Vancouver PASS

Meeting Details

LUNCHTIME: End-to-End SQL Server Master Data Services  
The Data Catalog in Power BI... and Beyond
EVENING: Cloud-Based Machine Learning for the Developer 

Presentation Abstract

This presentation describes how SQL Server Master Data Services can be used to implement Master Data Management (MDM). It introduces the discipline of MDM and maps common processes to the feature set of Master Data Services.


Topics include defining models, entities, attributes and hierarchies, to store and manage master data. Additionally, administrative tasks including business rules to validate data, the import and export of master data, model versioning, and permission management will be described. The two Microsoft user interfaces (the Master Data Manager web application, and the Excel add-in) will be covered, in addition to T-SQL scripting opportunities to automate master data processes.


This session will be of interest to data stewards, ETL developers and ETL administrators to appreciate what SQL Server 2012 (or 2014) Master Data Services can achieve.


The Data Catalog that currently ships as part of the Power BI for Office 365 provides capabilities for self-service invormation publishing and discovery, enabling users of Power BI to share, discover, understand, and consume data sets created in Power Query.  These capabilities are a vital component of self-service BI, but self-service information managment is just part of the story...

In this interactive session, we will briefly go over the capabilities delivered with the Data Catalog today, followed by a discussion about the high level plans for evolving the Data Catalog moving forward.  Plans include suppose for a more diverse set of data sources as well as integration into additional application experiences.  This is your opportunity to let us know how you would like to see the catalog to evolve!


Machine Learning is a subfield of computer science concerned with systems that learn from data. In this session, learn how a Microsoft Azure Machine Learning solution comes to life: From the creation of a workspace, to the preparation of data, to experimentation with machine learning algorithms, and then finally to the integration and embedding of predictive insights. This session has been specifically designed to describe machine learning fundamentals, and to help enable and inspire existing developers taking their first steps to leverage cloud-based predictive models delivered with Azure Machine Learning. It is guaranteed to thrill you with potential, and excite you with the relative ease in which it can be accomplished.


Peter Myers 
Peter Myers has worked with Microsoft database and development products since 1997. Today, he specializes in all Microsoft BI products and provides mentoring, technical training, and training course content authoring for SQL Server, Office, and SharePoint. Peter has a broad business background supported by a bachelor’s degree in applied economics and accounting, and he extends this with solid experience backed by current MCSE and MCT certifications. He lives in Melbourne, Australia and has been a SQL Server MVP since 2007.
Julie Strauss
Julie Strauss is a Principle Group Manager with Microsoft for the Data Platform based in Redmond.

Wednesday, 2015/05/13, 12pm-2pm   Then again at 6pm-8pm
  • Microsoft Canada Suite 1100 – 1111 West Georgia Street








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