Profiler Object is a multiplatform API designed to analyze data in a variety of column types to ensure it adheres to the limitations imposed by the user-specified type. Profiler Object provides a great number of statistics, at varying levels of details, allowing users to develop informed strategies on how best to manage and employ their data.

Profiler Object was designed to tackle two possible scenarios

  1. Discovery- In this scenario, Profiler analyzes new data before it's inserted into a data warehouse. It ensures the data is correctly fielded, consistently formatted, standardized, etc. Detecting and fixing data problems before data is merged into a data warehouse saves time and money.
  2. Monitoring- It is difficult to maintain a comprehensive set of business rules in a data warehouse that supports multiple methods of access (Web, desktop, tablet, phone, etc.). Profiler addresses this problem by continually analyzing the warehoused data to ensure data quality.

Benefits:

  • Discovers existing weaknesses in your database (duplicates, badly fielded data, bad data, etc.)
  • Enforces business rules on incoming records at point-of-entry
  • Allows the building of metadata repository that aids in data governance and building strategic datamarts
  • Maintains data quality by continuously monitoring data after its merged into a data warehouse
  • Enforces business rules on incoming records, so you can maintain data standardization

Features:

  • Allows regexes and error thresholds to be set for full-fledged monitoring
  • Uses sophisticated matching to output fuzzy and exact match counts
  • Available as a commercial C++ Data Profiler API that can be OEM’d into custom apps
  • Uses every available general profiling count on the market today
  • Leverages sophisticated parsing technology to identify, extract, and understand data
  • Brings data quality analysis to data contained in columns
  • Returns numerous string and numeric stats from averages to quartiles to minimum and maximum values, etc.

Monitor, Measure & Analyze Data with Proler Object
Monitor, Measure, & Analyze Data with Profiler Object

Data Analysis

Profiler Object provides three levels of data analysis:

  • General Formatting:Used to determine if the input data ‘looks’ like what is expected (used for names, emails, postal codes, etc.)
  • Content Analysis:Relies on reference data to determine if the input data contains information consistent with what is expected
  • Field Analysis:Determines if the input data has duplicates

Knowledge-Based Analysis

Profiler can analyze a wide variety of data types:

  • Contact Name
  • Title or Department
  • Company
  • Address
  • City
  • State or Province
  • ZIP® or Postal Code
  • Country
  • Phone
  • Email Address