Visual Process, an innovative analytical solution by bridging business and data.

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Visual Process, an innovative analytical solution by bridging business and data.

  1. 1. Changing the Analytical Paradigm Copyright © 2014 Visual Process Ltd. All rights reserved. 1
  2. 2. 2 About Visual Process • Visual Process was founded in 2008 • Based in Israel with customers in the US, Asia and Europe • Offices in Haifa, Raanana
  3. 3. 3 Visual Process, innovative analytical solution, solves productivity, operation and maintenance problems by bridging business and data. Our Mission
  4. 4. 4 Short Exercise: What can you learn from the chart? Something is growing There is some Correlation One part is greater than 50%
  5. 5. 5 Something is growing There is some Correlation One part is more than 50% Short Exercise: What can you learn from the chart?
  6. 6. 6 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
  7. 7. 7 Organizations focus on VVV missing the last (value)
  8. 8. 8 Organizations focus on VVV missing the last (value)
  9. 9. 9 Mind the Gap! Fetch data from DWHmultiple sources Business and Data understanding Supervised Unsupervised data analysis Insights Context Indications, clues Supervised Unsupervised data analysis
  10. 10. 10 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!
  11. 11. 11 Business and Data Understanding is a team work!
  12. 12. 12 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?
  13. 13. 13 Test yourself: Does the gap exists in your organization?
  14. 14. 14 Is the interdisciplinary team communicating efficiently? Define business goals, understand the data Test yourself:Does the gap exists in your organization?
  15. 15. 15 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?
  16. 16. 16 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?
  17. 17. 17 Is it a managed process? Test yourself:Does the gap exists in your organization?
  18. 18. 18 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
  19. 19. 19 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
  20. 20. 20 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
  21. 21. 21 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
  22. 22. 22 Visual Process Path to Success Define the business problem Define
  23. 23. 23 Visual Process Path to Success Define the business problem Identify the data and upload the relevant data entities Define Upload
  24. 24. 24 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
  25. 25. 25 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
  26. 26. 26 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
  27. 27. 27 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. 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

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