Tag Archives: Address Validation
Informatica Cloud Winter 2013 has arrived. This is the fourteenth release of the company’s award-winning family of cloud integration applications and integration platform as a service (iPaaS), which has now expanded to include Informatica Cloud Master Data Management (MDM). In this post I’ll provide an overview of the new cloud integration and cloud data quality capabilities. Be sure to register for a 30 day trial and/or attend the release webinar on Thursday to see Informatica Cloud in action.
In my last post, I shared a minor epiphany I experienced working on a project to merge data sets from two different oil companies in which I fully recognized the difference between an address and a location. Borrowing from an assortment of definitions, a location describes a point or an area within a dimensional space. A location is frequently mapped to two dimensions on the surface of the earth, usually latitude and longitude, but may encompass three dimensions (including altitude). On the other hand, an address is a text string that is formatted according to a definition provided by a postal authority representing a location directing parcel or package delivery. (more…)
I read an article the other day called the “The 9 Dirty Little Secrets of CRM”. As a user of CRM systems for many years including salesforce.com (which I rate highly), I agree with many of the statements around the secrets of successful CRM. Firstly it’s all about the data! If high quality data is entered and data quality processes are in place to maintain the data, then user adoption will grow and the CRM implementation will be perceived to be a success.
The first step is a data quality audit/assessment which identifies data quality issues associated with the key data fields which drive your processes. Let’s assume a data quality audit results in a score of 65% – this means that your CRM processes will be only 65% effective due to the quality of the data. So if the CRM application is to support “attracting and retaining” customers and “increasing revenues via cross-selling”, management need to be very aware of the impact low quality data has on the effectiveness of the CRM processes. The data quality metrics are based on defining data quality dimensions including completeness, conformity, consistency, duplicates and accuracy, and applying these dimensions to the data fields. So for example a customer or prospect record includes the name, address, email and telephone number fields. Each field can be audited using several dimensions. The results are aggregated, resulting in the overall score e.g. in this case 65% – which is for many unacceptable. (more…)
This week, we announced the acquisition of AddressDoctor, the market leader of global address validation with coverage for over 200 countries and territories. This is another example of how we are continually working to deliver the most advanced data quality products to our customers. Address Doctor provides an address validation engine which is already fully integrated into Informatica Data Quality. This acquisition is simply another step towards market leadership for Informatica in the enterprise data quality market. Rob Karel from Forrester referred to our vision of pervasive data quality – supporting all roles, all applications, all data domains and all stages of the data integration lifecycle in his blog.
Let’s focus on “all data domains” and how the AddressDoctor acquisition supports this key criteria for successful enterprise data quality. (more…)