1 / 11

DQS: Business Logic Meets Enterprise Integration

DQS: Business Logic Meets Enterprise Integration. September 14 th , 2013. About Me. Senior Consultant at Pragmatic Works Present at SQL Saturday’s, code camps, SQL chapters Blog at intelligentsql.wordpress.com Twitter : @ sqlbischmidt. DQS. DQS was introduced in SQL Server 2012

gordon
Download Presentation

DQS: Business Logic Meets Enterprise Integration

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. DQS: Business Logic Meets Enterprise Integration September 14th, 2013

  2. About Me • Senior Consultant at Pragmatic Works • Present at SQL Saturday’s, code camps, SQL chapters • Blog at intelligentsql.wordpress.com • Twitter : @sqlbischmidt

  3. DQS • DQS was introduced in SQL Server 2012 • Allows us to bring data cleansing and business logic into our data warehouse/data mart and apply rules and standardization to it to create a cleaner reporting environment • NOT a replacement for Master Data Management

  4. Why use it? • Fixes “incorrect” data • Clean up bad data • So our inserted row into our final table is clean

  5. Knowledge Base • The database of knowledge! • About data! • Understands the data, and helps maintain integrity over itself • i.e. Florid is the same as Florida • Consists of domains • Domain Management creates and manages domains within the knowledge base (KB) • Knowledge discovery learns patterns in your data and adds that machine knowledge into your knowledge base • Matching policy teaches DQS where one records equals another. • John Smith is the same as John B Smith

  6. Domains • Single domains are individual representations of data in a data field • Manage key attributes about that field • Distinct list of values that should be allowed • Composite domains exist from one of more single domains and can use cross-domain rules or reference data sets to further clean the data • Collections of single domains

  7. Data Quality Project • Uses a knowledge base as the source • Improve the data by Cleaning & Matching • Run against already existing data. • Warehouse, anyone? • Exports data to SQL Server or Excel • Clean it, then match it

  8. Administration • Activity Monitoring • Cleansing and creating that has occurred in the environment • What consumed it and when? • Configuration • Add Azure Data Market account • Set min score for cleansing (70%) and matching (80%)

  9. SSIS Integration • In 2012, there is a DQS component that can consume a knowledge base • Clean the data as it’s coming in!

  10. The DQS Ecosystem • Discover • Identify your data • Match • Create the standards • Cleanse • Standardize your company data • Match • Run the rules

  11. The End • Comments are welcome! • Please feel free to contact me via twitter (@sqlbischmidt) or email at sqlbischmidt@gmail.com or cschmidt@pragmaticworks.com

More Related