Data visualization meetup presentation

Timo Elliott, Innovation Evangelist, SAP

Data

Visualization

@timoelliott

What Is An

Evangelist?

The Greek word εὐαγγέλιον (latinized to Evangelium) originally meant a reward given to the

messenger for good news (εὔ = "good", ἀγγέλλω = "I bring a message“)

3© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Proudly Selling 3D Pie Charts for 20+ Years!

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 4

88%

How Do Executives Make Decisions?

Aspect Consulting, 1997

12%Hard Facts

Gut Feel

90%

10%Hard Facts

Gut Feel

Economist Intelligence Unit, 2014

Why the worst-practice shaded 3D donut charts? JUST TO ANNOY YOUI!


Biggest Barriers to Business Intelligence

51%48%

44%

Data QualityProblems

Ease of Use Integration ofdifferent systems

43%

37% 36%

It is difficult todetermine if

information isaccurate

It takes a long timeto find information

Information isstored in ways that

makes it hard tofind

20152003

Sources: InformationWeek Survey 2015, BusinessWeek Survey, 2003


Plus Ça Change…


Use Analytics

Today

Need

Analytics

by 2020Gartner, 2014

Analytics is Still Hard!

Inability to see, understand, and

optimize new opportunities

Inaccessible data

and technologyInsights remain hidden

Complexity, cost, confusionSilos of approaches and

analytic technologies

75%

10%

Slow decision making

lacking future view

Rear view mirror

BI mentality


Data Visualization

An example

of a poor

data-oink

ratio?…


Proportion Analytics Success Depends On:

Data quality, data

integration, metadata

management, ease of

use, user training,

analytic processes,

information culture, etc.

Not using 3D pie

charts

Note: data completely made up – like most powerpoint charts


Flashy graphics can make useful sales tools early

on in the lifecycle of rolling out data visualization —

but encourage best practice as soon as possible


clouddata

mobile

MORE!

competition

speed

social

connected

There’s Been An Explosion of New Technology

Means new

opportunities…

12© 2015 SAP SE or an SAP affiliate company. All rights reserved.

Big Data

Discovery =Big Data

Data Discovery

Data Science

Gartner Strategic Planning Assumption:

By 2017, Big Data Discovery Will Evolve Into a Distinct Market Category


Big Data Discovery

• Volume, velocity, or

variety of data

• Potential business

impact

• Difficult to implement

• Potentially expensive

• Lack of skills available

• Ease of use

• Agility and flexibility

• Time-to-results

• Installed user base

• Complexity of analysis

• Potential impact

• Range of tools

• Smart algorithms

• Difficult to implement

• Slow and complex

• Narrow focus of

analysis

• Limited depth of

information

exploration

• Low complexity of

analysis

BIG

DATADATA

SCIENCE

DATA

DISCOVERY


Big Data Discovery

• Simpler to use than data science

• Accessible to a wider range of users

• Broad range of data manipulation features

• Able to handle new types of data sources

• With adequate performance for big data

BIG DATA

DISCOVERY


Potential impact

per user

Potential user

base

The Rise of the Citizen Data Scientist

Business

analyst

Data

scientist

Citizen data

scientist


The Opportunity*

New Business Opportunities

Traditional Analytics

Data

Value

Volume / Variety / Velocity of Data

“Big Data Discovery”

Data Discovery

Big Data

Data Science


Our Opportunity

Big Data

Discovery

SAP HANA

(+ Hadoop etc.)

SAP Predictive

Analytics 2.0

SAP Lumira


Data Discovery

The revenge of the full client

SAP Lumira


We Need Self-Service Data Preparation

Access Enrich Calculate & Correct Merge


We Need To Fluidly Explore And Interact With Data


We Need More Than Just Pie And Bar Charts


Integrated 3D Visualization


We Need Mobile


We Need To Tell Stories


Doctors Without Borders


We Need Predictive Analytics

A new generation of more user-friendly predictive technology

SAP Predictive Analytics


Vodafone Netherlands


We Need Support For Teams

SAP Lumira Edge

SAP Lumira Server


30

Agile Visualizations and Lumira Cloud

to identify and track potential sales for

dealers

Combine sales, vehicle registrations

and industry failure data

Over 200 dealers by the end

of the year

Why?

Performance

No infrastructure to maintain

Daimler Trucks


DEMO


We Need Dashboards

Let users drag and drop

their self-service data

visualization into

corporate dashboard

templates


We Need Analytic Applications

With the ability to “take action” by writing back to operational systems


We Need To Support The Analytics Lifecycle


We Still Need Reporting and Dashboards

18%

19%

25%

35%

53%

69%

Query & Analysis

Data Discovery

Alerts

Dashboards

Reports

Spreadsheets

Source: InformationWeek BI Survey 2015

To what extent are the following technologies used to share analytic and BI insights in your organization?

Used extensively:


We Still Need Industrial Scale BI and Reporting

Where did

that number

come from?!Why all these

information

silos?!

What about

security and

administration?!


Breathing New Life Into Enterprise Query & Reporting

Simplify

Enhance

Extend

Mobile

Cloud

Big Data BI


We Need To Have Full-Cycle Analytics


Cloud-Based Planning


We Need One Platform With Many Workloads

Transactions Streaming Predictive Text MiningAnalytics Spatial

Mobile Analytics Collaboration IntegrationPortal Security

Core Services (data ingestion, federation, etc) — Cloud AND On-Premise

Data visualization meetup presentation

Technology

Transcript of Data visualization meetup presentation