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Using open source BI. Practical experience 2012 - En

Serge Ivanko
Serge Ivanko

The document discusses the implementation of an open source business intelligence (BI) solution at a digital e-commerce company. Previously, the company used various homegrown systems and Google Analytics, requiring manual data merging. The goals of the new solution were to effectively manage key performance indicators (KPIs) and market responses. Pentaho was selected as it provided OLAP, pivots, and integration with the company's MySQL database. The implementation took around 6 months, resulting in a single source of data truth, timely insights from regular KPI monitoring, and new opportunities from business analysis and data mining.

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Using Open Source BUSINESS INTELLIGENCE My practical experience Copyright 息 2012 by Serge Ivanko 1
Overview of the situation in the company Digital internet company. (e-Commerce) Network of selling web sites Homemade CRM + several other IT systems MySQL, PHP, ... Google Analytics is in active use Reports with monster-filters Data export to Excel and manual merging (+ formulas) 2
Goals and Formulation of the problem It is necessary to effectively manage by goals and respond to the market in a timely manner Transparent processes and relevant KPIs! 3
Core business process HLBP Model.vsd http://wiki.....com/display/PR/Business+processes 4
Choice 5
弌riteria. "We would like to have ..." OLAP and Pivots Allowed to display all the necessary KPIs Should be integrated with our MySQL Reports are easy to build... And in general It would be cool to have not just Pivots and Data cubes, but also a set of different data and analytic tools. To be serious... 6
Pentaho contains 7 Analysis View (+ SAIKU) Dashboard designer Data Integration (Kettle, Spoon, Pan, Kitchen) Metadata editor (we didnt use it yet) Report designer Weka - Data Mining tool with lots of integrated math models Web based ...
Well, let's get it done! 8
AGILE BI 9 Building of DWH and Agile BI Consequences of implementation (Data cleaning) Done? Use it right away Take the Spoon! "Doesn't match? So that's because And more...
Some more Agile Connecting to various data sources. Experience with Google Analytics Map of the World (Data world) 120 dimensions 60 measures Trainings for users 10
Training structure 11 Basic level Advanced level
Common structure 12 Ready made parameters structure It is ready and working http://wiki....com/display/PR/Measures+and +dimentions+dictionary Dictionary of dimensions and measures In IExpert BI.docx Measures and dimentions in IExpert BI.mmap Define traffic channel (Define source for each order): http://wiki.....com/display/PR/Traffic+ channel+dimension Getting data from tracked transactions
Introductory information (3 + 3 main terms in plain language) Theory Business Intelligence (BI) DWH Data Warehouse OLAP (On-Line Analytical Processing) Practice Facts, fact table Measure Dimension 13
What did we get 14
What did we get 15
What next in terms of this solution New tools - new opportunities Dashboard designer Convenience and Beauty Data Mining Weka Trends and forecasts I didn't know that (about hidden patterns) 16
Project scope and size Duration (0.5 year) Researching and experimenting took half the time. If you have experience, you can cut it by 2 times The first results - after 3 months. If you have experience, you can get in a few weeks (Using Agile approach) HR: 3 employees with 100% allocation 5 employees took part in the project 2 with >50% of allocation 3 with <=25% of allocation Additionally there were involved other employees business users Lessons learned: Work more actively with business users 17
What next Adopt it for other type of busiesses Make it more efficiently Reduce time for implementation by 2-3 Integration with 1弌 18
Business Results Consent. A common source of data (source of truth) - common criteria for evaluation Timely changes when the business environment changes due to regular monitoring of the necessary KPIs Effective motivation of employees - Due to Goal management and goal related bonuses Time saving for data collection and processing Forecasting and planning based on smart mathematical models. New opportunities. More ideas for business improvement and development - thanks to business analysis Full picture. Data from all systems. (including CRM, Google Analytics, etc.) Flexibility. Quick extensions of new reports or parameters (measures/dimensions) 19
Additional materials YouTube: http://www.youtube.com/watch?v=p3Yy3tVaiEY etc. 20
Thank you! Questions 息 Serge Ivanko + 38 050 385 12 08 https://www.linkedin.com/in/sergeivanko/ 21 sergey.ivanko@gmail.com

