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Business Intelligence and Big Data Analytics Project
The case of Stack Exchange - Data Administration
Lamprini Koutsokera
lkoutsokera@aueb.gr
Alexandros Lattas
alexander@lattas.eu
Working Space
Data Acquisition
41.779 Posts
22.390 Users
123.697 Posts History
69.185 Comments
148.425 Votes
42.127 Badges
XML to
CSV Converter
(Online tool)
447.603 rows
Data Cleansing - Adjustment
Comments & Post History & Posts
Users without Id but with Display Name -> Guest Users
Post History
Users without Id & Display Name -> 10.039 rows deleted
Votes -> 12.207 rows deleted
Badges -> 213 rows deleted -> 73 distinct badges remained
Primary & Foreign
keys
5% of data deleted
Varchars to Numerics
postHistoryTypes | postTypes | voteTypes
age | reputation | views
Tables/dimensions creation
(1)
(2)
(3)
Star - Snowflake Schema
Fact Metrics
Total Comment Score
Posts Edits
Users Participated
Score
View Count
Answer Count
Comment Count
Favorite Count
Cube Creation
Dimensions
Users (Age, Reputation, Views)
Badge Types
Post Types
Post History Types
Creation Date
Votes Types και Tags
Measurements
Bridge Tables
Posts Post History
Bridge Tags
Votes
Badges
Fact Table +
Posts
Posts
Bridge Tags Tags
Post History Post History Types
Votes Votes Types
Users Badges Badges Types
Dimension Usage
Stack Exchange in Metrics
Top 10 Tags
Wednesday 3:00 p.m. Age Group
25-34
Posts through months
#
#
#
Posts through countries
United States
3.525 posts
India
1.648 posts
United Kingdom
1.857 posts
Canada
1.473 posts
Data Transformation
postid firebird checkpoint warning oracle-apex aggregation subquery
16956 0 0 0 1 0 0
21733 0 0 0 0 0 0
35756 0 0 0 0 0 0
44484 1 0 0 0 0 0
43484 0 0 0 0 0 0
40422 0 0 0 0 0 0
44726 0 0 0 0 0 0
35932 0 0 0 0 0 1
13.608 Posts – 694 Tags
Tag separation into distinct words
<sql-server><aggregation>
Data Mining
Clustering Association Rules
Scalable EM
30% testing set – 70 % training set
default 10 number of clusters
min. support 0.01
min. confidence 0.1
3.343 score
6.556 edits
1.035.024 views
609 favorites
8.847 users participated
8.700 score
13.654 edits
1.695.060 views
1.065 favorites
20.637 users participated
7.999 score
12.364 edits2.067.306 views
1.028 favorites
19.521 users participated
2.818.903 views
1.391 favorites
18.741 users participated
6.436 score
15.655 edits
5.078
score
7.016 edits
948.036 views
11.936 users participated
1.038 favorites
3.294 score
6.939 edits
1.538.607 views
497 favorites
8.914 users participated
Cluster Mapping – Posts View
13.608 Posts
11.347 badges
475.314 reputation
42.600 views
56.657 upvotes
2.907 downvotes
29.844 badges
1.605.644 reputation
131.913 views
205.183 upvotes
9.812 downvotes
177.444 upvotes
6.503 downvotes
128.337 views
1.355.876 reputation
27.052 badges
81.750 views
2.308 downvotes
75.049 upvotes
25.612 badges
1.005.826 reputation
13.754
badges
709.640 reputation
55.846 views
3.421 downvotes
90.959 upvotes
6.008 downvotes
163.349 upvotes
81.289 views
1.332.268 reputation
21.083 badges
Cluster Mapping – Users View
6.534 Users
25-34 age group
25-34 age group
25-34 age group
25-34 age group
25-34 age group
25-34 age group
Association Rules
backup
sql
server
index
mysql
replication
performance
optimization
database-design
Map Reduce
Cleansing
XML Files
Posts & Users
(&).*?(;)
^((?!AboutMe=).)*$
Reducer
Mapper #1
Mapper #2
Map Reduce Results
Posts Users Posts further analysis
Body About Me
• Key
• Value
• Default
• Clustering
• Slave
• Physical
• Node
• Logging
• Relationship
• C
• Dynamic
• Language
Tags’ description
enhancement
DBs’ problem
solving
Graph DBs
Programming Languages
Visualization
Users’ background
exploration
• Developer
• Software
• Web
• Programming
• Server
• Engineer
• SQL
• Java
• C#
• PHP
• Microsoft
• Linux
Skills Knowledge
Interests Knowledge
Job recommendation
“without”
• Without Time Zone
• Without Restarting
• Without using SQL
Timestamp type without
losing timezone information.
Related with Oracle and PostregSQL.
MySQL automatically deals with it.
Practical Implications
Insights for Solutions
& Improvements
Targeted Marketing
actions per DB Product
Insights on customer
behavior per DB Product
Improve data-driven
decision making SE process
Improve descriptive
tags quality
Mining the Database Administration data | Stack Exchange

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Mining the Database Administration data | Stack Exchange

