fujitsu world tour 2017 - analytics in digital world

0 Copyright 2017 FUJITSU

Fujitsu World Tour 2017

Power of Information Analytics in Digital world


Experience the power of information

Pankaj Sharma

Sr. Solution Architect – High perfromance Computing & Big Data Solutions

Abhishek Dixit

Head of High Performance Computing and Big Data Business

Experience the power of data analytics on information to meet the digital transformation requirement.


Actuate

Data

Algorithms,

Al technology • Learning, Insights

• Decision support

The Internet

of Things (IoT) • Connect physical world

• Sensing

Today’s view of technology in digital world

Copyright 2017 FUJITSU

The IoT digitalizes physical objects, enabling the collection of digital data

The Big data does analysis of this data & produces useful insights, enabling better control

2


Key industry touch points P

ain

Po

int

#1

Pa

in P

oin

t #

2

Being able to collect & store data effectively

The Internet of Things Unstructured data Database infrastructure

Being able to draw insights from data

Real-time & predictive analytics Data visualization Using data to solve a problem

Pa

in P

oin

t #

3

Being able to leverage data across the business

Businesses need to be data-driven Data experts need to collaborate Data leaders need to be appointed


Digitization – The Challenges Organizations are facing different challenges in shifting to digital

world


Leadership & Talent Security Complexity Adaption


Our approach

Copyright 2017 FUJITSU 5

People Information Infrastructure (Things)

Bring together 3 dimensions to create innovation


Fast Time-to-Information

Data Discovery

Real-time Analytics

Visualization

Big Data solutions empower innovation

Traditional analytics focus on analyzing historical data. Big Data extends this concept to include real-time analytics of in-flight transitory data

CIOs recognize the importance of data but understand that data is useless without having the tools to make sense of it


Big Data value chain

Big Data

Collect

Stream

Structured &

unstructured data

Devices,

sensors,

Internet of Things

Cleanse

Transform

Analyze

Find

Decide

Navigate

Research &

development,

science

Operation,

automation,

production

Interactive

reporting,

advertising

Use cases, solution architecture, processes: Fujitsu’s approach

Social media,

open data,

linked data


Pure-play Hadoop distribution vendors

Hadoop becoming mainstream

Cloudera, MapR and Hortonworks innovate to meet enterprise demands

Enterprise IT vendors offering Hadoop distributions: Hadoop strategy & eco system in place

Big Data solution providers: Managed hosting and cloud vendors offer Big Data solutions

In-memory technology and streaming concepts accelerate

Market momentum:

50B connected devices by 2020

2016: Hadoop no longer a hype

“The broad and active utilization of big data requires the empowerment of business users and citizens by tools answering their questions and interests in a self-service way. Such environments will unveil huge values from big data and will help to democratize the access to information.” Dr. Fritz Schinkel, Fujitsu

- Distinguished Engineer

- Head of Big Data Competence Center


Vertical snapshot

Gain knowledge

from information Transportation

• Predictive maintenance for logistics

• Analytics allows airlines to predict flight times with greater accuracy

Retail

• Stores use analytics to streamline inventory management

• Algorithms enable retailers to generate appropriate offerings in real-time

Target Industries Finance

• High-speed trading

• Improve risk management

Public Sector

• Fraud detection to catch benefit cheats

• Next level traffic management

Automotive

• Foundation for driverless cars

• Cars contributing to IoT (Internet of Things)


Cybersecurity Target Industries: Large Public Networks, Government, Financial, Telecom, Utilities, etc.

Real Time

Detect

Attacks in

Real Time

Prevent

Threats in

Real Time


Fraud Detection Target Industries: Financial, Insurance, Government, etc.

Patterns

Words

External

Information

Internal

Information


Targeted Advertising Target Industries: Retail, Manufacturing, Service, Financial, etc.

Personalized Offers to Consumers

Data sources: • Social networks • CRM • Sales Orders • POS • Web Logs • Online profiles • etc.

Social Media

Data

Multi-

Structured

Data


Trace and interprets online

discussions in social media to Gather customer feelings

on: Your organization

Your Brand

Your Products and Services

Your Competition

Other events that may impact

corporate performance: politics,

disasters, large-scale events, etc.

Sentiment Analysis

or ?

Decide /

Improve

Target Industries: Retail, Manufacturing, Service, Financial, etc.

Like

Dislike

Want

Need


Predictive Maintenance Target Industries: Manufacturing, Natural Resources, Utilities, Telecommunication

Real Time

Improve Operations, Reduce Waste,

Identify Bottlenecks

Control Manufactured Product Quality

Monitor Asset Performance

Avoid Operations Downtime

Predict Asset Failure

Machine / Sensor Data

Predictive Models/Machine Learning


Usage Monitoring Target Industries: Manufacturing , Natural Resources, Transport, Utilities

Monetize Data

Monitor/Control

Optimize

Machine / Sensor Data


Big Data infrastructure reference architecture: Choose platform according to business case

Consolidated data Distilled essence Applied knowledge Various data

Extract, Collect Cleanse, Transform Decide, Act Analyze, Visualize

Data Sources Analytics Platform Access

Batch

processing

platform

Event

processing

platform

Fast response

platform

Data bases

Application server

Web content

Sensor data

Apps Services Queries

Visualization Reporting

Notification


Big Data infrastructure reference architecture

Consolidated data Distilled essence Applied knowledge Various data

Extract, Collect Cleanse, Transform Decide, Act Analyze, Visualize

Data Sources Analytics Platform Access

Batch

processing

platform

Event

processing

platform

Fast response

platform

Data bases

Application server

Web content

Sensor data

Apps Services Queries

Visualization Reporting

Notification


Hadoop readiness

What is the industry saying about Hadoop?

