Processor Families

A Flexible and Scalable Data Quality Solution

Functions from a single dn:Director Processor Family can be used in isolation to support a narrow–focus project, but combining them in a single integrated environment gives unprecedented capability, allowing you to mix and match individual data quality processors in any order, as opposed to restricting the process to a set of discrete stages.

Profiling and Analysis

Profiling and Analysis provides the ability to understand your data, highlighting the key areas of pain and helping you to not only analyze the business impact of these problems but to begin defining business rules directly from the data. This avoids pre-conceptions of how the data hangs together and quickly identifies weaknesses in existing business processes and technology implementations.

Transformation

Transformation provides the ability to start improving your data. This can be anything from a simple cleansing project to a more complex restructuring, standardization or enhancement exercise. Used in conjunction with Profiling and Analysis, Transformations can be used to check against defined business rules and transform data on the fly against those rules, providing flexible and adaptable data firewall.

Parsing

Text data is very rarely available in a completely neat and ordered fashion. Typical problems include:

Constructed fields, where a customer ID may be made up of a location code, a customer reference and an account manager code.
Misfielded data, such as names, comments or telephone numbers appearing in an address block.
Poorly structured data such as addresses, where data can flow from one field to the next.
Notes fields, typically used to store information that the data structure doesn’t support, can contain a wealth of useful semi-structured data that dn:Director can analyze and extract into a useful form.

All of these problems can be solved using the Parsing processor. Using a data–driven approach to rapidly ‘tag’ or describe data, Parsing can turn semi-structured data into usable structured information and by describing data and its structure, can significantly enhance any matching process.

Phrase Profiling

Phrase Profiling is Datanomic’s unique approach to understanding text data. Using a powerful profiling algorithm it helps you to identify key information buried within large datasets and, used in conjunction with the Parsing processor, can deliver unprecedented understanding of your data.

Matching

Matching is a key component of many data quality projects, and can be used to support different activities such as de–duplication, consolidation, Customer Data Integration (CDI) and Master Data Management (MDM). The Matching module provides a number of powerful matching capabilities, with flexible yet intuitive rule configuration enabling you to tune the rules to suit the task and supporting an iterative approach. A separate and ‘simple review only’ capability means you can expose the match results for review, without access to the underlying rules configuration.

Used in conjunction with the other modules, Matching becomes an extremely powerful and flexible solution that can be tailored to produce impressive results in any number of differing projects.

Reporting

Reporting utilizes Datanomic’s dn:Dashboard to provide a view on data quality within an organization. Using a web browser, workers and managers can monitor and review ongoing data quality against defined metrics. A simple traffic light system allows problems to be quickly identified and dealt with before they start to cause significant business impact. Graphical views show data quality trends over time, helping your organization protect its investment in data quality, by giving visibility to the right people.