Category: Learning Levels

Amazon DevOps Guru is a machine learning-powered service that detects abnormal application behavior and provides insights about the anomalous behavior. These insights are supported with metrics and events related to the anomaly and recommendations to help address and mitigate the anomalous behavior. Learn how Blue People used insights to identify the root cause for a non-responsive application that was otherwise hard to detect.

Engage360, built by Persistent Systems and powered by Amazon Kendra, is a security-certified app on Salesforce AppExchange that lets you provide machine learning-powered search and recommendations right inside Salesforce Sales Cloud, Salesforce Service Cloud, and Salesforce Financial Services Cloud. It transforms how Salesforce users securely discover, access, and deliver relevant knowledge distributed across disparate enterprise information silos and content formats.

Once data is available in Amazon Redshift Serverless, businesses typically look at ways to turn data into business insights. This is where modern analytics providers such as ThoughtSpot provide value. With its powerful AI-based search, live visualizations, and developer tools and APIs for sharing embedded analytics, ThoughtSpot democratizes access to data by providing self-service tools for all users. Learn how to create a connection between Amazon Redshift Serverless and ThoughtSpot.

IBM Z and Cloud Modernization Stack on AWS provide a cloud-native experience to modernize development practices, helping developers adopt a unified set of tools and DevOps methodology. Learn how the Wazi components available in IBM Z and Cloud Modernization Stack provide modern experiences for analyzing, developing, and testing mainframe applications in an isolated way, implementing the DevOps philosophy for developers to gain speed and flexibility.

One of the most exciting evolutions in cloud computing is the proliferation of hybrid cloud and edge computing services. Learn how the Confluent for AWS Wavelength solution was developed to bring Confluent’s data-in-motion technology to the network edge. We’ll demonstrate how the solution extends Confluent for Kubernetes (CFK) to Amazon EKS self-managed nodes in AWS Wavelength Zones to create a geo-distributed Kafka cluster at-scale for industrial IoT and low-latency 5G use cases.

We know that data can help organizations get closer to customers and unlock new revenue streams. But in order to monetize data, companies need to be able to trust it. Collibra Data Intelligence Cloud helps organizations build trust in data across any source, for any user. Learn how Collibra Data Quality (DQ) on AWS is core to this solution, enabling organizations to get the added benefit of cloud-scale combined with a rich set of features.

Data analytics and data science are constantly described as a black box that only technical people understand. To overcome this, AWS offers a set of services that make it easier for any user to learn firsthand from the data. This self-service approach enables non-technical users without coding experience to be more autonomous in their analysis. Learn how Data Reply empowers organizations with advanced analytics to achieve outstanding outcomes through the right use of data.

A unified, autonomous, and fully digital airline operations solution can help mitigate challenges related to cost inefficiency, latency, or suboptimal decisions and their consequences, including cost, disruption, and customer dissatisfaction. TCS Aviana is an AI-based solution developed by Tata Consultancy Services (TCS) that enables airlines to have comprehensive operations visibility, digital collaboration, and data-driven decision-making through connected insights and intelligence.

Through the Pega Platform and Amazon SageMaker, you can easily streamline the development and operationalization of machine learning models to improve process automation. This allows customers to combine the strengths of cloud, data, and machine learning with AI-powered decisioning and smart workflow capabilities. It also enables customers to operationalize and monetize data and insight, drive process efficiency and effectiveness, and improve customer experience and value.

Many organizations stay on track and achieve objectives by conducting a constructive analysis of strengths and weaknesses, but revenue and profitability analysis are not easy tasks. Explore why Metrodata chose AWS as a trusted platform to build SAP analytics offerings such as revenue and profitability analysis. These offerings empower customers to make business decisions quickly and effectively to expand in new market opportunities and focus on key growth areas.