PASS BA Visual Data Storytelling precon session with Mico Yuk

CEO of BI Brainz | Author | Global Keynote Speaker | BI Influencer | Trainer | Blogger| BI Executive Advisor *@micoyuk*

I am super excited that Mico Yuk is joining us again at PASS BA Conference!

aaeaaqaaaaaaaasjaaaajdfkmzdiywy2lwizmtktnduxyy05zmfilwy1owyzodgyyjzmzaMico Yuk is well known in the Business Intelligence ecosystem as a community leader, BI influencer, controversial blogger, and the founder of the highly rated BI Coaching Series,
the BI Dashboard Formula (aka BIDF). Headquartered in Atlanta, GA, her team of senior coaches and consultants work with Executives to transform their BI teams to meet the challenges in the new era of BI through a series of coaching, training, and consulting services.Mico’s most recent accomplishments include being named one of the Top 50 Analytics Bloggers by SAP and being rated a #1 global keynote speaker at a number of global BI conferences.

A computer engineer by degree, she has been designing and implementing enterprise dashboards for major corporate clients since 2006 and is considered to be one of the top data visualization experts in the world.

First as a consultant and now through her company, she has helped to implement executive dashboard and reporting using the SAP BusinessObjects platform for customers such as Allstate, Pfizer, Aviva Canada, McKesson, Ryder Logistics, Digicel Jamaica, QatarGas, St. Jude Medical, Walgreens, Chiquita, LG, the US Airforce, Medtronics, SAP Global Marketing, Amtrak, Fresh Direct, Bank of America, and Nestle, to name a few.

To find out more about Mico, please visit http://micoyuk.com.

Visual Storytelling – How to Tell a “Compelling” Data Story That Matters to Your Users

This business-oriented, hands-on session will provide the foundation necessary to make your data visualizations more intelligent, actionable, and useful! Whether you are a beginner or a data visualization veteran, this session will guide you on telling more compelling stories with your data, from storyboarding fundamentals to more advanced techniques such as how to add smart context and visual cues. Attendees will learn:

• how to create a simple four-part visual storyboard on paper in minutes, not weeks
why visual storytelling is more effective than traditional reporting
• the one element 98% of data visualizations are missing and how it is negatively affecting user adoption

Format: Half-Day Classroom (Afternoon)

Register here

 

PASS BA Header Mico

 

My Kibana presentation slide deck from SQLBits

Here are the slides from my first SQLBits XIV session at the Excel in London, March 2015.

I presented with Allan Mitchell on the topic of ElasticSearch and Kibana. I did the Kibana section and talked around the topic of data visualisation, and the slides are here. I whizzed through these first, before giving a demo. I’ll post up the SQLBits video as soon as I have it.

Visualising Data with R: HTMLWidgets for R

I’m interested in analyzing and visualizing data with R, as you know. Thanks to Jen Underwood, she pointed me at this cool series of widgets, called HTMLWidgets, that allows you to do some interesting visualisations with R. I must admit I haven’t touched JavaScript for years, ever since I helped to build websites for well known entertainment sites, but I’m glad I can pick it up again. What does it let you do?

  • Use JavaScript visualization libraries at the R console, just like plots
  • Embed widgets in R Markdown documents and Shiny web applications
  • Develop new widgets using a framework that seamlessly bridges R and JavaScript

Why don’t you head on over to the site and have a look? I’ll be playing with it, and finally finishing my R blog series, as soon as I can. I’ve been busy helping to organize the PASS BA Conference, which is taking place in April 2015 in Santa Clara. Therefore, I hope you’ll excuse the radio silence. It’s on my to-do list, which never goes down, ever!

Day 6: The Data Analysts Toolkit: Why are Excel and R useful together, and how do we connect them?



https://www.flickr.com/photos/38953955@N07/14764024879/player/
Why is analytics interesting? Well, companies are starting to view it as profitable. For example, McKinsey showed analytics was worth 100Bn today, and estimated to be over 320Bn by 2020.
When I speak to customers, this is the ‘end goal’ – they want to use their data in order to analyse and predict what their customers are saying to them. However, it seems that folks can be a bit vague on what predictive modelling actually is.



I think that this is why Power BI and Excel are a good mix together. It makes concepts like Predictive Modelling accessible, after a bit of a learning curve. Excel is accessible and user-friendly, and we can enhance our stats delivery using R as well as Excel.

One area of interest is Predictive Modelling. This is the process of using a statistical or model to predict the value of a target variable. What does this actually mean?  Predictive modelling is where we work to the predict values in new data, rather than trying to explain an existing data set. To do this, we work with variables. By their nature, these vary; if they didn’t, they would be called a constant.

One pioneer was Francis Galton, who was a bit of an Indiana Jones in his day.  Although he wrote in the 19th century, his work is considered good and clear enough to read today. Therefore, this research has a long lineage, although it seems to be a new thing. We will start with the simplest: linear regression.

Linear regression compares two variables x and y to answer the question, “How does y change with x?” For predictive modelling, we start out with what are known as ‘predictor variables’; in terms of this question, this would be x. The result is called the target variable. In this question, this would be y. Why would we do this?

