Sessions Overview

Engaged Learning in Data Analytics

Join us at PASS BA Day on June 21, 2017, for a day of focused learning from speakers who have expert knowledge of the Microsoft BI tools and technologies. Discover real world analytic skills and practices you can put to work immediately. Select from the Advanced Analytics or Data Visualization focused tracks for a deep dive into the topic.

Advanced Analytics
Data Science with Excel, Open Source R, and Python for Data Analysts

Jen Underwood, Founder, Impact Analytix

Quantifying business situations for forecasting and analytical modeling is an art and a science. This fast-paced course is designed for intermediate level data analysts. Hands-on labs will allow students to apply learned concepts to solve problems with popular open source R, Python, Weka, and Excel. After a quick introduction of data science foundation topics, we will work through a variety of descriptive, diagnostic, predictive, and prescriptive problem solving techniques across the entire advanced analytics lifecycle.

Participants will gain an understanding of when to choose specific analytic techniques, algorithms, and tools to solve common business problems. We will also dive into the critical importance of data preparation and sampling. After learning how to effectively develop models, we will cover evaluating models and embedding intelligent analytics into smart reports, dashboards, and applications to deliver actionable insight.


1. Introduction to Data Science

a.          Areas of Data Science

b.          Current Industry Trends

c.          Types of Analytics Models

d.          Solving Common Problems

e.          CRISP-DM Lifecycle

f.           Framing Questions and Problems


2. Descriptive and Diagnostic Analytics

a.          Basic Statistics

b.         Analysis Toolpak

c.          Introduction to R and Python


3. Data Collection and Preparation

a.          Common Tools and Techniques

b.          Cleansing and Shaping with Excel

c.          Analytical Data Transformation

d.          Sampling Methods


4. Predictive Analytics Development

a.          Overview of Data Mining and Machine Learning

b.          Building and Evaluating Predictive Models

c.          Introduction to Open Source Predictive Tools

d.          How to Choose a Predictive Algorithm


5. Prescriptive Analytics

a.          What-If, Scenarios, and Solver

b.          Forecasting and Regression

c.          Optimization and Simulation


Session Goals
By the end of this one-day session, attendees with gain:

    Data Science Techniques and Tools
    Descriptive and Diagnostic Analytics Fundamentals
    Predictive Analytics and Machine Learning
    Business Modeling for Prescriptive Analytics
    Embedding Analytics into the Business

Level of Expertise

Session Prerequisites

This fast-paced course is designed for intermediate level data analysts, advanced Excel users, and professional business intelligence developers who are comfortable with scripting and learning analytics programming languages. Statistics and data science background and experience are not needed.  

Session Requirements

Students will need a laptop with the following software installed:

Open source Weka

Frontline Systems Analytic Solver Basic V2017
(Important note: Since this software has a free 15-day trial, please download and install no earlier than June 14, 2017, to ensure that it is working properly and is still active for this session.)


Preferred Analytics Scripting Tools:

R fans: Open source R and free R Studio OR Microsoft R Open




Python fans:

Open Source Anaconda Python and Jupyter Notebooks

 Data Visualization
Beyond the Basics - Advanced Power BI for the Business Analyst

Patrick LeBlanc, Data Platform Solutions Architect, Microsoft

Are you a business/data analyst who would like to go from good to great? Let's dive deeper into Power BI to take full advantage of several key features and options to make your analysis and reporting better. From creating reports to deployment and maintaining fresh data, writing complex DAX expressions, and leveraging custom visuals, you’ll leave the basics behind and enter the realm of the power user. We will keep the focus of this session to the non-technical business users, so that you can take and apply what you learnt from this session directly into your workplace.


  • DAX Functions
  • Data Refresh
  • Data Modeling
  • Data Security
  • M language - to manipulate data with finer control
  • Reporting
  • Data Visualization

Session Goals

  • Learn and understand DAX: Data Analysis Expressions
  • Understand the importance of data refresh – from cloud, company (on-premise) and using Gateways
  • How to model your data relationships effectively
  • Understand M syntax within Power BI
  • Embedding Power BI in SharePoint and on the Web
  • Leverage custom visuals
  • Learn some of my favorite Power BI tips and tricks

Level of Expertise


Session Prerequisites

Familiar and have used Power BI Desktop in the past

Session Requirements

Following prerequisites and setup must be completed for successful completion of the exercise:

  • At minimum, a computer with 2-cores and 4GB RAM running one of the following versions of Windows: Windows 10, Windows 7, Windows 8, (64-bit preferred), Windows 8.1, Windows Server 2008 R2, Windows Server 2012, Windows Server 2012 R2
  • Microsoft Power BI Desktop requires Internet Explorer 9 or greater
  • Verify if you have 32-bit or 64-bit operating system to decide if you need to install the 32-bit or 64-bit applications
    • Search for computer on your PC, right click properties for your computer
    • You will be able to identify if your operating system is 64 or 32 bit based on “system type” as shown below
  • Download and install Power BI Desktop: Download and install Microsoft Power BI Desktop from
  • Please choose appropriate 64-bit or 32-bit version depending on your platform. Microsoft Power BI Desktop is available for 32-bit (x86) and 64-bit (x64) platforms
  • Download and install the Microsoft Power BI Mobile app on your mobile device. App is available on Apple Store, Android Play Store, and Windows Store

Ready to dive into the world of analytics?

Register Today