DQS Training

Explore data cleansing techniques on the Beebe won database, standardizing country names and city spellings, correcting hotel categories, and removing duplicates before domain creation.

Create and manage knowledge bases and domains in data quality services, map external data to domain values, refine rules and synonyms, and publish for data discovery and cleansing.

Explore data cleansing operations by building a data cleansing project in data quality services, using a knowledge base and cleansing activities to correct spellings, standardize country names, and manage duplicates.

Learn to create an SSIS package for data cleansing to automate cleaning and loading of the hotel knowledge base data, with mappings and a scheduled job.

Create and apply matching policies to identify duplicates across country, city, address, coordinates, and hotel name, using prerequisites and exact vs similar matching to score and remove duplicates.

Launch a deduplication project within a data quality framework, apply matching policies, and use survivorship rules such as most complete and longest record to remove duplicates and export results.

Explore the purpose of each dqs database, detailing cleansing and duplication operations, the behind-the-scenes programs and stored procedures, and how source data flows to staging and knowledge bases.

Create and apply domain and composer domain rules in a data quality knowledge base to cleanse company, city, state, and email data using regular expressions and normalization.

Manage data quality projects and knowledge bases by opening, deleting, renaming, locking, and exporting or importing domains and knowledge bases; edit domain values and publish updates.

Explore how to monitor and manage data quality activities with an interactive activity monitor, including filtering by status, viewing activity steps, and exporting profiler data to Excel.

back up dqs databases on sql server 2016 and restore to sql server 2017, preserving knowledge bases and projects with relocated files and a stored procedure to reconfigure target instance.

Explore dqs configurations and data profiling to assess data quality, set a minimum score for suggestions and auto correction, and perform cleansing with a knowledge base and domain values.