© 2019 NTT DATA Mathematical Systems Inc.

15 Feb. 2019NTT DATA Mathematical Systems, Inc.

Data & Intelligence Global One Team

NTT DATA Mathematical Systems, Inc. ‘Deployment’

2© 2019 NTT DATA Mathematical Systems Inc.

1. Optimization Let’s PoC

2. Analytics Self-service

3. Deployment Platform to appear

NTT DATA Mathematical Systems Inc. offers you

3© 2019 NTT DATA Mathematical Systems Inc.

1.Our History

2.VAP’s Concepts• Platform for Mathematical Solutions

• Cycle of Trial-and-Error Phase and Deployment Phase

3.VAP’s Future• New VAP is Coming

‘Deployment’ : NTT Data Mathematical Systems, Inc.

4© 2019 NTT DATA Mathematical Systems Inc.

Our History

5© 2019 NTT DATA Mathematical Systems Inc.

Visual Analytics Platform is a Platform for Mathematical Solutions

2000 2005 2010 2015 2020

Initially born in 2002as general data mining tool

Needed by professionals in various tradesas powerful Visual Programming Environment

Began to be developed in the late 1990s

6© 2019 NTT DATA Mathematical Systems Inc.

Their Needs and Desires Become Increasingly Complicated

2000 2005 2010 2015 2020

Providing functions for Mathematical Solutionsas Combinations

Capable of Rapidly Deploying and Using the solutions made

Reborn in 2011 as integrated Platform for Mathematical Solutions

Data Mining Machine Learning

OptimizationSimulation

7© 2019 NTT DATA Mathematical Systems Inc.

VAP’s Concepts

8© 2019 NTT DATA Mathematical Systems Inc.

SimulationOptimizationAnalysis

Powerful Platform for Mathematical Solutions

These products work on the Visual Analytics Platformand can connect with each other.

Platform for Mathematics + Computer Science

BayoLinkSNuoriumOptimizer

FIOPT

S-QuattroSimulation

System

VisualR

Platform

Text Mining Studio

PatentMiningeXpress

VisualMiningStudio

Big DataModule

Credit NASA

DeepLearner

9© 2019 NTT DATA Mathematical Systems Inc.

VAP has Great Advantages

VAP Web Server

You can make web applications from your analytics flow on VAP with ease.

You can use our products seamlessly by putting product icons on the ‘VAP project board’ and connecting them with arrows.

10© 2019 NTT DATA Mathematical Systems Inc.

The application of analytics in business is one of the most valuable!

Collecting and redoing analysis of feedbacks are also just as valuable!

PDCA Cycle of Data Analytics

Plan

• Make & Change analytics flow

Do• Deployment• System Implementation

Check

• Check effectivity

Action

• Finding problems

PDCA cycle of data analytics is a key point of making values

by using the analytics system.

11© 2019 NTT DATA Mathematical Systems Inc.

In the case of Customer Scoring

Receive Orders!

Not Receive Orders…I made it!

I would like to model customer scoring based on POS data

I’m contacting customersin the order of their scores.

The performance is reasonably good. Is it OK and Completed?

NO IT’S NOT

We have to re-model and refine based on feedback because of The Models Tendency To Become Rapidly Outdated!

analyst

contact center

12© 2019 NTT DATA Mathematical Systems Inc.

Cycle of Trial-and-Error Phase and Deployment Phase

Analytics (Trial-and-Error) Phase Deployment Phase

• Routine execution

• Frequent execution

• Fixed parameter

• Fixed View

• Fixed format

What users do

• Simple UI

• Intelligible UI

• Clear result view

• Parameter Tuning UI (Just a little)

• Cooperating with other systems

What they need

• Analytics design

• Changing data, type, format, etc…

• Model selection

• Parameter Tuning

• View selection

What users do

• Making analytics flow Flexible

• Partial execution

• Many models and algorithms

• Flexibility of parameter tuning

• Many graphs

What they need

WithFeedbacks

WithEase

13© 2019 NTT DATA Mathematical Systems Inc.

VAP’s Future

14© 2019 NTT DATA Mathematical Systems Inc.

Parallel Execution and Multi Processing

Unlimited executions per user

Multi processing is possible in execution (depending on PC)

Multi Layers

Various combinations in your needsREST API/Socket.IO/Python API

Multi Platform

Frontend implemented by HTML5

Backend implemented by Node.js and Python(Excepting analytic algorithms)

Windows/Linux/Mac OS (2021 Later)

Multi Language

Japanese/English/Chinese (2021 Later, or 2020 depending YOUR NEEDS)

New VAP is Coming!

15© 2019 NTT DATA Mathematical Systems Inc.

New VAP Architecture

Linux Windows Mac OS Others…

on-premises AWS Other Clouds…

Browser

VRPBDM NuOPTTMS BayoLink S4

GUIFor OtherApplication

WEB Server

GUI ForData

Pre-Processing

REST API

Socket.IO

VMS

Python API

Task Management Layer

Others...

OtherApplication

Client Side

Server Side

OS/HW

Deep Learner

GUI ForAnalysis

GUI ForOptimization

GUI ForSimulation

Well designed GUI for domain specific modeling

Selectable interconnections as your system needs

16© 2019 NTT DATA Mathematical Systems Inc.

Operation of New VAP

Platform

ServerInternalconnection

Remotedesktop

Platform

Server

Network

Network

Inn

ovate

!

Now New VAP

Stand Alone Edition

Client-Server Edition

Stand Alone Edition

Client-Server Edition

17© 2019 NTT DATA Mathematical Systems Inc.

Combinations of New VAP

What is a Characteristic of Requests Your System Needs?

Characteristic Solution

High Load and Low Frequency REST API

Low Load and High Frequency Socket.IO

Embedding in Edge etc. Python API

New VAP offers

Best Solutions for you needs!

18© 2019 NTT DATA Mathematical Systems Inc.

REST API and Socket.IO in Use Cases

Platform

ServerN

etw

ork

- Calling scheduled tasks, such as daily tasks

- Offering GUI

REST API

Socket.IO

Calling Asynchronouslyand Bidirectionally

Business System

Edge

WITHOUT CHANGESyou can use solutions you have made whenever!

19© 2019 NTT DATA Mathematical Systems Inc.

Python API in a Use Case

from msi.common.streaming import Serverfrom msi.common.dataframe import DataFramefrom msi.vms.modeling import load_model

class PredictServer(Server):def __init__(self, model, port):

super().__init__(self, port)self.__model = model

def message(self, request, response):record = DataFrame(request.message)model = self.__modelfitted = model.predict(record)response.json(fitted)

dtree = load_model(“pretrained_dtree_model”)server = PredictServer(dtree, 40000)server.serve_forever()

Python API

Others...

Call directly

VRP

BDM

NuOPT

TMS

BayoLink S4

VMS Deep Learner

EdgeSensors andControllers

Processing sensor streams and

Controlling based on analyzed feedback

Standalone operationor

Rapid response needed

20© 2019 NTT DATA Mathematical Systems Inc.

New Visual Analytics Platformis

Coming Soon.

Don’t miss it!

Experience accelerating your businesson cycles of trial-and-error and deployment

with New VAP.

© 2019 NTT DATA Mathematical Systems Inc.