  • 1. Business Intelligence and Big Data Analytics Project The case of Stack Exchange - Data Administration Lamprini Koutsokera lkoutsokera@aueb.gr Alexandros Lattas alexander@lattas.eu
  • 3. Data Acquisition 41.779 Posts 22.390 Users 123.697 Posts History 69.185 Comments 148.425 Votes 42.127 Badges XML to CSV Converter (Online tool) 447.603 rows
  • 4. Data Cleansing - Adjustment Comments & Post History & Posts Users without Id but with Display Name -> Guest Users Post History Users without Id & Display Name -> 10.039 rows deleted Votes -> 12.207 rows deleted Badges -> 213 rows deleted -> 73 distinct badges remained Primary & Foreign keys 5% of data deleted Varchars to Numerics postHistoryTypes | postTypes | voteTypes age | reputation | views Tables/dimensions creation (1) (2) (3)
  • 5. Star - Snowflake Schema Fact Metrics Total Comment Score Posts Edits Users Participated Score View Count Answer Count Comment Count Favorite Count
  • 6. Cube Creation Dimensions Users (Age, Reputation, Views) Badge Types Post Types Post History Types Creation Date Votes Types και Tags Measurements Bridge Tables Posts Post History Bridge Tags Votes Badges Fact Table + Posts Posts Bridge Tags Tags Post History Post History Types Votes Votes Types Users Badges Badges Types Dimension Usage
  • 7. Stack Exchange in Metrics Top 10 Tags Wednesday 3:00 p.m. Age Group 25-34
  • 9. Posts through countries United States 3.525 posts India 1.648 posts United Kingdom 1.857 posts Canada 1.473 posts
  • 10. Data Transformation postid firebird checkpoint warning oracle-apex aggregation subquery 16956 0 0 0 1 0 0 21733 0 0 0 0 0 0 35756 0 0 0 0 0 0 44484 1 0 0 0 0 0 43484 0 0 0 0 0 0 40422 0 0 0 0 0 0 44726 0 0 0 0 0 0 35932 0 0 0 0 0 1 13.608 Posts – 694 Tags Tag separation into distinct words <sql-server><aggregation>
  • 11. Data Mining Clustering Association Rules Scalable EM 30% testing set – 70 % training set default 10 number of clusters min. support 0.01 min. confidence 0.1
  • 12. 3.343 score 6.556 edits 1.035.024 views 609 favorites 8.847 users participated 8.700 score 13.654 edits 1.695.060 views 1.065 favorites 20.637 users participated 7.999 score 12.364 edits2.067.306 views 1.028 favorites 19.521 users participated 2.818.903 views 1.391 favorites 18.741 users participated 6.436 score 15.655 edits 5.078 score 7.016 edits 948.036 views 11.936 users participated 1.038 favorites 3.294 score 6.939 edits 1.538.607 views 497 favorites 8.914 users participated Cluster Mapping – Posts View 13.608 Posts
  • 13. 11.347 badges 475.314 reputation 42.600 views 56.657 upvotes 2.907 downvotes 29.844 badges 1.605.644 reputation 131.913 views 205.183 upvotes 9.812 downvotes 177.444 upvotes 6.503 downvotes 128.337 views 1.355.876 reputation 27.052 badges 81.750 views 2.308 downvotes 75.049 upvotes 25.612 badges 1.005.826 reputation 13.754 badges 709.640 reputation 55.846 views 3.421 downvotes 90.959 upvotes 6.008 downvotes 163.349 upvotes 81.289 views 1.332.268 reputation 21.083 badges Cluster Mapping – Users View 6.534 Users 25-34 age group 25-34 age group 25-34 age group 25-34 age group 25-34 age group 25-34 age group
  • 15. Map Reduce Cleansing XML Files Posts & Users (&).*?(;) ^((?!AboutMe=).)*$ Reducer Mapper #1 Mapper #2
  • 16. Map Reduce Results Posts Users Posts further analysis Body About Me • Key • Value • Default • Clustering • Slave • Physical • Node • Logging • Relationship • C • Dynamic • Language Tags’ description enhancement DBs’ problem solving Graph DBs Programming Languages Visualization Users’ background exploration • Developer • Software • Web • Programming • Server • Engineer • SQL • Java • C# • PHP • Microsoft • Linux Skills Knowledge Interests Knowledge Job recommendation “without” • Without Time Zone • Without Restarting • Without using SQL Timestamp type without losing timezone information. Related with Oracle and PostregSQL. MySQL automatically deals with it.
  • 17. Practical Implications Insights for Solutions & Improvements Targeted Marketing actions per DB Product Insights on customer behavior per DB Product Improve data-driven decision making SE process Improve descriptive tags quality

Editor's Notes

  1. Cluster 1 -> 65percent reputation - 65percent views Cluster 2 -> 65percent reputation – inactive views Cluster 3 -> 65percent reputation – inactive views Cluster 4 -> 65percent reputation - views Cluster 5 -> 65percent reputation - views Cluster 6 -> 65percent reputation - views