Assessing Your Data Quality Needs
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Assessing Your Data Quality Needs
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Whether you are a large corporation struggling to deal with big data, or a small company wanting to improve customer communications, it is important to have clean data. When evaluating your data quality needs, it is important to profile the data you currently have including the extent to which common errors such as duplicate records, name misspellings or incorrect addresses occur. First collect your basic system information e.g. whether you run a CRM or ERP system and if there are any regular data feeds/outputs to/from these systems. Then you can define your current and future data objectives such as standardizing and verifying your data, creating a 360 degree Customer View, deduplication, etc. Whatever your goals, this simple and effective guide will help you through the process of assessing your company’s data quality needs so that you are ready to define the scope of your DQ project.
Transcript of Assessing Your Data Quality Needs
Assessing Your Data Quality Needs
Intro
Assess your data quality needs by following these guidelines:
Profile your current data
Collect system information
Define data objectives
Profile Your Current Data
Where is the data coming from? (CRM, Accounts, Legacy Systems, Lists, etc)
What are the current points of entry?(CRM, Website, POS, Call Center, Batch Feeds, etc)
What are the average number of records processed?
What is the current or desired frequency of processing?
Profile Your Current Data
Standard Data Elements Name Address Phone Number Email Address Date of Birth Social Security Number Customer ID # Login/Password
Product or Part Numbers Price Transaction Data Order Reference # Shipping/Billing Addresses _____________________
Common Data Errors Name Misspellings Incorrect Addresses Duplicate Records Missing Data Incorrect Data Inconsistent Data Unlinked Transactions
Incomplete Transactions Garbage Data Incorrect Formatting Nicknames/Aliases _____________________
Collect Basic System Info
Recruit your technical department to provide information on your company’s System Profile
You should consider the User Profile list when determining the data quality tools you will select in the long run.
System Profile: CRM/ERP Systems Data Warehouse Platform(e.g. SQL
Server, Oracle, etc.) Data Feed Types (i.e. Excel, CSV,
XML, etc.) Extract File Types (i.e. Excel, CSV,
XML, etc.)
User Profile: Marketing Department end- user Mail-house staff Admin level staff with limited
technology training Database administrator Other
Define Technical Data Objectives
Cleanse and standardize data as part of an existing data warehousing initiative
Support enterprise data governance, MDM or other global BI initiatives
Data enrichment & profiling
Data integration & migration
Eliminate unnecessary IT resource strain
___________________________________________________
Define Strategic Data Objectives
Send more targeted communications based on customer mail preferences Reduce wasted advertising spend of inaccurate mailing lists Improve sales and checkout process (Web, Store, Call Center) Improve customer service with better access to global customer data Generate more accurate view of campaign ROI Develop a global demographic picture Automation and enforcement of approved business rules Remain in compliance with industry data requirements Reduce delivery complications and associated overhead Make informed operational and merchandising decisions Maintain a positive brand perception ___________________________________________________
Define Data Quality Objectives
Basic single or two-file deduplication of files Matching of multiple records Address validation Front-end data capture Batch cleansing of records Automation of Data Quality Processes Establish a single, 360 customer view ___________________________________________________
Keep These Things In Mind
Consider data quality challenges you have had in the past, the ones you have currently, and what you might have in the future
Get other departments involved: IT, Marketing, Finance, Customer Service and Operations
Consider what info you are missing. Is it sitting in another department, or is this information that needs to be collected?
Map out the path that data takes in your company to find what works, what is lacking, and where improvements can be made
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