Improved Asset Data Quality - UK & Ireland SAP Users Group · PDF file© 2014 SAP SE or an SAP affiliate company. ... Improved Asset Data Quality © 2014 SAP SE or an SAP ... EAN Amperage

© 2014 SAP SE or an SAP affiliate company. All rights reserved. 1Public

Improved Asset Data Quality


Agenda

Why is data quality key?

What is data quality?

How to improve?

How to execute data quality projects?

How to guarantee quality?

What is the business case for Alliander?

2

Why is data quality key?

3


We want data at our fingertips

External view / customers:

When is an outage over?

Where can I find what they are doing in my

street?

When do they come to my home for the

repairs?

Internal view / grid operator:

What does a field worker have to take with

him to repair an outage?

How to optimize work force planning?

What are the main risk factors in the grid?

4

What is data quality?

5


How is data quality defined?

Data quality

Completeness Correctness Consistency

How to improve it?

7


Which data?

Divide the subject into smaller pieces

8

AssetLegal

Finance Asset healthSafety &

environment

Network & network-

management

Customer Work planning Remainder


What is important?

The 5 sec rule:

Define in 5 sec the important

objects

Define in 5 sec the important

attributes

9

Asset

Object Y

Attribuut 1

Attribuut 2

Attribuut n

Object X

Attribute 1

Attribute 2

Attribute n


What is the norm for completeness?

Define minimum levels for data completeness (norms)

Set the norm for each object

10

Asset

Object Y Object Y Object X Object X

Object X Object C

Object BObject B Object B

Object CObject C

Object AObject B

Object C

Object AObject A


What is the norm for correctness?

11

Background

check

ME

ID-check

PassportIntroduction


What is the norm for correctness?

Define the level of correctness for the data (norms)

Set the norm for each object

12

Data

mining

Correctness

Expert

knowledge

Visual

inspections

Data is validate by 3 of 3



Regular process of new data

Data with unknown origin

Wrong data

How to execute data quality

projects?

13


How to solve data quality issues?

The most challenging task is to correct data quality issues

Extract data,

identify issuesCorrect issues

Approve and

change data

???

STANDARD SOLUTION AVAILABLE STANDARD SOLUTION AVAILABLE


Data mining-based approach to correct data quality issues is powerful

How to correct data quality issues?

Computing

power

Effort

Manual cleansing Record by record, inspections

Effort: #data records × #attributes

Expert/Rule-based Use expert knowledge to derive rules

Effort: #attributes × #rules

Data mining-based Automatically derive rules using statistics

Review rules and results with experts

Effort: Smaller than #attributes

Intellectual

property


How to correct data quality issues?

Most efficient approach is to combine manual and expert/rule-based

cleansing with data mining

Data

mining

Expert/

Rules

Manual

clean-

sing


Business problem

Number of phases of

connection points is

partially missing

Red: One phase

Blue: Three phases

Gray rectangles: Phase

information missing3 phases

3 phases1 phase

1 phase

???

??????


Collect data about connection points in a finger print

EAN Amperage Auto fuse Connection

type

Decade

constructed

Fraction of

1-phase

neighbors

Number of

phases

871685900009726493 25 A No Apartment 10 100% 1


type

Decade

constructed

Fraction of

1-phase

neighbors

Number of

phases

871685900009730377 25 A No Apartment 10 60% 3


type

Decade

constructed

Fraction of

1-phase

neighbors

Number of

phases

871685900100096846 ??? No Apartment 10 60% ???


Analytic table

Data about many connections


type

Decade

constructed

Fraction of

1-phase

neighbors

Number of

phases

871685900009726493 25 A No Apartment 10 100% 1

871685900009730377 25 A No Apartment 10 60% 3

871685920000769466 40 A No Apartment 10 28% 1

871685900010940246 25 A No Apartment 3 12% 3

871685900100198441 35 A No Business & Ap. 7 9% 3

871685920000547606 40 A Yes Apartment 10 0% ???

871685900002665362 ??? ??? Business 8 55% ???

871685900010837782 40 A No Other 9 50% ???

871685900100096846 ??? No Apartment 10 60% ???


Analytic table

Split finger print into explaining fields and target field

EAN

871685900009726493

871685900009730377

871685920000769466

871685900010940246

871685900100198441

871685920000547606

871685900002665362

871685900010837782

871685900100096846

Amperage Auto fuse Connection

type

Decade

constructed

Fraction of

1-phase

neighbors

25 A No Apartment 10 100%




35 A No Business & Ap. 7 9%

40 A Yes Apartment 10 0%

??? ??? Business 8 55%

40 A No Other 9 50%

??? No Apartment 10 60%

Number of

phases

1

3

1

3

3

???

???

???

???

Explaining fields Target field


Analytic table

Statistical training of a function from explaining fields to target field


type

Decade

constructed

Fraction of

1-phase

neighbors






Number of

phases

1

3

1

3

3


??? ??? Business 8 55%

40 A No Other 9 50%


???

???

???

???


f


Analytic table

Use trained function to predict missing data


type

Decade

constructed

Fraction of

1-phase

neighbors






Number of

phases

1

3

1

3

3


??? ??? Business 8 55%

40 A No Other 9 50%


3

3

1

3


f

Probability that

a prediction is

correct is also

included

Can e.g. be used

to prioritize

review of data


Prediction of missing data


type

Decade

constructed

Fraction of

1-phase

neighbors

Number of

phases

871685900009726493 25 A No Apartment 10 100% 1


type

Decade

constructed

Fraction of

1-phase

neighbors

Number of

phases

871685900009730377 25 A No Apartment 10 60% 3


type

Decade

constructed

Fraction of

1-phase

neighbors

Number of

phases

871685900100096846 ??? No Apartment 10 60% 3

What is the business case?

25


Fast learning curvedue to efficient knowledge transfer

between experts and data miners

Lessons learned to improve the

data quality

Prerequisite: Data ownership in the business

Visual

inspect

ions

Expert

know-

ledge

Data

mining

Advantages of triangle approach

Higher data qualitybecause validity of data is examined

in up to three different ways

Cheaper, more insightcompared to the traditional way


Data maturity

Business cases for a better data qualityB

us

ine

ss

va

lue

Better data

quality

More accurate

asset condition

More accurate

asset valuation

Better integration of

IT systems

Risk reduction

Better transparency for

customers about outages

and repairs

Lower annual spend

for asset investments

approx. by 1% to 2%

Reduce investments

in asset infrastructure

and maintenance

Better planning of

future workloads

Thank you

Contact information:

F name MI. L name

Title

Address

Phone number

Documents

Improved Asset Data Quality - UK & Ireland SAP Users Group · PDF file© 2014 SAP SE or an SAP affiliate company. ... Improved Asset Data Quality © 2014 SAP SE or an SAP ... EAN Amperage