Content Sneak Peek

Catch a glimpse of the sessions you'll find at the Conference. Watch the recordings now:

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End-to-End Power BI

Peter Myers

Find out how to use Excel authoring tools to discover, acquire, transform, relate, and enrich data for analysis and reporting. You’ll be ready to take advantage of these self-service technologies to get the most from your company’s data.

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Predictive Analytics for Absolute Beginners

Mark Tabladillo and Artus Krohn-Grimberghe

Interested in getting started in predictive analytics? In this 1-hour preview of the upcoming full-day pre-conference session, we'll cover the main motivation for learning about predictive analytics and highlight some of the technologies available.

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Adding Valuable Techniques to Your Data Science Toolbox

Mark Whitehorn

This preview of the upcoming full -day pre-conference session day introduces less well-known but very useful techniques and methodologies for understanding complex patterns in data.The techniques you will hear about are immensely useful in turning masses of data into useful information.

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Has Big Data Killed the EDW?

Stacia Misner

Big Data technologies have given us the ability to process massive amounts of data at a low cost, and yet the Enterprise Data Warehouse (EDW) still plays a key role in most corporate IT shops. Is it time for EDWs to transition? Or is the future of EDW doomed because we now need to solve different problems?

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Advanced Analytics in Excel 2013

Dejan Sarka

Learn how to use PowerPivot data for data mining, how to combine Big Data with PowerPivot data, how to use data mining models in PowerPivot, and how to mash up data when you don’t have common identification. 

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Introduction to Querying in DAX

Marco Russo

Get introduced to the Data Analysis eXpressions (DAX) language to query both Tabular and PowerPivot data models. Practical demos will have the right pointers to start writing your own DAX queries.

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Panel: Myths, Misunderstandings, and Successes in Data Analytics

Karen Lopez,  Stacia Misner,  Joseph D'AntoniLynn Langit

Big Data, Business Analytics, Data Analytics, NoSQL, Relational . . . do we even agree on what we mean by these terms? In this panel session, industry thought leaders discuss and debate the most common myths, truths, and mostly-truths of new and traditional approaches for enterprise data management and analytics.

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Power Query: Beyond the Basics

Chris Webb

You may be asked to deliver complex data sets in Power Query that require some knowledge of advanced functionality, including the M language. This session examines what these requirements might be, how to implement them, and how best to deploy them to end users. We cover how to create common types of calculations in M, how to best use functions, calling to web services, and OData data sources.

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Small Big Data: Phase 0 - Data Hygiene

Lynn Langit

Get ready for Big Data with practical tips from this sneak peek of my upcoming full-day pre-conference session as we talk about the starting point for every Big Data project: getting your current (data) house in order. Drawing from real-world experience, this session covers patterns, tools, and techniques for improving data hygiene.

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DataViz You Thought You Could NOT Do with SSRS

Jason Thomas

Despite SQL Server Reporting Services (SSRS) being a very flexible and adaptable tool when it comes to visualization techniques, very few venture beyond its ready-made charts.  Join this session as we bust popular myths around "impossible in SSRS" visualizations and construct them live in SSRS!

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Implementation and Design on the Parallel Data Warehouse

Jason Strate

If you need to design a data warehouse that scales for today and into the future, then you need to know about Microsoft's Parallel Data Warehouse (PDW). In this preview session, we review the architecture of PDW and discuss what it takes to migrate a data warehouse to PDW and what bottlenecks you could expect to see in a migration.

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An Introduction to Predictive Modeling

Carlos Bossy

Learn how to solve a real-world data mining problem using the entire development life cycle of a predictive model. Learn the essentials required to harness the power of a decision tree algorithm to develop and optimize a production-ready predictive model. Then you will learn how to make the most of a predictive model by seeing how to deploy it and use in your applications and reports.

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