The PASS Business Analytics Conference (BAC) will be in San Jose, CA on May 7-9. You can get a jump start on some of the most notable presentations with these recorded sessions from the 24 Hours of PASS, BAC Edition. These include some great talks from Peter Myers, Mark Tabladillo, Mark Whitehorn, Stacia Misner, Dejan Sarka, Marco Russo, Karen Lopez, Chris Webb, Lynn Langit, Jason Thomas, Jason Strate and Carlos Bossy.
These are just the tip of the whole big iceberg that is the BAC. I encourage you to attend. Also, watch the streaming keynotes and selected sessions, attend your local PASS Chapter events and virtual chapters. This information is accessible from the PASS site.
From the BAC Sessions Sneak Peak page:
Get a sneak peek at some of the Business Analytics and Business Intelligence best practices, expert tips, and demos you’ll find at the PASS Business Analytics Conference. We recently hosted an online event featuring 12 back-to-back webcasts from various BA Conference speakers. Watch the recordings now:
End-to-End Power BI
The aim of this session is to excite you with the potential of Microsoft’s new self-service suite of BI products and collaboration platform named Power BI. You will learn about four “Power” authoring products available in Excel, and how they function to discover, acquire, transform, relate and enrich data for analysis and reporting.
Topics include Power Query, PowerPivot, Power View, and Power Map. This session has been designed to provide perspective across the Power BI story
Speaker: Peter Myers, BI Expert, Bitwise Solutions
Predictive Analytics for Absolute Beginners
In this one-hour preview presentation, we cover the main motivation for learning something about predictive analytics. We will show some of the Microsoft technology which will be in the Pre-Conference session on May 7. We also will be answering any questions you may have. This session and the Pre-Conference session are for absolute beginners.
SPEAKERS: Mark Tabladillo, Data Mining Architect, MarkTab Consulting and Artus Krohn-Grimberghe, Assistant Professor, Analytic Information Systems and Business Intelligence
Adding Valuable Techniques to your Data Science Toolbox
Data Science requires us to see and understand complex patterns in data, so we use techniques like data mining to uncover them. There are other, less well-known but equally useful techniques and methodologies that we can add to our toolbox.
I’ll be covering a range of these in the full day, Pre-Conference, session that I am giving at The PASS Business Analytics Conference and I’ll use this one hour session to introduce you to a couple of my favorites. It is worth stressing that I love these techniques, not just because they are fascinating in their own rights but because I have found them immensely useful in my work of turning masses of data into useful information.
This session will NOT include any heavy (or, indeed, light!) mathematics; it is focused on how an understanding of these techniques can be of real benefit in your day-to-day work.
SPEAKER: Mark Whitehorn, Co-Founder, Penguinsoft Consulting Ltd.
Has Big Data Killed the EDW?
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? This session will answer your questions about the future of EDW.
SPEAKER: Stacia Misner, Principal, Data Inspirations
Advanced Analytics in Excel 2013
Excel is “the” analytical tool in Microsoft’s suite for advanced analysts. Of course, you know that Excel 2013 includes PowerPivot and Power View add-ins out of the box. You also may have heard that you can use Big Data and Azure DataMarket data in Excel and that you can mash up data from different sources. However, you probably don’t know how to use PowerPivot data for data mining, how to combine Big Data with PowerPivot data, how to use data mining models in PowerPivot, or how to mash up data when you don’t have common identification.
This session is not about introducing the cool new features; instead it will focus on the most advanced part of Excel analytics: data mining with Excel.
SPEAKER: Dejan Sarka, Mentor, Dejan Sarka s.p.
Introduction to Querying in DAX
The DAX (Data Analysis Expressions) language can be used to query a Tabular and PowerPivot data model. This session will introduce the syntax of DAX queries and will show several scenarios in which you can use DAX as a query language, such as Excel and Reporting Services, as well as creating a quick prototyping environment for new DAX measures in your model.
There will be many practical demos where you will learn which tools you can use to write and format the DAX formulas and queries, including SQL Server Management Studio, DAX Studio, and DAX Formatter. At the end of the session, you will have the right pointers to start writing your own DAX queries.
SPEAKER: Marco Russo, Consultant, SQLBI
Panel: Myths, Misunderstandings, and Successes in Data Analytics
Big Data, Business Analytics, Data Analytics, NoSQL, Relational . . . do we even agree on what we mean by those terms? In this panel session, industry thought leaders will discuss and debate the most common myths, truths, and mostly-truths of new and traditional approaches for enterprise data management and analytics.
SPEAKERS: Karen Lopez, SR. Project Manager & Architect, InfoAdvisor, Stacia Misner, Principal, Data Inspirations, Joseph D’Antoni, Solutions Architect, Anexinet, Lynn Langit, Found, Lynn Langit
Power Query: Beyond the Basics
You already know that you can accomplish a lot within the Power Query user interface. If you are a data steward, however, 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 will examine what these requirements might be, how to implement them, and how best to deploy them to end users.
We will cover how to create common types of calculations in M, how to best use functions, calling to web services, and OData data sources, and more. We will also discuss the best way to use Power Query with the rest of the Power BI stack, especially PowerPivot.
SPEAKER: Chris Webb, Director, Crossjoin Consulting Limited
Small Big Data – Phase 0 – Data Hygiene
In this talk, we will talk about the starting point for every Big Data project – getting your current (data) house in order. Drawing from real-world experience, Lynn Langit will discuss patterns, tools, and techniques for improving data hygiene with SQL Server. These will include use of SSDT, 3rd party tools, such as D&B and Melissa Data, and more.
Learn how to get ready for Big Data with practical tips from this session.
SPEAKER: Lynn Langit, Founder, Lynn Langit
DataViz You Thought You Could NOT Do with SSRS
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. Most of the time, all it takes to build a chart considered “outside the scope” of SSRS is a bit of lateral thinking. Sometimes, we need to go a little further and use custom code. Join this session as we bust popular myths around "impossible in SSRS" visualizations and construct them live in SSRS!
SPEAKER: Jason Thomas, Consultant, Mariner
Implementation and Design on the Parallel Data Warehouse
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 will review the architecture of PDW with an emphasis on what makes PDW the solution of choice for data warehouses.
We will discuss what it takes to migrate a data warehouse to PDW and what bottlenecks you could expect to see in a migration. Through live demonstrations, you will witness the power and performance of PDW and see the performance impact of PDW’s data distribution.
SPEAKER: Jason Strate, Database Architect, Pragmatic Works
An Introduction to Predictive Modeling
This session will show you how to solve a real-world data mining problem by demonstrating the entire development life cycle of a predictive model. You will learn the essentials required to harness the power of a decision tree algorithm to develop and optimize a production-ready predictive model. You will also see how to iterate through the process to improve the model’s effectiveness. 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
SPEAKER: Carlos Bossy, Principal Consultant, Quanta Intelligence
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