1. Changing the
Analytical Paradigm
Copyright © 2014 Visual Process Ltd. All rights reserved.
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About Visual Process
• Visual Process was founded in 2008
• Based in Israel with customers in the US, Asia
and Europe
• Offices in Haifa, Raanana

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Visual Process, innovative analytical
solution, solves productivity, operation
and maintenance problems by bridging
business and data.
Our Mission

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Short Exercise: What can you learn from the chart?
Something is growing
There is some Correlation
One part is greater than 50%

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Something is growing
There is some Correlation
One part is more than 50%
Short Exercise: What can you learn from the chart?

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In most cases data analysis is not a push of a button…
Fetch data
from
DWHmultiple
sources
Business and Data
understanding
Supervised
Unsupervised
data analysis
Insights
Context
Indications,
clues
Supervised
Unsupervised
data analysis

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Organizations focus on VVV missing the last (value)

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Organizations focus on VVV missing the last (value)

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Mind the Gap!
Fetch data
from
DWHmultiple
sources
Business and Data
understanding
Supervised
Unsupervised
data analysis
Insights
Context
Indications,
clues
Supervised
Unsupervised
data analysis

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Business and Data
understanding
Context
• Requires skills that most data analysts don’t have
• Takes long time without any reuse capabilities
The biggest gap is here
Mind the Gap!

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Business and Data Understanding is a team work!

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Typical Conversations
“What is the goal of the project?”
What does these columns mean?
The data doesn’t make sense
(or does it?)
Can I make a rule that if the value
is A then its actually B?

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Test yourself:
Does the gap exists in your organization?

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Is the interdisciplinary team
communicating efficiently?
Define business goals, understand the data
Test yourself:Does the gap exists in your organization?

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Is the knowledge they gather kept for
future use?
Do they ever use context or data transformation rules
from one project in another
Test yourself:Does the gap exists in your organization?

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Are they using the Context to enhance the analysis?
Do they use it to create transformation rules that will
enhance the analysis or just validate that what they did
make sense.
Test yourself:Does the gap exists in your organization?

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Is it a managed process?
Test yourself:Does the gap exists in your organization?

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Trends that are going to make it worse!
Unless the organization reuses of knowledge the people “who know” will
work in explaining what they know to each data analyst separately…
More people are analyzing data

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Trends that are going to make it worse!
Source Data
Data Warehouse
The trend of analyzing source
data that has never been
through any process will cause
even more confusion and
wrong conclusions

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Software:
 Cloud based
 Context based scripts in R, SAS, Drools or free text
 Knowledge indexing
Methodology: based on Object Process Methodology
(ISO 19450)
Visual Process Path to Success

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Visual Process Path to Success
Web based analytical task management
Visual Context Editor -OPM
Automatic knowledge indexing and context search
Team members management capabilities
Tagging and manual indexing
Meta data consolidation
Meta data import from CSV or XML
Exports to R, SAS, Drools and CSV
Key Features

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Visual Process Path to Success
Define the
business
problem
Define

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Visual Process Path to Success
Define the
business
problem
Identify the data
and upload the
relevant data
entities
Define Upload

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Visual Process Path to Success
Define the
business
problem
Identify the data
and upload the
relevant data
entities
Describe the
data using
Object Process
Methodology
Define Upload Describe

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Visual Process Path to Success
Define the
business
problem
Identify the data
and upload the
relevant data
entities
Describe the
data using
Object Process
Methodology
Create
Enrichment
rules based on
the knowledge
and apply these
rules to the data
Define Upload Describe Enrich

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Visual Process Path to Success
Define the
business
problem
Identify the data
and upload the
relevant data
entities
Describe the
data using
Object Process
Methodology
Create
Enrichment
rules based on
the knowledge
and apply these
rules to the data
Define Upload Describe Enrich
Reuse

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Return on investment
 Explain the data only once. Save time!
 Improve the accuracy of the analysis!
 Identify gaps and hidden connections in the data
 Formally manage the Problem Analysis and Data
Understanding phases
 Focus on the value added phases of the analysis

28. Copyright © 2014 Visual Process Ltd. All rights reserved.28
Your contact- EMEA:
Avraham A. CHOUKROUN
Vice President of Sales, EMEA
Visual Process
Mobile: (972) 54.48.72.736
Email: avraham@visual-process.com
Web: www.visual-process.com
Request a Demo!
Your contact- USA:
Chen Linchevski
CEO
Visual Process
Mobile: +1 518 3003637
Email: chen@visual-process.com
Web: www.visual-process.com