How did we implement BI for product e-commerce company? Share our experience to avoid gotchas.

1. Using Open Source
BUSINESS INTELLIGENCE
My practical experience
Copyright © 2012 by Serge Ivanko
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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)
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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!
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4. Core business process
 HLBP Model.vsd
 http://wiki.....com/display/PR/Business+processes
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5. Choice
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6. Сriteria. "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...
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7. Pentaho contains
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 Analysis View (+ SAIKU)
 Dashboard designer
 Data Integration (Kettle,
Spoon, Pan, Kitchen)
 Metadata editor
(we didn’t use it yet)
 Report designer
 Weka - Data Mining tool
with lots of integrated math models
 Web based
 ...

8. Well, let's get it done!
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9. AGILE BI
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 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
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11. Training structure
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Basic level Advanced level

12. Common structure
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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
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14. What did we get
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15. What did we get
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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)
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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 1С
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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.
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21. Thank you!
Questions …
© Serge Ivanko
+ 38 050 385 12 08
https://www.linkedin.com/in/sergeivanko/
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sergey.ivanko@gmail.com