A one-size-fits-all approach does not work with Hadoop

IT departments are unsure how to manage it

Businesses need people with the right expertise

Hadoop is an undiscovered concept to many non IT-experts

Solution

FUJITSU PRIMEFLEX helps to solve these business needs per inclusion of analytic features and services


PRIMEFLEX for Hadoop solution stack

Software stack Business oriented analytic (spreadsheets) Hadoop core: Map Reduce / file system Streaming and In-memory technologies

Hadoop platform sourcing options On-premise: Entry or Rack option Storage or compute intensive workloads Off-premise: Cloud offering Designed to connect to SAP HANA

Service and Consulting Consulting, Hadoop and Analytic Services Tool supported sizing Integration Service

Entry Rack Cloud

Big Data Management

Analytics

Analytic Services

Integration Service

and

Sizing

Serv

ices

So

ftw

are

In

frastr

uctu

re

Smart

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PRIMEFLEX for Hadoop stack A

na

lyti

cs

Vis

ua

liza

tio

n

End-to-end data analytics Iterative spreadsheet Self-service data integration Explore data to identify patterns Segment data and use decision trees

Move beyond static dashboards Extensive library of visualization tools Visualize and communicate data according to business needs Integrate data visualizations


Fujitsu Consulting and Services for Big Data

Big Data Assessment Workshop Understand the opportunities Big Data can bring to your organization through the assessment of your organization’s strategic objectives, processes, and technical assets.

Strategy Consulting Develop the comprehensive Strategy Plan and optimal road map needed to efficiently introduce Big Data into your business.

Analytic Service Fujitsu Big Data Analytics Services assist our customers to quickly implement new Big Data analytics workflows through a proven Use Case driven approach

Hadoop Service Pragmatic, efficient and assured services for integrating complex Hadoop customizations into your business.

Integration Service Deploy the solution in your environment and connect to IT services.

•Fujitsu Big Data Assessment Workshop

•Fujitsu Big Data Strategy Consulting

•Fujitsu Big Data Analytics Services

Big Data Consulting Services

•Fujitsu Services for Hadoop

Fujitsu Services for Hadoop

•Fujitsu PRIMEFLEX for Hadoop Deployment Service

Fujitsu Integration Services


PRIMEFLEX for Hadoop highlights

Integrated System combining the convenience of pre-configured and pre-tested hardware with the economic advantages of open source software

Analytic Capabilities: Self-service data analytics, benchmarking, historic comparisons, forecast functions

Visualization Features: Powerful and transparent visualization of big data scenarios from versatile data sources at highly-productive level

In essence: Derive value from information


PRIMEFLEX for Hadoop testimonials

The principle benefit is the speed at which big data can be analyzed. What once would have taken weeks to process can now be completed within an hour or two. Dr Martin Fengler, CEO, Meteomatics

PRIMEFLEX for Hadoop is the ideal platform to foster innovation in Big Data use cases. For instance, in an analytics-based real-time shopping assistant, it is mission critical to manage and analyze Big Data volumes at high speed. At our industry-joint Software Innovation Campus Paderborn, we help to develop innovative models for all user types to enable new shopping experiences. Dr Stefan Sauer, Senior Researcher, University of Paderborn

With Hadoop, we can run parallel on large datasets, enabling us to skip the reduction step and work without performance degradation…The parallelization approach can even speed up the analysis of a single genome by a factor of four or more. Dr Matthias Schlesner, German Cancer Research Center (DKFZ) The purpose of the CoE is to solve local urban challenges; bringing together expertise across three organizations to develop solutions that can be applied globally. Fujitsu is playing a key role in the joint research and commercialization of the outcome.

Dr Hazel Khoo, Deputy Executive Director of the Science and Engineering Research Council, A*STAR


Use case: Hadoop-based genome research

Cancer research focuses on genomic data, which involves DNA sequencing,

assembly and analysis. The human genome, with three billion base pairs, is a

classic example of Big Data, as multiple patient samples can generate

petabytes of data.

Benefits

By leveraging parallel processing power, the PRIMEFLEX for Hadoop

platform analyzes genomes faster and more efficiently

Integrated self-service analytics software allows biologists or physicians to

work with raw genome data

No risk of data degradation as the system minimizes the number of

processing steps and the need for data transport, while considering the full

data set

Zero downtime hardware of the Big Data platform

fujitsu world tour 2017 - analytics in digital world

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