Enterprise Data Mashup and Data Matching

A mashup is a web page or application that uses or combines data or functionality from two or many more external sources to create a new service. Mashups can be considered to have an active role in the evolution of social software and Web 2.0. Enterprise Mashups are secure, visually rich web applications that expose actionable information from diverse internal and external information sources. So says Wikipedia.

I think that Enterprise Mashups will need data matching – and data matching will improve from data mashups.

The joys and challenges of Enterprise Mashups was recently touched in the post “MDM Mashups: All the Taste with None of the Calories” by Amar Ramakrishnan of Initiate. Data needs to be cleansed and matched before being exposed in an Enterprise Mashup. An Enterprise Mashup is then a fast way to deliver Master Data Management results to the organization.

Party Data Matching has typically been done in these two often separated contexts:

  • Matching internal data like deduplicating and consolidating
  • Matching internal data against an external source like address correction and business directory matching

Increased utilization of multiple functions and multiple sources – like a mashup – will help making better matching. Some examples I have tried includes:

  • If you know whether an address is unique or not this information is used to settle a confidence of an individual or household duplicate.
  • If you know if an address is a single residence or a multiple residence (like a nursing home or campus) this information is used to settle a confidence of an individual or household duplicate.
  • If you know the frequency of a name (in a given country) this information is used to settle a confidence of a private, household or contact duplicate.

As many data quality flaws (not surprisingly) are introduced at data entry, mashups may help during data entry, like:

  • An address may be suggested from an external source.
  • A business entity may be picked from an external business directory.
  • Various rules exist in different countries for using consumer/citizen directories – why not use the best available where you do business.

Also the rise of social media adds new possibilities for mashup content during data entry, data maintenance and for other uses of MDM / Enterprise Mashups. Like it or not, your data on Facebook, Twitter and not at least LinkedIn are going to be matched and mashed up.

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3 thoughts on “Enterprise Data Mashup and Data Matching

  1. Amar Rama 7th April 2010 / 03:44

    Hi Henrik,
    Good points. It is definitely worth remembering that enterprise mashups do not have to awe inspiring. Your point about using a mashup to reduce errors during data entry is a great example of a practical and focused application.

    Social media mashups are inevitable imho. Rapportive.com for example is a new gmail plugin that calls itself “social CRM built into gmail”.

  2. Greg Wenden 14th April 2010 / 15:42

    Henrik,

    We’re starting to look at how we can use (and provide) data for tasks like this. I’d be interested to hear what you think of the wiki-data website and its data that we’ve recently started to publish.

  3. Henrik Liliendahl Sørensen 14th April 2010 / 16:04

    Amar and Greg, thanks for commenting and supplying the great links to data in the cloud.

    Greg, first of all I think the service is fantastic.

    As I am a search geek and always looking for handling of diversity I have found an area for improvement.

    If I look for a company in my home town “Copenhagen” I find it. But if I write “København”, which is the local name, I don’t. You could include support for such synonyms.

    If I look for a specific bank called “Forstædernes Bank” I find it. If I write in only English characters “Forstaedernes Bank” I don’t. This will probably only be solved in a practical way by adding fuzzy search.

    But again, a great service as it is:

    http://www.wiki-data.com/

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