A Revolution in Business AnalyticsThe Zika Virus Example

October 2016

Data is growing…and it effects everyone

How Big Is Big?

What is Big Data?

4

What is Hadoop?

Apache Hadoop is an open source, Java-based programming framework that supports the processing and storage of extremely large data sets in a distributed computing environment. • Hadoop is an ecosystem of open source components that fundamentally changes the way

enterprises store, process, and analyze data.

• Unlike traditional systems, Hadoop enables multiple types of analytic workloads to run on the same data, at the same time, at massive scale on industry-standard hardware.

IBM BigInsights, AWS, MapR, Microsoft HDInsight, Intel, Datastax, Teradata, Pivotal HD

Hortonworks Data Platform (HDP) is a secure, enterprise-ready open source Apache™ Hadoop® distribution based on a centralized architecture (YARN). HDP addresses the complete needs of data-at-rest, powers real-time customer applications and delivers robust analytics that accelerate decision making and innovation.

Cloudera provides Apache Hadoop-based software, support and services, and training to business customers for enterprise-class deployments . It is the most popular distribution of Hadoop and related projects in the world

Others

Market Growth … does it match your budget?

The global Hadoop market, which spans hardware, software, and services, is expected to grow to $85B by 2021 (CAGR of 63% from 2016)

-Allied Market Research

Prediction of Adoption

“Forrester estimates that 100% of all large enterpriseswill adopt it (Hadoop and related technologies such as Spark) for big data analytics within the next two years.”

--The Forrester WaveTM, Big Data Hadoop Distributions, Q1 2016

100% of all large enterprises will adopt Hadoop and related technologies such as Spark

Why does Forester predict that there will be 100% adoption

• With Hadoop the storage volume problem is solved

• We are nearing the peak in the life cycle—it is no longer a emerging technology

Source: Hortonworks June 2015

What can be done with all the data?

Operational Efficiency

New Business Value

OPERA

TIONS

DATAM

ANAGEM

ENT

UNIFIEDSERVICES

PROCESS,ANALYZE,SERVE

STORE

INTEGRATE

Store and process unlimited data fast and

cost-effectively.

Data Integration

Explore, analyze, and understand all your data.

Data Discovery and

Analytics

Build data-driven productsto deliver real-time

insights.

Real-Time Data

Applications

The real issue is not about acquiring large amounts of data, It's about what is done with the data.

Big Data Implementation Examples Combining Big Data with Analytics:

By combining Big Data and high-powered analytics, it is possible to:

• Determine root causes of failures, issues and defects in near-real time, potentially saving billions of dollars annually.

• Optimize routes for many thousands of package delivery vehicles while they are on the road.

• Analyze millions of SKUs to determine prices that maximize profit and clear inventory.

• Generate retail coupons at the point of sale based on the customer's current and past purchases.

• Send tailored recommendations to mobile devices while customers are in the right area to take advantage of offers.

• Recalculate entire risk portfolios in minutes.

• Quickly identify customers who matter the most.

• Use clickstream analysis and data mining to detect fraudulent behavior.10

How do we do it?

• What are the technologies?

• How do we combine them to form a Modern Data Architecture?

• How do we leverage the technologies in place to combine Big Data with High Powered Analytics?

• Let’s start by examining the Analytics Value Chain

The Analytics Value Chain

It’s what we do.

Apply, Artificial Intelligence (AI), Machine Learning (ML), predictive, prescriptive and geospatial analytics to further leverage your data assets.

Identify patterns, relationships and outliers in vast amounts of data in visually compelling ways.

Democratize your data further by empowering business users to prep their data for analysis. Enable DaaS with governance.

Modernize your architecture to take advantage of a schema-less data-lake approach that rapidly adjusts to changing business requirements.

The Bardess Analytics Value Chain is a

systematic approach to conceptually

visualize the strategic journey to insightful

business analytics

Enterprise-ReadySolutions

BU

SIN

ESS

VA

LUE

Enterprise-Ready Solutions

Database & Storage

Modernizing the data architecture to take advantage of a schema-less data-lake approach that rapidly adjusts to changing business requirements providing scalability, security and governance.

BU

SIN

ESS

VA

LUE

Data Preparation

Enterprise-Ready Solutions

Enable DaaS with governance.

