MIST ALLOWS SPARK FUNCTIONS TO BE DEPLOYED IN MULTI-TENANT MICROSERVICES ARCHITECTURE.
Turn Analytics into Products
Increase the return on investment of big data analytics by building end user products on top of those.
Expose data science and algorithms to enterprise apps
Makes it easier for developers to tap into big data models from web apps by addressing those as APIs.
Simplify the handoff between business and data scientists
Deliver forecasting apps, smart alerts, and prescriptive insights that business can understand instead of statistical reports and raw algorithms.
Lets business interact with big data
Write a simple web app that lets business users type input into the model and provide feedback. Then the data scientist tunes the model based on that. Provides an easy interface that does not require coding.
Hide complex big data details
Regular, non-big-data web programmers can run complicated big data pipelines and models without having to understand distributed computing, machine learning, statistics, and advanced mathematics.
Build productivity tools for data scientists
The advanced Mist user can use Mist to develop their own hosted notebooks, ETL builder, or write other productivity tools for data analysts.