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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 growingThere is some Correlation
One part is greater than 50%
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Something is growingThere is some Correlation
One part is more than 50%
In the best case these are clues not business insights!
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 DWH\
multiple 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 DWH\
multiple 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 managementVisual Context Editor -OPMAutomatic knowledge indexing and context searchTeam members management capabilities Tagging and manual indexingMeta 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
Copyright © 2014 Visual Process Ltd. All rights reserved.
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Your contact- EMEA:
Avraham A. CHOUKROUN
Vice President of Sales, EMEA
Visual Process
Mobile: (972) 54.48.72.736
Email: [email protected]
Web: www.visual-process.com
Request a Demo!
Your contact- USA:
Chen Linchevski
CEO
Visual Process
Mobile: +1 518 3003637
Email: [email protected]
Web: www.visual-process.com