• Data Preparation• Data Wrangling• Data Quality Improvement• Data Enrichment

Democratize data further by empowering business users inn:

BU

SIN

ESS

VA

LUE

Solution Provider of the year 2016

Visual Analytics

Enterprise-Ready Solutions

Identifying patterns, relationships and outliers in vast amounts of data in visually compelling ways.

User-driven Analysis

BU

SIN

ESS

VA

LUE

Advanced Analytics

Enterprise-Ready Solutions

Further leveraging data assets by applying advanced• Machine Learning• Predictive Analytics• Prescriptive Analytics• Artificial Intelligence

The Zika Virus Example

This Zika analysis is an example of the Value Chain in action…

• A modern data architecture that provides agility to adjust to changing business requirements, and a repository for really disparate data.

Enterprise-ReadySolutions

• Security and governance.

• A compelling story about Zika and what's been done about it, presented in Qlik Sense.

• A foundation for future analytics including Machine Learning and predictive analytics.

What is Zika?

The Spread of Zika

How is Zika Spreading?

Getting the Message Out

The Zika Virus Demo

Zika Virus Demo

See the whole storythat lives within your data

Visualization alone is insufficient

A modern analytics platform like Qlik provides the vehicle to solve a multitude of business analytics challenges.

Founded in Lund,

Sweden in 1993

Headquartered in

Radnor, PA, USA

39,000 customers and

1,700 partners in more

than 100 countries

10 years’ growth

outpacing market

More than

2,500

employees

39,000

1,700

100

What Qlik®

delivers

26

Gartner Recognizes Qlik® as a Leader in Magic Quadrant for BI & Analytics Platforms

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Qlik. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and is used herein with permission. All rights reserved.

Source: Gartner, Magic Quadrant for Business Intelligence and Analytics Platforms, Josh Parenteau et al, February 4, 2016. The Gartner document is available upon request from Qlik.

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The Qlik Portfolio

Associative Engine Technology, APIs, Toolkit…

AnalyticsGuided, embedded, self-

service, collaborative

DataAccess, smart load,

governed data, big data

CloudCreate & share, managed cloud, value

added services, ecosystem

Cap

abili

ties

Pro

du

cts

Pla

tfo

rm

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• Self-service visualization and discovery• Associative model

• Smart visualizations

• User-driven, drag-and-drop creation

• Sharing of knowledge and insights• Centralized sharing and collaboration

• Data storytelling and reporting

• Anywhere, anytime mobility

• A platform for the entire enterprise• Embedded analytics, custom apps and

extensions

• Robust data integration

• Enterprise-class governance

With Qlik’s patented Associative Data Indexing technology at its core, Qlik Sense delivers:

Qlik® Sense

29

• Most Big Data Users are not Data Scientists

─ Business users want simple, guided access

• Helping the user find relevant and contextual information

─ Instead of having to search through everything

• Ensuring the solution can accommodate today and tomorrow

─ Big Data landscape continues to rapidly evolve

• Able to use different methods for different data volumes and

complexities

─ “One method does not fit all”

Challenge - Providing Big Data to everyone

“A car may produce an exabyte of data a year (a billion gigabytes), but most is

completely meaningless. Isolating the megabyte of data a month that’s really

valuable, and then figuring out what you can do with it, that’s the challenge of Big

Data.”Scott McCormick, president of the Connected Vehicle Trade Association and industry adviser to the U.S. Secretary of Transportation, September 2013

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The Qlik platform – for all usersMost Big Data Users are not Data Scientists

Deep drilling

Mostly drilling, some exploration

Mostly exploration,

some drilling

Data Experts

Data Scientists

Breadth of Coverage

De

pth

of

Co

ve

rag

e

Data Explorers

Descriptive, diagnostic and predictive analytics(“What happened?”, “Why did it happen?” and “What is likely to happen?”

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Qlik & Cloudera

Benefits For Customers

.

Fast

For Business

Easy

To Manage

Secure

Without Compromise

Make Big Data

Accessible

Deliver Big Data

In Context

Keep Big Data

Relevant

Faster and Higher Big Data

ROI

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Qlik within a Big Data Architecture

Analyze

Refinement

Initial Processing

Gather

HADOOPDATA SOURCES

ACCELERATORS

QIX Associative Engine

Unstructure

d data

Structured

data

NON-HADOOP

Standards-based or application-specific connector