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Using open source BI. Practical experience 2012 - En

  • 1. Using Open Source BUSINESS INTELLIGENCE My practical experience Copyright 息 2012 by Serge Ivanko 1
  • 2. Overview of the situation in the company Digital internet company. (e-Commerce) Network of selling web sites Homemade CRM + several other IT systems MySQL, PHP, ... Google Analytics is in active use Reports with monster-filters Data export to Excel and manual merging (+ formulas) 2
  • 3. Goals and Formulation of the problem It is necessary to effectively manage by goals and respond to the market in a timely manner Transparent processes and relevant KPIs! 3
  • 4. Core business process HLBP Model.vsd http://wiki.....com/display/PR/Business+processes 4
  • 6. 弌riteria. "We would like to have ..." OLAP and Pivots Allowed to display all the necessary KPIs Should be integrated with our MySQL Reports are easy to build... And in general It would be cool to have not just Pivots and Data cubes, but also a set of different data and analytic tools. To be serious... 6
  • 7. Pentaho contains 7 Analysis View (+ SAIKU) Dashboard designer Data Integration (Kettle, Spoon, Pan, Kitchen) Metadata editor (we didnt use it yet) Report designer Weka - Data Mining tool with lots of integrated math models Web based ...
  • 8. Well, let's get it done! 8
  • 9. AGILE BI 9 Building of DWH and Agile BI Consequences of implementation (Data cleaning) Done? Use it right away Take the Spoon! "Doesn't match? So that's because And more...
  • 10. Some more Agile Connecting to various data sources. Experience with Google Analytics Map of the World (Data world) 120 dimensions 60 measures Trainings for users 10
  • 12. Common structure 12 Ready made parameters structure It is ready and working http://wiki....com/display/PR/Measures+and +dimentions+dictionary Dictionary of dimensions and measures In IExpert BI.docx Measures and dimentions in IExpert BI.mmap Define traffic channel (Define source for each order): http://wiki.....com/display/PR/Traffic+ channel+dimension Getting data from tracked transactions
  • 13. Introductory information (3 + 3 main terms in plain language) Theory Business Intelligence (BI) DWH Data Warehouse OLAP (On-Line Analytical Processing) Practice Facts, fact table Measure Dimension 13
  • 14. What did we get 14
  • 15. What did we get 15
  • 16. What next in terms of this solution New tools - new opportunities Dashboard designer Convenience and Beauty Data Mining Weka Trends and forecasts I didn't know that (about hidden patterns) 16
  • 17. Project scope and size Duration (0.5 year) Researching and experimenting took half the time. If you have experience, you can cut it by 2 times The first results - after 3 months. If you have experience, you can get in a few weeks (Using Agile approach) HR: 3 employees with 100% allocation 5 employees took part in the project 2 with >50% of allocation 3 with <=25% of allocation Additionally there were involved other employees business users Lessons learned: Work more actively with business users 17
  • 18. What next Adopt it for other type of busiesses Make it more efficiently Reduce time for implementation by 2-3 Integration with 1弌 18
  • 19. Business Results Consent. A common source of data (source of truth) - common criteria for evaluation Timely changes when the business environment changes due to regular monitoring of the necessary KPIs Effective motivation of employees - Due to Goal management and goal related bonuses Time saving for data collection and processing Forecasting and planning based on smart mathematical models. New opportunities. More ideas for business improvement and development - thanks to business analysis Full picture. Data from all systems. (including CRM, Google Analytics, etc.) Flexibility. Quick extensions of new reports or parameters (measures/dimensions) 19
  • 20. Additional materials YouTube: http://www.youtube.com/watch?v=p3Yy3tVaiEY etc. 20
  • 21. Thank you! Questions 息 Serge Ivanko + 38 050 385 12 08 https://www.linkedin.com/in/sergeivanko/ 21 sergey.ivanko@gmail.com