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AnalyticsEarth
เข้าร่วมเมื่อ 3 ก.ค. 2017
Qlik 2 DataRobot
DataRobot is a Automated Machine Learning platform used by a number of Qlik customers. This document outlines how the integration between Qlik and DataRobot can unlock insight through the power of integration using the broad APIs available.
Overview
Businesses want to not only understand how they are performing, but also look to the future and make decisions based upon predictions. Platforms such as DataRobot provide an easy way for a broad range of business professionals to make these predictions, however in isolation there can be challenges in both ingesting data and integrating the predictions into the analytic platforms used by the broader business to inform decision making.
That is where the integration outlined here comes in; seamlessly and securely selecting and sending data from Qlik Sense to DataRobot directly from an application without any manual exports required.
Once a predictive model has been created and deployed in DataRobot, making predictions against the new data being generated each day is critical. Through a seamless request in a Qlik Sense application refresh, the new predictions are associated in your data model to drive insight.
All of this is possible using the Qlik2DataRobot client and server-side extensions, which leverage the unique integration capabilities of the patented Qlik associative engine. These extensions are available now for you to download for free, under MIT open source licence permission.
Capabilities
Send associated data securely from Qlik to DataRobot
Identify data for analysis directly from your Qlik Sense application using the associative difference, before sending it securely to DataRobot directly from the Qlik engine
Automated model scoring within a Qlik application reload
Seamlessly score new production data against your chosen model deployments in DataRobot, all seamlessly from the Qlik reload process without the need for external triggers or data exports
Real time scoring direct from a Qlik dashboard
Simulate your model predictions directly from a Qlik dashboard using the live analytic connector expressions within your charts
Overview
Businesses want to not only understand how they are performing, but also look to the future and make decisions based upon predictions. Platforms such as DataRobot provide an easy way for a broad range of business professionals to make these predictions, however in isolation there can be challenges in both ingesting data and integrating the predictions into the analytic platforms used by the broader business to inform decision making.
That is where the integration outlined here comes in; seamlessly and securely selecting and sending data from Qlik Sense to DataRobot directly from an application without any manual exports required.
Once a predictive model has been created and deployed in DataRobot, making predictions against the new data being generated each day is critical. Through a seamless request in a Qlik Sense application refresh, the new predictions are associated in your data model to drive insight.
All of this is possible using the Qlik2DataRobot client and server-side extensions, which leverage the unique integration capabilities of the patented Qlik associative engine. These extensions are available now for you to download for free, under MIT open source licence permission.
Capabilities
Send associated data securely from Qlik to DataRobot
Identify data for analysis directly from your Qlik Sense application using the associative difference, before sending it securely to DataRobot directly from the Qlik engine
Automated model scoring within a Qlik application reload
Seamlessly score new production data against your chosen model deployments in DataRobot, all seamlessly from the Qlik reload process without the need for external triggers or data exports
Real time scoring direct from a Qlik dashboard
Simulate your model predictions directly from a Qlik dashboard using the live analytic connector expressions within your charts
มุมมอง: 1 125
วีดีโอ
Conditional show and hide a layer with Picasso Designer
มุมมอง 536 ปีที่แล้ว
A How To Guide for Picasso Designer, an extension for Qlik Sense. to download visit: github.com/AnalyticsEarth/aePicassoChart
Styling a Chart Layer with Picasso Designer
มุมมอง 1196 ปีที่แล้ว
A How To Guide for Picasso Designer, an extension for Qlik Sense. to download visit: github.com/AnalyticsEarth/aePicassoChart
Creating a reference line with Picasso Designer
มุมมอง 646 ปีที่แล้ว
A How To Guide for Picasso Designer, an extension for Qlik Sense. to download visit: github.com/AnalyticsEarth/aePicassoChart
Adding a Layer Legend with Picasso Designer
มุมมอง 726 ปีที่แล้ว
A How To Guide for Picasso Designer, an extension for Qlik Sense. to download visit: github.com/AnalyticsEarth/aePicassoChart
Using a Picasso Designer Chart Template
มุมมอง 1676 ปีที่แล้ว
A How To Guide for Picasso Designer, an extension for Qlik Sense. to download visit: github.com/AnalyticsEarth/aePicassoChart
Introducing Picasso Designer for Qlik Sense
มุมมอง 7K6 ปีที่แล้ว
Picasso Designer is an extension to aid building complex charts based on the Picasso.JS library without having to write any code or understand the Picasso JSON structure. The extension also provides support for selections against the chart for the expected user experience in Qlik Sense. This video provides a demo of some of the feature available in the current BETA release.
AAI Expression Builder
มุมมอง 3.5K7 ปีที่แล้ว
AAI Expression Builder The AAI Advanced Analytics Expression Builder is a Qlik Sense extension used to create advanced analytics expressions as master items and wrap these in to a pre-built visualization. These visualizations use native chart types and can be edited either as a master item or un-linked and customized. How to get started? Install the extension through the Qlik Sense QMC. Create ...
Hi, on the github page there is a scatter plot and best fit line, can you show how you achieved this?
How do you export it to picasso.js objects?
Great! How do we add value labels in Picasso layers?
Excellent function! thanks for sharing!
Love it, Great work.Many Thanks