Category: Analytics

Tens of thousands of customers use Amazon Redshift to process exabytes of data per day and power analytics workloads such as business intelligence, predictive analytics, and real-time streaming analytics. Learn how Etleap integrates with new data sharing and cross-database querying capabilities in Amazon Redshift to enable workload isolation for diverse analytics use cases in customer environments. Etleap integrates with any data source and runs either as a hosted solution (SaaS) or inside your VPC.

It can be complicated to maintain a robust, scalable, and reliable monitoring system that inputs terabytes of data under heavy traffic. Learn how Thundra has delivered 99.9 percent availability to customers since incorporating AWS services into its product. Thundra’s platform can handle scalability and availability challenges, recover both from partial failures and major outages, and support point-in-time recovery in case of disaster.

Systems are growing more complex, cloud applications are growing in adoption, and cloud data lakes are being increasingly deployed. At the same time, organizations need to implement data cataloging solutions to provide data governance, data analytics, or pure metadata management. Informatica Enterprise Data Catalog (EDC) scans and catalogs an enterprise’s data assets, whether hosted on the cloud or stored on-premises.

Zendesk and VoiceFoundry released the Amazon Connect app on the Zendesk Marketplace as part of a broader vision for the intelligent contact center of the future. The Amazon Connect app for Zendesk brings together a wide set of capabilities and unlocks endless possibilities for you to empower your agents and better engage your customers. By combining the powers of Amazon Connect and Zendesk, businesses can build a more intelligent contact center.

ThoughtSpot has developed a way for business people to easily answer their own data questions. Search-driven analytics is based on the concept that finding answers to business questions should be as easy as a basic internet search. With ThoughtSpot, there’s no need for SQL expertise or lengthy training sessions—rather, simple searches are translated into database queries and answers are calculated on-the-fly.

Data lakes have evolved into the single store-platform for all enterprise data managed. On AWS, an integrated set of services are available to engineer and automate data lakes. A data lake on AWS is able to group all of the previously mentioned services of relational and non-relational data and allow you to query results faster and at a lower cost. Learn how nClouds used code automation via AWS CloudFormation to create a dynamic data lake stack to visualize and analyze the financial market data.

Insider, an AWS Competency Partner, has been using Elasticsearch for a long time and is satisfied with its performance and features. They had a couple of issues when scaling up its usage, however, but they fixed them by making changes on configurations, architecture, and hardware. Follow along as Insider’s team realizes that fixing symptoms without understanding the root cause may lead to worse scenarios, and how they learned the hard way the importance of identifying the real issue as soon as possible.

Although many SQL engines allow tools to query Amazon S3 data, organizations face multiple challenges, including high latency and infrastructure costs. Learn how Dremio empowers analysts and data scientists to analyze data in S3 directly at interactive speed, without having to physically copy data into other systems or create extracts, cubes, and/or aggregation tables. Dremio’s unique architecture enables faster and more reliable query performance than traditional SQL engines.

Many oil & gas operators need near-instant access to their geoscience data. Unfortunately, most subsurface applications provide only a limited, fragmented view of data. INT’s data visualization platform IVAAP uses OSDU on AWS to enable users who want to optimize this and other workflows. The IVAAP platform offers a single point of access to search, interact with, analyze, and visualize multiple petrotechnical data sources in a single web-based application.

Apache Hudi on Amazon EMR is an ideal solution for large-scale and near real-time applications that require incremental data pipelines and processing. This post provides a step-by-step method to perform a proof of concept for Apache Hudi on Amazon EMR. Learn how a non-customer-facing PoC solution from nClouds set up a new data and analytics platform using Apache Hudi on Amazon EMR and other managed services, including Amazon QuickSight for data visualization.