2020 Prospectus - StoryIQ...Our Lead Data Storytelling Trainer and a TEDx speaker, Dom brings a wealth of data storytelling experience to StoryIQ from his career at QBE, one of Australia’s

storyiq.com.ph

2020 Prospectus

CONTENTSABOUT

COURSES

DATA STORYTELLING FOR BUSINESS

DATA TO INSIGHTS

EXCEL ANALYTICS NINJA

ADVANCED VISUALIZATION & DASHBOARD DESIGN

DATA WRANGLING

Our Mission

Course Overview

Course Overview

Course Overview

Course Overview

Course Overview

Course Summary

Course Outline - Day 1










Delivery OptionsOnline Delivery

4

12

8

15

19

22

4

13

9

16

20

23

55

14

11

18

21

25

TRUSTED BYINDUSTRY

Data analytics and visualization is revolutionizing business across all industry verticals.

Since 2015, we’ve trained over 300 companies, government departments and NGOs in fundamental data science skills. From banking to telcos and retail to real estate: we’ve trained people in your field.

Our Mission

Course Summary

Delivery options at no extra cost:

Our mission is to prepare people to solve real business problems. Our courses put concepts first, and treat tools and technology as an enabler, not the core focus. We take the key concepts and best practices of analytics, visualization and design thinking based on the latest academic research, and present them in a clear, concise and actionable format.

We bring the concepts to life with realistic, business relevant examples based on our consulting experience. All our courses are hands on, and get participants applying the concepts to real problems right away. We ensure that all participants walk away at the end of each course with new outputs they have created themselves, which they can apply to real business problems the next day.

Our instructors will help your team makeover their existing reports and dashboards on the fly so that you can walk away with improved outputs that you can use with your teams immediately.

All our courses can be delivered by Webex virtual classroom, enabling you to roll the course out to staff in disparate locations with a full interactive experience.

Our 2-day courses can be summarized to 1-day to be even more targeted at learning concepts, with no need to open tools like Excel or Tableau at all. This option is designed for busy, senior staff who will not be implementing the best practices themselves, but rather need to learn the concepts so that they can direct more junior staff to implement. We replace the hands-on workshops in tools like Excel and Tableau with wire framing using old fashioned paper and post-it notes.

Ideal for onboarding new hires. We can deliver modules you select from any of our courses in a tailored program.

Course

Workshops using your own reports and data

Remote delivery

Executive courses

Analytics training bootcamp

Data to InsightsData Storytelling for BusinessExcel Analytics NinjaAdvanced Visualization& Dashboard DesignData Wrangling

2 - Day2 - Day2 - Day2 - Day

2 - Day

DataData, LeadershipData, DigitalData

Data, Leadership

Excel, PowerPointExcel, PowerPointExcelTableau or PowerBI

Excel, Azure (optional)

Full Length Learning Pillars Tools Used

4

Customized Industry-Based Data Sets and Examples

Online Delivery

We can work with you to tailor the content for your organization, and to use your real business data in our examples. Of course, we are happy to sign a non-disclosure agreement and maintain absolute confidentiality.

Our team of analysts and consultants can provide a thorough make over your existing reports and dashboards in advance of the course, applying industry best practices. Our instructor will then walk your teams through the reasoning behind the changes, and how to implement similar improvements in the future.

A fully online version of our most popular course. It will include detailed instructional videos, and online knowledge check tests. This can also be integrated with face to face delivery or Webex to include a workshop with an instructor to consolidate the concepts.

Customized industry-based data sets and examples

In depth reporting and dashboard makeovers

Data Storytelling For Business Online (Q2 2020)

5

OUR FACULTYLearn from the thought leaders in the field

A data storytelling expert, Jay is concurrently a trainer at StoryIQ and Head of Operations at Magpie.IM, an online payments startup.

In his prior role, Jay was the Head of the Manila Shared Services Center for Kforce (Nasdaq: KFRC) and a Business Development Director at analytics company, Sencor. Jay holds an MBA and B.S. in Mathematics from Ateneo de Manila University. He was a winner of the 2017 Grab Data Visualization challenge.

