We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byJoselyn Linson
Modified over 4 years ago
Inaport Training Fuzzy Matching
© Copyright 2010 InaPlex Inc Matching Process of deciding which record or set of records in the target table(s) should be updated Alternatively, decide if record already exists and take appropriate action
© Copyright 2010 InaPlex Inc Matching Techniques Inaport supports different ways to match Standard build expressions on source and target Fuzzy Refine Standard to allow for poor data SQL Use SQL SELECT instead of expressions
© Copyright 2010 InaPlex Inc Fuzzy Matching Standard Matching can use any combination of fields can use expressions BUT Ultimately is restricted to exact match “InaPlex” <> “Innerplex Ltd”
© Copyright 2007 InaPlex Limited Fuzzy Matching Fuzzy matching compares source and target, and gives a similarity score Score measures how “close” two strings are Score = 1 : Perfect match Score = 0 : No match “InaPlex” and “inaplx” : 98% “InaPlex” and “innerplex” : 87% “InaPlex” and “ibm” : 49% See Tools – Fuzzy Match Demo
© Copyright 2010 InaPlex Inc How it Works As with Standard matching, Fuzzy match Can use any field or combination of fields Reads the match fields Builds an in memory index for each table The target match expression is applied to the field data read from the table
© Copyright 2010 InaPlex Inc How it Works Set scoring levels Score > Upper good match – accept immediately Lower < Score < Upper Possible match – user review Score < lower Not a match – reject No match < Lower < Possible < Upper < Good No match < 85% < Possible < 95% < Good
© Copyright 2010 InaPlex Inc How it Works When a source record comes in: Source expression applied to build match value Source match value scored against every value in target index “Best” matches used – you set boundaries No match < Possible match < Good match No 0.85 Possible 0.95 Good
© Copyright 2010 InaPlex Inc How it Works User Review Shows the source record and possible matches in target User can select one or more records as match Options Review “good” and “possible” matches –For testing purposes Review just “possible” matches –If there are no possibles, good and no match accepted automatically No review –Good and no match accepted automatically –Possible treated as bad
© Copyright 2010 InaPlex Inc How it Works Customise User Review May need to see more than the target table to decide on match Can also display associated tables E.g. Address, Contact Can also select which fields from associated tables to display
© Copyright 2007 InaPlex Limited Example – Operation Tab Select Fuzzy Match from Match Type
© Copyright 2010 InaPlex Inc Example – Match Tab Specify the base match criteria Source and target match expressions Boundary scores for no, possible, good matches Cluster Match covered later
© Copyright 2010 InaPlex Inc Example – Match Tab Set up the User Review Can choose No review – use in batch mode Only possible matches – accept good matches Good + possible – review all matches
© Copyright 2007 InaPlex Limited Example – User Review Shows possible matches at run time Source record Possible matching target records, with score If configured, child records of selected target record Allows selection of desired matches
© Copyright 2010 InaPlex Inc Clustering Fuzzy Matching is powerful, flexible BUT Every source record must be scored against EVERY target match, then highest scores selected 100,000 records in target => 100,000 scores per source record Solution is CLUSTERING
© Copyright 2010 InaPlex Inc Clustering Specify an expression to sort target records into clusters Then an equivalent expression for source to sort it into one cluster Finally scoring only done against members of the selected cluster 100,000 target divided into 20 clusters 5,000 records per cluster => 5,000 scores per source record
© Copyright 2010 InaPlex Inc Clustering Cluster expression should: Sort target into roughly equal groups Guard against allocating source to wrong cluster Examples First letter of company name Zip/Post code Phone area code
© Copyright 2010 InaPlex Inc Clustering Alpha Corp Zulu Corp Beta Corp Source record scored against every record in target No clustering established
© Copyright 2007 InaPlex Limited Clustering Set up clustering based on first letter of company name
© Copyright 2010 InaPlex Inc Clustering Alpha Corp Zulu Corp Beta Corp Source record only scored against records in “b” cluster Beta Corp Brown Corp Cluster on first letter
© Copyright 2010 InaPlex Inc Clustering Important Note Because source records will only be scored against one cluster, if clustering is poorly done can lead to missed matches “naplex” would look in “n” cluster, not “I” Cluster expression does NOT have to use same fields as match E.g. Match on name, cluster on ZIP code
© Copyright 2010 InaPlex Inc Summary Fuzzy matching provides powerful new tool for handling complex, dirty data Need to Use carefully, especially clustering Allow of overhead of user review
© Copyright 2010 InaPlex Inc THANK YOU www.inaplex.com www.inaplex.com/cs/forums
FedEx Ship Manager® at fedex.com Shipping Administration
Topic: Sales Tax and 1099 Reporting
Inaport Training Introduction to Matching. Matching The purpose of Inaport is to: Extract data from a source Transform that data Load into a target Loading.
User Friendly Price Book Maintenance A Family of Enhancements For iSeries 400 DMAS from Copyright I/O International, 2006, 2007, 2008, 2010 Skip Intro.
Organisation Of Data (1) Database Theory
Microsoft Office Illustrated Fundamentals Unit K: Working with Data.
Ultimate Bundle Overview Products Benefits Technical Requirements Licensing Pricing Valid until 01-Sep-2010.
Background Virtual memory – separation of user logical memory from physical memory. Only part of the program needs to be in memory for execution. Logical.
Microsoft ® Access ® 2010 Training Create queries for a new database.
Fuzzy Duplicates Analysis with ACL
Company Confidential 1 © 2005 Nokia DBUpgradeTool_ ppt / / JMa A Database Upgrade Tool Nokia Networks Jukka Maaranen.
Inaport Training Standard Matching. © Copyright 2010 InaPlex Inc Matching Process of deciding which record or set of records in the target table(s) should.
Copyright I/O International, 2013 Visit us at: A Feature Within from Sales Rep User Friendly Maintenance – with Zip Code.
1 of 30 G/L Journal Authorisation / DA00594-w1 Last updated: G/L Journal Authorisation.
Concepts of Database Management Seventh Edition
Concepts of Database Management Sixth Edition
User Friendly Customer Ship-To Maintenance A Family of Enhancements For iSeries 400 DMAS from Copyright I/O International, 2006, 2007, 2008, 2010, 2011.
Classifications and CASCOT Ritva Ellison Institute for Employment Research University of Warwick.
Queries Help Topics Using the Access 2007, you can press the F1 to pop up the help windows, where you can search the following topics to help to generate.
C++ for Engineers and Scientists Third Edition
© 2018 SlidePlayer.com Inc. All rights reserved.