Personal BI to Personal Data Science

Mulkens Jan Hermans KimberlyMicrosoft BI Consultant Data scientist

Twitter: @JanMulkensBlog: www.janmulkens.be

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Jan MulkensMicrosoft BI Consultant

Ordina Belgium

“I love the Power BI experience from desktop to mobile.Put on top of that the community and the continuous stream of high value releases and it’s clear why Power BI is the future.”

Kimberly Hermans

My favourite thing about Power BI is its ease to work with. Within hours I know what my data looks like, what story it tells and how I should start my

modelling phase.

Data Scientist & CRM consultant Ordina Belgium

Agenda• Introduction• Corporate BI & DS

• Goals • Solution

• Personal BI & DS • Goals • Solution

• Applying Power BI

“With Power BI, it’s simple. Everything becomes possible.”Philip Dean, Tees and Hartlepool National Health Services Trust

Introduction

Power BI can not only be used to democratize BI across

the enterprise, but also to democratize Data Science

across the enterprise.

2012 - Value vs difficulty

Action Decision

Interactive dashboardsWhy did it happen?

PredictionsWhat will happen?

RecommendationsWhat should I do?

Decision automation

Decision support

Data

Static reportsWhat happened? Manual process

ValueSource: Gartner (October 2014)http://www.gartner.com/newsroom/id/2881218

2014 - Data to action

Data Science

Traditional BI

End User

Everyone

The age ofClassic BI

End UserIT Analyst

The age ofSelf Service BI

The age ofData Culture

Data Culture

Corporate BI & DS

Corporate goals

Corporate goals

Corporate Solution

Solution created by IT.Established corporate context & is reusable, scalable and backed up.

Corporate Business Intelligence

... ?

Corporate Data Science

... ?

Corporate Data Science

Traditionalresearch

Dangerzone

MachineLearning

DATASCIENCE

Hacking

skills

Math

& st

at

know

ledg

e

Domainexpertise

Corporate Data Science

Up to15hrs / week

Up to15hrs / week

Up to15hrs / week

Data

Cleaning

Exploratory

Data Analysis

Full work week

Machine

Learning

ETL Up to 4 hrs / week

Source: Generalized from O’Reilly’s “2015 Data Science Salary Survey” (sep 2015)

ETL Data Cleaning Machine LearningExploratory Data Analysis

Personal BI & DS

Personal GoalsRemove frictions between users and data

• Business-driven vs IT-driven

• Rapid delivery

• “Less” governance

• Freedom vs Standardized

Personal Solution

BI solution created by a user.Context is only for user & exists as a document

Personal Business Intelligence

Personal Data Science

Applying Power BI

Personal Data Science1) Problem statement

Demand forecasting• Public biking system Washinton

• +/- 350 stations

• Peaks in demand & supply

• Goal of project: optimize planning of relocating bikes

Personal Data Science

2) Get Data1) Problem statement

Personal Data Science

2) Get Data3) Enforce Data Quality

1) Problem statement

Personal Data Science

2) Get Data

4) Exploratory Data Analysis3) Enforce Data Quality

1) Problem statement

Personal Data Science

2) Get Data

5) Feature engineering4) Exploratory Data Analysis3) Enforce Data Quality

1) Problem statement

?

Personal Data Science

2) Get Data

5) Feature engineering4) Exploratory Data Analysis3) Enforce Data Quality

1) Problem statement

6) Form hypotheses

Patterns per station

Pattern similarity between stations

Pattern similarity between stations

Personal Data Science

2) Get Data

5) Feature engineering4) Exploratory Data Analysis3) Enforce Data Quality

1) Problem statement

6) Form hypotheses7) Machine Learning

Takeaway

1) BI vs DS2) Personal BI & DS3) Power BI!

http://community.powerbi.com

https://support.powerbi.com

https://www.youtube.com/user/mspowerbi

Resources

https://app.powerbi.com/visuals

Gallery• Made for the Community

by the Community• Use in Power BI

Desktop or online at Power BI.com

• Create new custom visual with Developer Tools

Gallery

Questions?

Thank You!