As the world moves to an era where data is the most valuable asset, being able to efficiently process large volumes of data in real time can help to gain a competitive advantage for businesses. Then, making business decision within milliseconds has become a mandatory need in many domains. Streaming analytics play a key role in making these decisions and is also a vital part of the digital transformation of businesses. WSO2 Stream Processor provides a high performance, lean, enterprise-ready streaming solution to solve data integration and analytics challenges. It provides real-time, interactive, predictive and batch processing technologies to deal with large volumes of data and generate meaningful decisions/output from it. This session explains how to enable digital transformation through streaming analytics and how easily streaming applications can be implemented.
- The Architecture of WSO2 Stream Processor
- Understanding streaming constructs
- Patterns of processing data in real time, incremental and with intelligence
- Applying patterns when building streaming apps
- Deployment patterns
Simplify Feature Engineering in Your Data WarehouseFeatureByte
Feature Engineering is critical to successful delivery of AI solutions. Crafting relevant features from organization data requires business domain knowledge and creativity, powered by human capital in data science teams.
With growing adoption of machine learning and AI in organizations, there is a pressing need to develop processes around ML development and deployment to maximize productivity with limited resources. While there is no lack of tools for ML model management, solutions for feature engineering remains inadequate.
In this presentation, we outline our approach and design to make feature engineering efficient, repeatable and enjoyable for data science practitioners so they can experiment and iterate fast, without overlooking important issues such as scalability, deployment and auditability.
Gaining actionable insights in real time enables organizations to grab opportunities and omit threats. Sensing the world, detecting actionable insights, and acting upon them has now become far easier than ever with the advancements of streaming SQL. Below are the topics discussed in this slide.
- Building stream processing applications using streaming SQL
- Deploying and monitoring streaming applications
- Scaling streaming applications
- Building domain specific business UIs
- Visualizing stream processing outputs via dashboards
This is a run-through at a 200 level of the Microsoft Azure Big Data Analytics for the Cloud data platform based on the Cortana Intelligence Suite offerings.
[WSO2Con USA 2018] Patterns for Building Streaming AppsWSO2
This slide deck explains how to enable digital transformation through streaming analytics and how easily streaming applications can be implemented.
Watch video: https://wso2.com/library/conference/2018/07/wso2con-usa-2018-patterns-for-building-streaming-apps/