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InfoZoom Tips & Tricks – Part 5
Automated data cleansing via templates & queries
About corma GmbH

Stops suspects by:
analytical investigations
operative investigations
Saves time by:
online research
online monitoring

Increases efficiency
and saves money by:
data analytics
global intelligence
solutions

2
Sample Scenario
Cleanse address data
•
Original data:

3
Sample Scenario
Template and queries for data cleansing

4
Sample Scenario
Result of the data cleansing
•
•

Copy of the original attributes will be created
Via the queries, the values were unified and prepared for further analysis
by converting them to upper case, deleting special characters etc.

5
Sample Scenario
Additional examples for data cleansing
• Phone numbers
• Company and person names
• Date and time fields
• Description fields in log, case or transaction files
•

Further options:
•
Extract keywords from these fields to classify them

6
InfoZoom Trainings
InfoZoom online trainings
• IZ50 InfoZoom Web-Starter-Seminar
• IZ51 InfoZoom Web-Expert-Seminar
o Overview of all training dates can be found here:
http://infozoom-online-training.de/content/infozoomonline-training-trainings.html

7
Thank You!
infozoom@corma.de
+49 (2161) 277850

corma GmbH · Heinz-Nixdorf-Straße 22 · D-41179 Mönchengladbach ·
Tel: +49 2161 277 85 - 0 ·
E-Mail: mail@corma.de · Web: www.corma.de, www.blog.corma.de
8

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InfoZoom Tips & Tricks – Part 5: Automated data cleansing via templates & queries

  • 1. InfoZoom Tips & Tricks – Part 5 Automated data cleansing via templates & queries
  • 2. About corma GmbH Stops suspects by: analytical investigations operative investigations Saves time by: online research online monitoring Increases efficiency and saves money by: data analytics global intelligence solutions 2
  • 3. Sample Scenario Cleanse address data • Original data: 3
  • 4. Sample Scenario Template and queries for data cleansing 4
  • 5. Sample Scenario Result of the data cleansing • • Copy of the original attributes will be created Via the queries, the values were unified and prepared for further analysis by converting them to upper case, deleting special characters etc. 5
  • 6. Sample Scenario Additional examples for data cleansing • Phone numbers • Company and person names • Date and time fields • Description fields in log, case or transaction files • Further options: • Extract keywords from these fields to classify them 6
  • 7. InfoZoom Trainings InfoZoom online trainings • IZ50 InfoZoom Web-Starter-Seminar • IZ51 InfoZoom Web-Expert-Seminar o Overview of all training dates can be found here: http://infozoom-online-training.de/content/infozoomonline-training-trainings.html 7
  • 8. Thank You! infozoom@corma.de +49 (2161) 277850 corma GmbH · Heinz-Nixdorf-Straße 22 · D-41179 Mönchengladbach · Tel: +49 2161 277 85 - 0 · E-Mail: mail@corma.de · Web: www.corma.de, www.blog.corma.de 8