Closing the Data Quality Gap
Transcript of Closing the Data Quality Gap
Closing The Data Quality Gap in Dynamics CRM
Setting the scene…
Who are we
?
What do we do ?
How do we do it ?
What’s in it
for our clients
?
The Data Quality Delusion
Everyone understand
the importance of data quality
Everyone agrees data
quality is important
Everyone cares about data quality
Everyone knows what actions to
take to improve data
quality
A year in the life of B2B data…
5m trading businesses in the UK
5.7m company or individual details changes:• 1 moves every 6 Minutes• 1 fails every 4 minutes
On average a person changes jobs 11 times during their career
On average data decays…@ 24% p.a. ½ life attrition = 3 yearsWith insufficient care…@ 35% p.a. ½ life attrition = 2 years
How can we end up with bad data?
A Boy's name
beginning with the letter J:
"Gerald.."
A word beginning
with Z: "Xylophon
e.."
A part of the body beginning
with N: "Knee..“
A mode of transport that you can walk in: "Your shoes.."
Misinterpretation & Standards
M = Male in one system and Married in another
S = Single in one system
and Separated in
another
Gender•9 variants in the gender field of a hotel project
Padhraic, Pádraig or PáraicLane, LN, Ln, Road, Rd, Rd. etc.MI or MichiganUS or USA or United StatesGB or UK or United KingdomMr. or MisterHants or Hampshire
Numbers in Text and Shared Numbers
Systems Contain:
• 0’s and/or O’s• 1’s and/or I’s• Tel numbers
with 9 x 000 000 000
Same product – different
numbers in 2 systems
• Same Part number 99 000 1111• 99 000 1111 = 1 days cold ration
pack• 99 000 1111 = Radio valves
• Leasing Agreement numbers• ID Counters shared across systems• SKU’s• Tank & Aircraft Parts
Anomalies & Congruence
eMail does not tally
with name parts
Currency does not tally with location
Goods shipped before order
Values not in
application pick lists
(metadata)
Default values used
Notes (memo)
fields used without
validation rules
What can happen when data “goes bad”?
User Adoption Rates
Pipeline Issues
Account Management Efficiency
User Adoption Rates
Pipeline Issues
Account Management Efficiencies
Different Functions
Different People
Different Systems
Solutions to help close the Data Quality Gap
Identifying matchesLinkingMasteringMergingUpdating
Solutions to help close the Data Quality Gap
Solutions to help close the Data Quality Gap
ClassifyCompareFormat
GenerateTransform dataValidate
DQ Studio
Questions…
• Build a better business based on trusted data…
• Contact DQ Global• www.DQGlobal.com
• Talk to a consultant• [email protected]• +44 2392 988303 (Europe)• +1 314-253-7873 (North America)