JP has varied experience in different industries, building an analytics career with strong roots in customer service, manufacturing, retail, digital marketing, and market research.

His longest and most recent engagement was with ABS-CBN, the Philippines’ biggest media network, where he led digital analytics to drive key businesses including the company’s video streaming services for both local and international markets and other owned digital properties.

A distinguished chemist, Kenon worked in the analytical laboratories of multinational corporations such as Dole and Coca-Cola. He won the 2019 Data Visualizationchallenge held by Data Science Philippines before committing fully to a career in Data. His aptitude for the arts and sciences, as well as his experience in technical data collection, analysis, and communication, have been key to his success as a data storyteller.

Denise has had decade-long work experience in the clinical and pharmaceutical research space where she gained knowledge and expertise in various business areas including workforce, total quality management, and learning & development. Prior to joining StoryIQ, she led a data management team for a national disease and therapy index in IQVIA, a human data science company. On top of this, she also delivered trainings to colleagues and managers on Microsoft Excel analytics, businesscommunication, and data storytelling.

Jay Manahan

JP Domingo

Kenon Vinson

Denise Tan

6

Our Lead Data Storytelling Trainer and a TEDx speaker, Dom brings a wealth ofdata storytelling experience to StoryIQ from his career at QBE, one of Australia’slargest insurance companies. At QBE, he was a senior leader in analytics,procurement, and business improvement.

He has been responsible for negotiating multi-million dollar contracts withsuppliers, presenting data driven strategy recommendations to the company’ssenior executives, and producing reporting for the Group Board of Directors.

Isaac Reyes, Co-Founder at StoryIQ, is a TEDx speaker and international keynotepresenter in data science and machine learning. He was the keynote speaker atthe 2019 Open Data Science Conference in Brazil and over 2018-2019, hisspeaking tour visited 26 cities across 5 continents. His ultimate goal is toempower every organization to derive value from data.

Gerald has over 10 years of experience in the field of corporate education.Combining his extensive experience in corporate training and organizationaldevelopment, he has been involved in developing tools and training solutions for a variety of audiences in both big and small organizations as a former CourseAdministrator and Developer at Avaloq, a Fintech leader in digital banking and digital wealth management in Switzerland.

Graduated from the Ateneo de Manila University with a bachelor’s degree and amasters in applied mathematics, Zac is the Gen Z analyst who is in the road tobecoming a data scientist of the millennium. He was a business statistics andprogramming lecturer of the Ateneo, mentoring students from the John Gokongwei School of Management. In 2016, he was also a Temasek Foundation International Leadership Enrichment and Regional Networking Scholar of the National University of Singapore, having completed real analysis and mathematical statistics courses there.

Dominic Bohan

Isaac Reyes

Gerald Valentin

Zachary Bisenio

7

data to insightscourse 1

Course duration:Laptop Specs:

Required Software:

2 DaysMinimum required specs of Intel i3 processor, 4GB RAM.Either Mac or Windows operating system

Any data visualization software package (e.g.Excel, Tableau, PowerBI, Qlik) Powerpoint

Learning Objectives

- Determine great business questions that can be answered with data

- Clean and prepare your data for analysis

- Learn the fundamentals of descriptive analytics

- Communicate your outputs effectively through data storytelling

Suitable forAny professional who works with data.

8

• Existing data sources – external vs internal• Generating new data• Data types• Data linkage, data dimensionality, data aggregation, data transformation, data reduction, data aggregation, metadata• Data cleaning and wrangling• All data is biased• Data doesn’t equal insights

III. Collect Data – Gather and Prepare Data to Answer the Question

COURSE OUTLINE - DAY 1

I. How Data Drives Value

II. Hypothesize – Determine a Good Business Question

• Data has been around forever – why is it so important now? •• The perfect storm – lower storage costs, higher computing power •• The 4 V’s of big data• What is data analytics? What is data science? What is machine learning?• The ‘analytics value chain’• What does a data analyst do? What does a data scientist do? What does an analytics team look like? What does a data science team look like?• What is a data evangelist? How do they interact with analytics teams, data science teams and the business?• Why do 60% of big data projects fail?• Introduction to the scientific method• Introduction to the data analytics process •• Hypothesize •• Collect data •• Analyze the data •• Report on the results and take action

