Quick start: Build, run, and deploy a Decision Optimization model
Quick start: Build, run, and deploy a Decision Optimization model You can build and run Decision Optimization models to help you make the best decisions to solve business problems based on your objectives. Read about Decision Optimization, then watch a video and take a tutorial that’s suitable for users with some knowledge of prescriptive analytics, but does not require coding. Your basic workflow includes these tasks: 1. Open your sandbox project. Projects are where you can collaborate with others to work with data. 2. Add a Decision Optimization Experiment to the project. You can add compressed files or data from sample files. 3. Associate a Watson Machine Learning Service with the project. 4. Create a deployment space to associate with the project's Watson Machine Learning Service. 5. Review the data, model objectives, and constraints in the Modeling Assistant. 6. Run one or more scenarios to test your model and review the results. 7. Deploy your model. Read about Decision Optimization Decision Optimization can analyze data and create an optimization model (with the Modeling Assistant) based on a business problem. First, an optimization model is derived by converting a business problem into a mathematical formulation that can be understood by the optimization engine. The formulation consists of objectives and constraints that define the model that the final decision is based on. The model, together with your input data, forms a scenario. The optimization engine solves the scenario by applying the objectives and constraints to limit millions of possibilities and provides the best solution. This solution satisfies the model formulation or relaxes certain constraints if the model is infeasible. You can test scenarios using different data, or by modifying the objectives and constraints and re-running them and viewing solutions. Once satisfied you can deploy your model. [Read more about Decision Optimization](https://dataplatform.cloud.ibm.com/docs/content/DO/DOWS-Cloud_home.html) Watch a video about creating a Decision Optimization model ![Watch Video](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/lc-video.png) Watch this video to see how to run a sample Decision Optimization experiment to create, solve, and deploy a Decision Optimization model with Watson Studio and Watson Machine Learning. Video disclaimer: Some minor steps and graphical elements in this video might differ from your platform. The user interface is frequently improved. This video provides a visual method to learn the concepts and tasks in this documentation. Try a tutorial to create a model that uses Decision Optimization In this tutorial, you will complete these tasks: * [Task 1: Open a project.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-do.html?context=cdpaas&locale=enstep01) * [Task 2: Create a Decision Optimization experiment in the project.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-do.html?context=cdpaas&locale=enstep02) * [Task 3: Build a model and visualize a scenario result.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-do.html?context=cdpaas&locale=enstep03) * [Task 4: Change model objectives and constraints.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-do.html?context=cdpaas&locale=enstep04) * [Task 5: Deploy the model.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-do.html?context=cdpaas&locale=enstep05) * [Task 6: Test the model.](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-do.html?context=cdpaas&locale=enstep06) This tutorial will take approximately 30 minutes to complete. Expand all sections * Tips for completing this tutorial ### Use the video picture-in-picture Tip: Start the video, then as you scroll through the tutorial, the video moves to picture-in-picture mode. Close the video table of contents for the best experience with picture-in-picture. You can use picture-in-picture mode so you can follow the video as you complete the tasks in this tutorial. Click the timestamps for each task to follow along.The following animated image shows how to use the video picture-in-picture and table of contents features: ![How to use picture-in-picture and chapters](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/pip-and-chapters.gif){: width="560px" height="315px" data-tearsheet="this"} ### Get help in the community If you need help with this tutorial, you can ask a question or find an answer in the [Cloud Pak for Data Community discussion forum](https://community.ibm.com/community/user/cloudpakfordata/communities/community-home/digestviewer?communitykey=c0c16ff2-10ef-4b50-ae4c-57d769937235){: new_window}. ### Set up your browser windows For the optimal experience completing this tutorial, open Cloud Pak for Data in one browser window, and keep this tutorial page open in another browser window to switch easily between the two applications. Consider arranging the two browser windows side-by-side to make it easier to follow along. ![Side-by-side tutorial and UI](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/tutorial-side-by-side.png){: width="560px" height="315px" data-tearsheet="this"} Tip: If you encounter a guided tour while completing this tutorial in the user interface, click Maybe later. [Back to the top](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/get-started-do.html?context=cdpaas&locale=envideo-preview) * Task 1: Open a project You need a project to store the data and the AutoAI experiment. You can use your sandbox project or create a project. 1. From the navigation menu ![Navigation menu](https://dataplatform.cloud.ibm.com/docs/content/wsj/getting-started/images/navigation-menu.svg){: iih}, choose Projects > View all projects 1. Open your sandbox project. If you want to use a new project: 1. Click New project. 1. Select Create an empty project. 1. Enter a name and optional description for the project. 1. Choose an existing [object storage service instance](https://dataplatform.cloud.ibm.com/docs/content/wsj/admin/storage-options.html){: new_window} or create a new one. 1. Click Create. 1. When the project opens, click the Manage tab and select the Services and integrations page. 1. On the IBM services tab, click Associate service. 1. Select your Watson Machine Learning instance. If you don't have a Watson Machine Learning service instance provisioned yet, follow these steps: