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Find & fix errors with expert Data cleansing services

Make your data reliable and usable with our data cleansing and validation services. Our team quickly detects inaccuracies and rectifies errors

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Reliable, straight forward data cleansing services from a proven specialist

Cleansing And Cleaning a Wide Range of Data

How We Do It: The Sharecat Data Cleansing and Formatting Process

Low-Quality Data is a Problem You Can't Afford

Gain a Competitive Advantage With Our Data Cleansing Solutions

Why Pick Sharecat for Data Cleansing

FAQs - Data Cleansing

Reliable, straightforward data cleansing services from a proven specialist

Functional Location

ABCC-11-DDD-94523
ABCC-11-DDD-94524
ABCC-11-DDD-94526
ABCC-11-DDD-94527
ABCC-11-DDD-94529

Technical obj. type

ANALYZER
INSTRUMENT
INSTRUMENT
INSTRUMENT

Technical identification no.

Serial Number

Manufacturer part number

EJX430A-JAA5G-919DZ/SU2/C3/T01
EJX110A-JMS5G-919DZ/SU2/C3/T13
EJX110A-JMS5G-919DZ/SU2/C3/T13
EJX110A-JMS5G-919DZ/SU2/C3/T13
EJX110A-JMS5G-919DZ/SU2/C3/T13
EJX110AJLS5GB19DGSU2X2HCC3N4CA

Size/dimension

Gross Weight

0
0
0
0
0
0
0

Construction year

Construction month

Manufacturer of asset

INST. CO.
INST. CO.
INST. CO.
INST. CO.
ANALYSIS INC.
ANALYSIS INC.

Model number

EJX430A
EJX110A
EJX110A
EJX110A
TDLS200
EJX110A

Item ID

Item 1

Item 2

Item 3

Manifactuer

Emerson Fisher

Fisher

Fisher C

Should Be

Fisher Controls

Fisher Controls

Fisher Controls

  • Or multiple ways to write “needle valve
    • “Needle valve”
    • “Vlv, needle”
    • “Needle vlv”
  • Incorrect or incomplete input such as:
    • Typos due to data cataloguing by traditional “low cost” service providers that don’t understand the data they are handling, for example:
      • In manufacturer names

Field Name

Manufactuer

Input

Caterpliar

Should be

Caterpillar

  • In model numbers:

Field Name

Manufactuer

Part Number

Input

Rosemount

305ITG3A2B21KE7M6T1P8Q4Q8C4C5

Should be

Fisher Controls

3051TG3A2B21KE7M6T1P8Q4Q8C4C5

A single lowercase “L” where there should be a number “1” makes the difference between useful and useless data.  

(Find out how we prevent this problem in our Cataloguing Services).

  • Model numbers are listed instead of part numbers, e.g. Yokogawa “EJX630A” is a model of pressure transmitter and not a part number, you can’t order based on model number alone.
  • Incorrect unit prices – typically items where the average price is recorded as less than 1.
  • Wrong links and references, such as:
    • Document referenced has not been provided
    • Referenced functional location or tag doesn’t exist.

Cleansing And Cleaning a Wide Range of Data

How We Do It: the Sharecat Data Cleansing and Formatting Process

Low-Quality Data is a Problem You Can’t Afford

Gain a Competitive Advantage With Our Data Cleansing Solutions

Why Pick Sharecat for Data Cleansing?

Get in Touch Today

Are you ready to transform your data?

If you’re ready, we’d love to talk to you to find out if Sharecat Data Services is the right partner to help remove restrictions and unlock value through making your data more reliable and accurate.

Get in Touch

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FAQ - Data Enrichment

1. What is data enrichment, and how is it different to data cleansing?

2. Why is data enrichment needed in the first place?

3. What types of data can be enriched?

4. How does data enrichment improve decision-making?

5. Is my data secure during the enrichment process?

FAQ - Data Cleansing

1. What are data cleansing services?

2. How much does cleansing data cost?

3. Why is the Sharecat approach cheaper than traditional data cleansing?

4. Can you show me an example of data cleansing?

5. Do I need to fix all of my errors to get improvements?

6. Is Sharecat Data Services the right partner for me?

7. How long does data cleaning take?

FAQ - Data Cataloging

1. What are data cataloging services?

2. Why should I choose Sharecat for my data cataloging needs?

3. Why is data cataloging required?

FAQ - Data Standardisation

1. Can you give me an example of data standardisation?

2. Why is data standardisation important for master data management?

3. What does the data standardisation process look like?

4. What data standards and classification systems are Sharecat experts in?