List of Quality Processes - trillium_discovery - trillium_quality - Latest

Allows you to analyze attributes as part of a Quality process flow in the Control Center and in an exported batch script. The Analysis process is created as a Time Series Analysis project so that you can produce a new generation of output every time that you run the process.

Identifies and standardizes business data (non-name and address) and is driven by rules that you can customize to meet specific data requirements. The process uses pattern-recognition to identify, verify, and standardize components of free-form text. It performs these functions:

• Identifies words and phrases in free-form text by their values or masks.
• Produces standardized output in useful formats.
• Uses customized user-defined attributes.
• Uses rules tables that can be customized.
• Corrects misspellings.
• Enables recoding of words or phrases using external tables.

This profiling process allows you to analyze entity business rules in entities within a Quality workflow and view passing and failing rule results.

This process has two major functions:

• Survivorship – Select a user-defined "survivor" record among a group of matching records, using survivor selection rules.
• Commonization – Standardize data, according to user-defined rules, across a set of matching records that are linked by a common key.

Processes unstructured name and address lines to output a series of structured name and address components (such as first name, last name, house number, city, etc.).

• Identifies words and phrases in free-form text by their values or masks.
• Produces standardized output in useful formats.
• Identifies elements of data from the input data file.
• Uses country-specific tables to verify and identify data according to each country’s postal rules and idioms.
• Allows users to customize name and address identification for specific business requirements.
• Defines word and phrase patterns (tokens) for a given country.
• Uses City Directory files to define state/province/county names, city names, and postal codes for a given country.
• Corrects misspellings.
• Enables recoding of words or phrases using external tables.

Allows you to write the output back to your database so you can directly update the target tables without using any other database tools. You can connect a variety of different databases on Windows and UNIX systems, build an integrated process flow, and write the output back to the database.

Enables you to split the data based on the filtering condition you define. A Decision Point can be used anywhere in a process flow and lets you analyze the passing/failing rows or use only the passing rows in the following processes.

You can add a Dependencies profiling process to a Quality workflow to create permanent dependencies from attributes in the input entity. After you run the process, drill down on the output entity to see the permanent dependencies created by the process.

Updates a master file with the data from another file, referred to as the transaction file.

Matches input data to country-specific tables to provide latitude and longitude values.

Scans an input file that contains record data from more than one country, identifies the country-specific data, and then creates one output file per country that contains only the data specific to the country you select. It performs these functions:

• Uses rules files that contain country-related word definitions and tables.
• Specifies how many output files to generate and which countries are identified.
• Uses a country code attribute to identify and score country of origin.
• Uses settings to determine which attributes to inspect when there is no valid country code or the country code is suspect.

You can add a Keys profiling process to a Quality workflow to create permanent keys from attributes in the input entity. After you run the process, drill down on the output entity to see the permanent keys created by the process.

You can add a Load profiling process to a Quality workflow to run a data load and analysis on dynamic input entities or the output of Quality processes. Analysis includes business rules results, discovering keys and dependencies, and analyzing attributes.

Lets you manipulate files with merge keys and split rules. You can define merge keys that determine how files will be merged. You can also create rules to produce multiple output files from a single input file, or split multiple input files into smaller files.

Matches the Customer Data Parser output data to the country-specific Global Address Verification (GAV) tables and returns address details and directory matches. The Postal Matcher performs these functions:

• Verifies and assigns postal codes to address data.
• Assigns delivery point identifiers.
• Standardizes and corrects address components.
• Provides linked data in a presentation form that meets country-specific addressing standards.

Compares records in an input file to an existing reference file. Use this process to update new records within an existing master file (also called a reference file) in the database. For example, after running an initial linking process, you can compare new records in an input file with the initial matched records as your reference file. By comparing the input file to the reference file, you can then verify new records in the reference file and update the file if necessary. The process performs these functions:

• For matches, copies a matching key number from the reference record to the input record.
• For no matches, generates a new key number and appends it to the input record.

Identifies the relationship between records in a file. It performs these functions:

• Uses rules that can identify two levels of business matching as well as two levels of consumer matching.
• Uses comparison routines to determine the level of similarity between records. Results are categorized as Pass, Suspect, or Fail, depending on the similarity of data elements.
• Attempts to match only records that have the same window key so that it does not need to compare every record in the database to every other record.

Resolves transitivity, which is what happens when two records are linked indirectly by a third record. The process creates a relationship among the records that can then be used to represent the entire matched record set.

Selects matching records from an input file and then, based on match keys and select or bypass record directives, the process skips, selects, and reformats data when it creates the output file.

Reads records from input files and sorts them to produce a single output file that is ready for input to the Relationship Linker process in a workflow.

Reads records from input files and sorts them to produce a single output file that is ready for input to the Postal Matcher process in a workflow.

Converts data from one or more entities and formats to a single output entity. It can perform these functions:

• Scan data records for defined shapes (masks) and literal values, and then copy, move, change, or delete the data.
• Recode character attributes, based on a user-defined external table.
• Apply conditional logic to perform an unlimited number of data transformations.
• Make calls to third-party web services.

This Transformer includes the logic required to format data for the Global Postal Matcher. This process will also create a common set of derived attributes (DR_ attributes) that are used in the batch to real-time implementation.

Creates delivery address lines from the attributes output by the Customer Data Parser and Postal Matcher.

This process is only valid in projects that use the Basic Countries (zz) template. It precedes the Sort for Postal Matcher and its purpose it to populate the input attributes the Global Postal Matcher will use to parse, standardize, and validate the addresses.

Produces outputs in a common format and encoding (UTF8) so that you can merge output entities from multiple countries into a single output entity.

User-specified process (usually a third-party application). A user must specify the path to the parameter file and executable.

Reads records from input files and sorts them to produce a single output file that is ready for input to the next process in a workflow as defined by the user.