We have social media tiles for you to use. Make some noise on social media about your SAS Hackathon team and case.  ... View more

  Calling All Data Scientists The most important thing about data is what you do with it. This is your chance to work on real-life problems. We want you to tackle some of the most challenging business and humanitarian issues using SAS® Analytics, AI and open source on Microsoft Azure.  There’s no cost to participate.   Registration opens in November. Interested? Complete the interest form and we’ll notify you when it’s time to register.   Top three reasons you should participate: Collaborate with fellow coders: Everyone – from experienced data scientists to novice technologists to partners and SAS experts – will be using SAS and open source on Microsoft Azure. Accelerate - Develop your idea for the marketplace or deploy your solution into your own production after the Hackathon. Get free enablement resources: Take advantage of coaching on AI, cloud environments and industries with training courses and virtual learning labs.   Industry Tracks and Target audience  Developers, students, startup businesses, SAS customers and technology partners. Teams: Can be made up of people within your organization, your organization and a technology partner, or an individual looking to join a group. Tip: Form teams with multidisciplinary skills and backgrounds.   Use-case and Data centric  The SAS hackathon structure will hopefully create a “speedboat” for your hack and a new way to engage to solve real problems. Collaborate customers, partner ecosystem, students Build a new Team Evaluate use-cases& data Together Technology and Industry approach Timeline and milestones Registration opens November 1 Enablement January  Build March 15 - April 15 April - Record videos  Jury voting Industry Award June  SAS Explore Grand Prize Winner    Get inspired Watch the video's from 2022 Team Profiles from 2022   ... View more

The IoT analytical life cycle expands traditional analysis processing beyond investigation of stored data (i.e., at rest) to analytical investigation of streaming data (i.e., in motion) or at the edge. The combined capability of data management, streaming analytics execution, and intelligent decisioning enables fast and confident decision making from data, to discovery, to deployment.   SAS Analytics for IoT offers an optimized IoT solution ecosystem and addresses the entire analytical life cycle.     In this document we are focusing on the integrated process of model management and analytics deployment.   Key take-aways: Learn how to import ASTORE from models built in SAS Model Studio, SAS Studio, or Jupyter Notebook into SAS Model Manager Learn how to deploy ASTORE from SAS Model Manager in SAS Event Stream Processing Studio   Download the files to try it yourself! The CSV file for data and XML model file are available along with step by step instructions in GitHub. Take Me To GitHub ... View more

SAS ESP can be a bit overwhelming at first. The functionality is so vast that knowing where to begin is difficult. One of the best learning techniques is learning by example. The SAS Event Stream Processing Studio Examples GitHub repository provides several examples of ESP code that can be used in various scenarios. You can even edit the provided code and try things yourself.     There are 42 examples in the repository divided into four categories:   Getting Started   Basic   Advance   Analytics     The Getting Started and Basic examples are a great place to start. Each example covers a specific ESP technique and uses  a single ESP window. The Advanced examples are more complex and involve the use of multiple ESP windows. These examples are closer to “real-world” examples.    ESP supports numerous algorithms for performing analytics on streaming data. The Analytics section of the repository includes an example for many of these algorithms.  The SAS Help Center contains step-by-step instructions for many of the Analytics examples.     Be sure to check out this GitHub repository as these examples will surely improve your ESP skills!   ... View more

One of the best features of SAS ESP is that it can be integrated with many third-party environments. One of these environments is Microsoft Power Automate.     Microsoft Power Automate (formerly Microsoft Flow) allows you to create automated workflows that use a trigger and then perform an action. It has 500 flow connectors to the entire Microsoft family, several third-party products, and any publicly available API. You can use ESP as the trigger to execute a flow or use ESP to receive events as the action portion of the flow.       Azure Event Hubs is a data streaming platform and event ingestion service. It sits between event publishers and event consumers and manages the event stream between the two. The above diagram illustrates Event Hubs providing bi-directional flow between ESP and Power Automate.     The Integration of SAS Event Stream Processing with Microsoft Power Automate using Microsoft Azure Event Hubs GitHub site provides the information you need to connect ESP with Power Automate through Azure Event Hubs including:   Prerequisites   Installation   Finding your Event Hubs connection strings   Connecting ESP to Azure   ... View more