Cloud AI Platform Pipelines vs Hal9

Push-button installation via the Google Cloud Console; Enterprise features for running ML workloads, including pipeline versioning, automatic metadata tracking of artifacts and executions, Cloud Logging, visualization tools, and more; Seamless integration with Google Cloud managed services like BigQuery, Dataflow, AI Platform Training and Serving, Cloud Functions, and many others ; Many prebuilt pipeline components (pipeline steps) for ML workflows, with easy construction of your own custom components

Start by importing data from Google Sheets, Excel or any other service that supports exporting your data. Simply drag the type of data you have: CSV, Excel, or JSON and open the URL or file with your data; After importing your data, drag the chart and fields to visualize, is that simple. You can choose from bar, line, scatter, bubbles, wordclouds and many more charts; Forecast future values by dragging a prediction, select the field to predict, the type of prediction that best fits your needs and how many values to predict into the future, is that easy; If you want to go the extra mile, you can export your analysis to HTML and embed the results in any site that supports static HTML: Wix, WordPress, you name it. In this example, we use Hal9 and Google Analytics to visualize and embed our own worldwide daily product use