Add Advanced Analytics to Your BI Apps

Vincent Vikor – Consulting

Why Advanced Analytics ?

Companies that inject big data and

analytics into their operations show

productivity rates and profitability that

are 5% to 6% higher than those of

their peers.

https://hbr.org/2012/10/making-advanced-analytics-work-for-you

http://ai.arizona.edu/mis510/other/Big%20Data%20-%20The%20Management%20Revolution.pdf

While many companies develop different systems for Advanced

Analytics and Business Intelligence, integrating both worlds remains a

challenge.

Stuck in your Momentum?

MicroStrategy Bridges the Gap

Advanced Analytics Spectrum

Descriptive

What Happened?

Diagnostic

Why did it happen?

Predictive

What will happen?

Prescriptive

What should happen?

Analytical functions

Math, OLAP & Financial,

Operators & Statistics

Descriptive models

Cluster & Association,

Link & Factor Analysis,

Anomaly Detection

Predictive models

Regression, Time Series,

Classification

Optimization

Simulation, Rule

Systems, BPM

MicroStrategy Analytic Map

MicroStrategy

Functions Library

MicroStrategy Native

Data Mining Features

R Analytics

What is R

R is a language and environment for statistical computing and graphics

Over 5,000 packages:

Calculations and graphics

Millions of practitioners

Vibrant user communities

Top choice of data scientists worldwide

1 2 3

R Integration Pack

R is a language and environment for

statistical computing and graphics

Write R script

Capture its Signature

Deploy as a metric

Integrate R in 3 Steps

MicroStrategy

Desktop MicroStrategy

Web

MicroStrategy

Mobile

MicroStrategy

Office

Competitive Advantages

Usable in any MicroStrategy Environment

One Analytic: Multiple Outputs, Multiple Applications,

Standalone Scripts

Flexible applications with

parameters/Prompts/Transaction services

Transparent R environment

Error Logging

Usable in any MicroStrategy Environment

Analytics Desktop Web/Visual Insight Developer

Mobile Available on-premises or Cloud

One Analytic: Multiple Applications via Standalone Scripts

Don’t re-invent the wheel

Eg. Use the same clustering analytic to cluster

stores, employee, customers and products

Maintain and update multiple applications through a

single script

• Maintenance nightmare

• Rife with errors

• Complex for end-users

• Edits must be made within each calculation

• Easy to Maintain

• Error Proof

• Abstracts complexity

• Edits made in a single location

Inline scripts Standalone scripts

Flexible applications with Parameters/Prompts/Transaction services

Parameters

Submit scalar values at metric execution time, e.g. (Number

of Clusters, % Confidence Interval, Train vs Score)

Prompts

Utilize all types of prompts to maximize flexibility, e.g.

(Choose a metric to forecast, choose a level at which to

aggregate)

Transaction Services

Score on-the-fly by entering in variable values on your mobile

device, e.g. (Customer applies for a loyalty credit card, enter

attribute values, and predict the risk for a default.)

Transparent R environment

Access to File System

• Big Data File System

• Read/Write data files and images

• Persist R environment and models for

further investigation

• Send insights to data scientists for

validation

Silent Installations of R Package

• Don’t burden administrators with

package configuration

Error Logging

No Error Message Reported: Errors Logged and Reported:

Demo

Additional resources

https://rintegrationpack.codeplex.com

Join our Webcasts

http://www.microstrategy.com/us/events/webcasts

Try us now today

Thank you.