  • Machine Learning
  • Statistics
  • Programming with Software
  • Programming with Data 
  • Fun!

Why would businesses work with it at all?

  • to discover new knowledge and patterns in the data
  • to improve business results 
  • to deliver better customised services

If we have only one predictor variable and the response and the predictor variable have a linear relationship, the data can be analyzed with a simple linear model. When there is more than one predictor variable, we would use multiple regression. In this case, our question would be: , “How does y change with multiple x?” 

In fitting statistical models in which some variables are used to predict others, we want to find is that the x and y variables do not vary independently of each other, but that they tend to vary together. We hope to find that y is varying as a straight-line function of x.

If we were to visualise the data, we would hope to find a pleasing line chart which shows y and x  relating to each other in a straight line, with a minimal amount of ‘noise’ in the chart. Visualising the data means that the relationship is very clear; analysing the data means that the data itself is robust and it has been checked.

I think that’s why, in practice, Power BI, Excel and R work well together. R has got some great visualisations, but people are very comfortable with Excel for visualisations. All that loading packages stuff you have to do in R… it doesn’t work for everyone. So we use R and Excel, at a high level, as follows:

https://www.flickr.com/photos/38953955@N07/14764024879/player/

  • We cleanse and prepare data with Excel or Power Query
  • We use RODBC to load data into R
  • We analyse and verify the data in R
  • We build models in R
  • We load the data back into Excel using RODBC
  • We visualise the data for results


Excel is, after all, one of the world’s most successful software applications ever, with reputedly over one billion users. Using them both together means that you get the best of both words: R for analysis and model building: Excel is the ‘default’ for munging data around, and visualising it. I’m sure that one of the most popular buttons on software such as Tableau, QlikView et al is the ‘Export to Excel’ or ‘Export to CSV’ functionality. I’d be interested to know in what people think about that!

Building linear regression models in R is very simple; in our next session, we will look at how to do that, and then how to visualise it in Excel. Doing all this is easier than you think, and I will show you how.

David McCandless announced as PASS BAC keynote speaker

The Professional Association of SQL Server announced this morning that acclaimed data visualization expert, TedTalk speaker, and Information Is Beautiful author David McCandless will keynote at the 2nd annual PASS Business Analytics Conference in San Jose, CA, May 7-9.

 
David will take the stage on Day 2 for a journey through the world of visualizing facts, data, ideas, and statistics. Microsoft’s Kamal Hathi and Amir Netz will kick off the conference on Day 1 with insights into how Microsoft is making data more accessible through easy-to-use tools including Power BI. Exciting times, people!
 
The PASS BA Conference – featuring 65+ sessions across five topic tracks – brings together business analysts, data scientists, and BI and IT professionals to connect with each other, share experiences, and learn more about the power of data to transform business. You can find all the details at http://passbaconference.com. On a minor note, I’m speaking too during a general session (not the keynote, obviously!) and I hope to see you there!
 
I am REALLY looking forward to David McCandless speak, and it would be wonderful to meet him in person. I hope you can make it to PASS BAC. If you are looking for a discount code, here is mine for you to use to get $150 off: BASF2O
 

How do you choose the right data visualisation in Power BI to show your data?

How do you choose the right visualisation to show your data? Usually the customer wants one thing, the business user want something else, the business sponsor wants something flashy…. and it’s hard to tease out the requirements, and that’s before you’ve even opened up Power BI such as Power View, Excel, Tableau or whatever your preferred data visualisation software.

In other words, there are simply too many charts to choose from, and too many requirements to meet. Where do you start?

I found this fantastic diagram which can help you to choose the right visualisation. I’m often surprised to see that people haven’t seen this before. Note: this diagram was done by Andrew Abela of Extreme Presentation and the source is here and his email address is on the slide, so be sure to thank him if you’ve found it useful. If you can’t see it very well, click here to go to the source.

choosing-a-good-chart-09_001

Chart Choosers should not replace common sense, however, and Naomi Robbins has written a nice piece here which is aimed at the wary. However, diagrams like Abela’s can really help a novice to get started, and for that, I’d like to thank him for his work.

How does it related to Microsoft’s Power BI? If you look at the visualisations that are available in Power View, you can see that most of the visualisations in the diagram are available in Power BI.  The ones that are excluded are the 3D graphs, circular area charts, variable width charts, or the waterfall chart.

Why no 3D? I personally hope that Microsoft will leave 3D out of Power BI tools, unless of course it is in Power Map.  With 3D on a chart, it is harder to identify the endpoints, and it can take us longer. It might also mean that points are occluded. If you’re interested and want to see examples, here is one by the Consultant Journal team or you can go ahead and read Stephen Few’s work. If you haven’t read anything by Stephen Few, get yourself over to his site right now. You won’t regret it. Why is it different from Power Map? 3D maps provide context, and they are the exception where I will use 3D for a data visualisation showing business data. I’m obviously excluding other types of non-business data here, such as medical imaging and so on.

Why no circular area or variable width charts? I am not a fan of variable width of circular area because we aren’t very good at evaluating area when we look at charts and graphs, and Robert Kosara has an old-but-good post on this topic here.

This blog is mainly for me to remember stuff but I hope it helps someone out there too.

Best Wishes,
Jen