Category: Analytics

With the 2018 release of Amazon OpenSearch Service integration with Amazon Cognito, you can now enable corporate users to access OpenSearch with Kibana using your corporate directory credentials through identity federation. In this post, we share a step-by-step integration of Auth0 and Amazon Cognito. With Amazon Cognito User Pool, you can extend your directory so Auth0 users are able to log in to Kibana with the same security credentials.

Data is at the nucleus of informed decision-making. For many organizations, however, there are complicated processes that come into play before data can serve its true purpose. The Alteryx Platform is a self-service data science and analytics platform that enables organizations to take full advantage of their data and analytics assets through a drag-and-drop interface that is both code-free and code-friendly. The end-to-end platform empowers users to break data barriers and deliver business-critical insights faster.

With the 2018 release of Amazon OpenSearch Service integration with Amazon Cognito, you can now enable corporate users to access OpenSearch with Kibana using your corporate directory credentials through identity federation. In this post, we share a step-by-step integration of Active Directory (AD) and Amazon Cognito. With Amazon Cognito User Pool, you can extend your directory so AD users are able to log in to Kibana with the same security credentials.

Deloitte’s Gary Arora, an APN Ambassador, will show you how to integrate an application with Amazon Athena to execute SQL queries with ‘athena-express.’ This is a wrapper around the AWS SDK that can simplify executing SQL queries in Amazon Athena and fetch the JSON results in the same synchronous call—a capability well suited for many web applications. Developers can use ‘athena-express’ to help save time and effort in setting up the integration and focus on core application development.

Today’s businesses deal with many different varieties of data, including structured datasets stored in various repositories like a relational databse management system (RDBMS) or enterprise resource planning (ERP); semi-structured datasets like web logs and click-stream datasets; and unstructured datasets like images and videos. AWS provides a secure, scalable, comprehensive, and cost-effective portfolio of services that enable customers to build their data lake in the cloud.

AWS provides a broad set of managed services for data analytics that, along with a strong APN Partner community, can help you build a scalable, secure, and cost-effective data lake. Customers and APN Partners want to know how to put all these pieces so we created a new poster and video explaining the overall flow of data—from data collection, storage, and processing all the way to analytics and machine learning.

Despite advances in music-sharing technology, touring and live shows remain staples for emerging artists. How do artists and promoters align the reach of streaming services with fans’ physical locations to better plan, promote, and manage live shows? To answer this question, Vertical Trail partnered with Gigable to create a music platform and app that uses curated playlists, geo-based concert discovery, and online ticketing to close the gap between artists and their fans—all while building a formidable big data asset.

While modernizing customer mainframes, the team at AWS Blu Age discovered that Batch can be a complex aspect of a mainframe migration to AWS. It’s critical to design your AWS architecture to account for the key Batch stringent performance requirements such as intensive I/Os, large datasets, and short durations. Let’s explore how to migrate mainframe Batch to AWS microservices using AWS Blu Age automated transformation technology.

Amazon Athena is a Presto-distributed SQL engine used to query unstructured data using standard SQL, where you pay only for the amount of data you query. Chartio, an AWS Competency Partner, recently announced support for Athena. Their solution allows you to query and visualize data stored in an Amazon S3 data lake using standard SQL. You can also use their visual drag-and-drop SQL layer, which generates native SQL queries for you.

To gain the insights needed to fuel business growth, organizations need to collect more data and do more with it. That’s where a data lake can help—it’s a repository that holds a large amount of raw data in its native (structured or unstructured) format until that data is needed, enabling you to accommodate virtually any use case. Check out Cloudwick’s Data Lake Foundation on AWS Quick Start, and then drill down a bit deeper into the workings and value of the data catalog.