Quick Start.

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Building a Single Source of Truth with a Data Hub from Semarchy

Organizations need a comprehensive data management solution that includes data quality, cleansing, de-duplication, and curation capabilities. After consolidating trusted golden records, they need to enforce governance requirements and track changes over time. Semarchy’s xDM platform is an innovation in multi-vector Main Data Management (MDM) that leverages smart algorithms and material design to simplify data stewardship, governance, and integration.

How TIBCO Leverages AWS for its COVID-19 Analytics App

TIBCO Software has launched an analytics app to track the spread and impact of the COVID-19 pandemic in real-time, over local regions worldwide. The goal of this analytics app is to enable organizations to assess the potential impact of the COVID-19 pandemic on their business fabric, using sound data science and data management principles, in the context of real-time operations. Learn some of key capabilities of the app and how it was developed on AWS.