Create Analytics Apps for Enterprise
How the Analytic Application of Sparkflows becomes a Performance Management
Fire Insights enables you to quickly develop an Analytics Application for analysis of a buisness process like Sales Pipeline Analysis, Accounts Payable Analytics or risk adjusted profitable analysis in support of decision making.
With Application Analytics, build a user interface screen with drag & drop and add various stages to execute the whole application.
Build UI with Drag and Drop
Various stages can be added and they can also be rearranged using the drag and drop.
Add column component and divide in two columns.
Add select, text-field, select boxes, buttons etc. components.
Execute the notebook with all parameters added in the App.
Integrate with Databricks Notebook
Example of Housing Analytics
The Web App in Fire Insights can trigger a Notebook in Databricks.
Fire Insights passes 2 parameters to the Notebook:
Add wheel file to your Databricks Notebook
Add the wheel file to your Databricks Notebook. This is to enable using the Fire Insights API’s for sending data to it.
Outputing details to Fire Insights
The Databricks Notebook can output text, tables and charts to be dispalyed in Fire Insights.
Running Analytics App
Once the Analytics App has been created, they can be executed
with the below steps for executing an Analytics App.
Click on Analytics App Name
Go through the various stages
Easily scale horizontally to petabytes of data. Sparkflows also allows you to control the persistence level of DataFrames, execution parameters etc. to ensure you are not limited in any way.
Sparkflows processors are written to run at extreme scale. Save millions of dollars by running faster with efficient algorithms.
Deploy and Run
Run your workflows with one click, schedule them or trigger them by event. Easily view the results of past executions.
Or run them with the scheduler of your choice as Sparkflows is an open system.
Save, Load and Deploy your ML models.
Sparkflows is a collaborative data science and analytics platform. Teams can work together to build Applications. Data Analysts, Data Scientists and Data Engineers can iterate, build and deliver data products seamlessly.
Multiple groups with different permissions can work together on an Application in Sparkflows. From preparing data to analytics to building predictive models to visualization and dashboards, users can seamlessly accomplish them in an Application.
Integrate with your other systems using the powerful REST API's. Create workflows, run them, view models and execution results using the REST API's.
Perform Predictive Analytics
Deploy & Run
Provides algorithms developed from the ground up for distributed computing.
Random Forest, GLM, GBM, XGBoost, GLRM, Word2Vec and many more.
Provides extensive Machine Learning in Python
SVM, Nearest Neighbors, Random Forest, SVR, Ridge Regression, Lasso, K-Means, Spectral Clustering, Mean-Shift and many more.
Provides fully managed Machine Learning System.
Apache MXNet, TensorFlow, PyTorch, and Chainer.Scikit-learn and SparkML by providing pre-built Docker images.