Getting to Know Your Environment¶
Teradata’s AnalyticOps (AOPS) framework provides an easy-to-use web-based user interface (UI) and a command-line interface (CLI) to handle end-to-end pipelining of data science workflows.
This guide introduces you to the workspace environment of AnalyticOps framework.
AnalyticOps Accelerator (AOA) landing page is our browser-based landing page that allows you to access all the applications that are required to work in AnalyticOps environment.
Open the AnalyticOps Accelerator Landing page.
The landing page displays.
You can use all products and features as described in the table below.
|Demo Environment||Lets you open the demo environment. The demo environment is created to use and test internally, and is updated frequently.|
|Master Environment||Lets you open the master environment. The master environment is ready to release and contains only the finalized and tested changes.|
|AnalyticOps||Lets you open AnalyticOps UI. Teradata AnalyticOps (AOps) UI provides simple controls for creating new projects, adding new models to these projects and training, evaluation, approval and deployment of these models.|
|JupyterHub||Run use cases from a Teradata-managed object store using sample Jupyter notebooks. You can also create your own Jupyter notebooks to write and execute SQL, Python, or R code.|
|Git Code||Access to Github repository of Teradata AnalyticOps Core Services.|
|Demo App||Lets you access an example demo app.|
|API||Provides a link to AnalyticOps API Documentation on Swagger.|
|CI||Allows you to access Jenkins.|
|Schedular||Allows you to access Airflow Schedular.|
|FAQs||Lets you access the AnalyticOps FAQs available at Teradata Consulting Services Portfolio page.|
|Documentation||Lets you access the HTML content of this guide, Teradata AnalyticOps Getting Started Guide.|
|Video Tutorials||Lets you watch short videos about available features in Teradata AnalyticOps.|
(Comment: The description taken from Teradata Vantage Documentation: https://docs.teradata.com/r/dLArVI09J62c8byzVbHMtw/wkUkrBazpKbulpMlPw_jlg)
JupyterHub is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations, and narrative text using notebooks. Teradata provides SQL extensions for JupyterHub that allow you to do the following:
Navigate database objects through a visual user interface
Run queries, display result sets, and manage SQL history
Run magic commands that enhance the user experience, including a chart magic for visualization and dataload magic for loading data into Teradata Vantage
Provides an integrated Teradata parser for SQL syntax checking and context-sensitive code completion
Various sample notebooks allow you to run SQL, Python, or R code and create charts and graphs. Beyond the sample notebooks, you can also create your own SQL, Python, or R notebooks and connect to your own storage container to load data.
Teradata Package for R (tdplyr) and Teradata Package for Python (teradataml) provide access to powerful Vantage analytic functions and provide Vantage in-database analytic capabilities. They combine the benefits of the open source language environment with the massive parallel processing capabilities of Vantage.
To access JupyterHub from the landing page:
Select Master Environment on the landing page.
To open the JupyterHub environment, click JupyterHub.
The JupyterHub sign-in page opens in a separate browser window.
Click the Sign in with AWSCongnito button. The Jupyter lab environment opens in a separate browser window.
(Comment: Further details of the environment needed here?)
The AnalyticOps UI provides simple controls to create new projects, add new models to these projects and train, evaluate, approve and deploy these models.
To open the AnalyticOps Home page, click AnalyticOps on the landing page.
The AnalyticOps sign-in page displays in a separate browser window.
Enter your User Name and Password.
Click Sign In to login. The AnalyticOps Home page displays. The Home page includes the following areas.
1. Top Pane
The Top pane displays the product name and logo, session details of the logged-in user and an option to logout from the session.
2. Navigation Bar
The Navigation bar displays on the left side and lets you navigate to your required modules. The Projects module is opened by default. All the remaining modules can be accessed when one of the projects is selected from the List of Projects.
The Workspace is where you perform the tasks for each module. It can be a list of Projects, Models, Deployments, Dataset templates, Datasets, Jobs, Model History, or Connections depending on the opened module.
The Actions area displays all the actions that can be performed on the content in the workspace.
The top pane provides you the following information:
Product name and logo.
Session details related to the logged-in user.
The option to logout from AnalyticOps.
To view the current session details:
Click the More icon on top right corner of the Top pane. A dropdown displays.
Click Session Details. The Session Details dialog displays where you can see the logged-in user name and copy the listed tokens.
To logout from AnalyticOps:
Select Logout from the drop-down. You log out and the sign-in page displays.
The workspace is where you perform the tasks for each module. All the contents related to a module display in its workspace. Clicking on a module displays its workspace.
Click Deployments in the Navigation bar. The Deployment’s workspace displays all the active deployments in the Demo project.
The Actions area is located directly below the Top pane. This area displays the tools to perform different actions on the items available in the Workspace. These tools are dynamic and display actions that are specific to the selected module or item.
The Models workspace displays the actions:
Define BYOM Model
Edit BYOM Model