• Is the question answerable?• Is answering the question feasible? Is it feasible right now?• Does the answer to the question drive business value?• Is the answer to the question actionable?• Ranking project opportunities• Getting to an answer •• Descriptive analytics and basic data visualization •• Hypothesis testing •• Machine learning and optimization methods •• vWhen to put the brakes on the data science team

DATA TO INSIGHTS

9

• Exploratory data analysis for business• Exploratory metrics •• Measures of the middle (average, median, mode) •• Measures of spread (standard deviation, range) •• Business metrics ••• Metrics based on $ amounts, metrics based on totals, metrics based on counts, metrics based on percentages ••• Ranking metric importance for reporting and data storytelling ••• Tracking metrics (The 4 T’s) ••• Today, Target, Trend, Tomorrow ••• Combining metrics (case study: CommetComm churn) ••• Metrics - caveats ••• Anscombe’s quartet and the ‘datasaurus’ ••• Comparing apples with apples ••• Going beyond the dataset• Using Excel Pivot Tables to analyze data (demo) •• Calculating totals, counts, percentages and averages •• Grouping data in pivot tables •• Creating a customer spend distribution using pivot tables and a histogram •• Why Excel is so loved and yet so hated and when to use it

IV. Analyze the Data - Exploratory Data Analysis – Exploratory Metrics

Workshop 1In this workshop, participants will perform hands on exploratory data analysis (focusing on metric selection) on an invoice dataset using Excel and pivot tables

V. Analyze the Data - Exploratory Data Analysis – Exploratory Visualization

• Exploratory visualization •• Exploring vs explaining: two types of data visualization •• Visuals for informing pre-existing hypotheses •• Visuals for enabling the generation of new hypotheses •• Caveats ••• Correlation isn’t causation ••• Data aggregation ••• Missing data ••• Time cuts• Performing exploratory visualization in practice (demo in Excel) •• A framework for exploratory chart selection• Tools for fast tracking the EDA process (including Python or R EDA demo)

Workshop 2In this workshop, participants will perform hands on exploratory data analysis, focusingon exploratory visualization on an invoice dataset using Excel and pivot tables.


DATA TO INSIGHTS

10

• The Analytics Value Chain •• Descriptive Analytics •• Predictive Analytics •• Machine Learning• Introduction to Machine Learning •• Supervised Learning •• Unsupervised Learning• Training and test datasets• Building a supervised machine learning model in Excel• Building a supervised machine learning model in the cloud (Azure ML Studio)• Productionizing machine learning models• Auto ML overview (featuring DataRobot)

• Presentation medium selection framework• Storyboarding• Data storytelling •• The Four Keys to Data Storytelling •• The Audience •• The Data •• The Visuals ••• Tables ••• Charts ••• Impact Metrics •• The Narrative

• Being an analytics champion and evangelist• Arm yourself with domain relevant case studies• Next steps for continued learning


I. Analyze the Data – Explanatory Data Analysis

II. Report on the Results and Take Action

III. Go Forth and Evangelize, Course Wrap Up

Workshop 3In this workshop, participants will take the results from yesterday’s analysis and usedata storytelling skills to weave their results into a story that compels stakeholders totake action. The participants will present this data story at the conclusion of theworkshop.

DATA TO INSIGHTS

11

DATA STORYTELLINGFOR BUSINESSCourse duration:Laptop Specs:

Required Software:

2 Days

Minimum required specs of Intel i3 processor, 4GB RAM.Either Mac or Windows operating system

Any data visualization software package (e.g.Excel, Tableau, PowerBI, Qlik, R, Python) and Powerpoint.

Predicted to be the top business skill of the next 5 years.

Suitable for

Well told data stories are change drivers within the modern organisation. But how do we find the most important insights in our business data and communicate them in a compelling way? How do we connect the data that we have to the key underlying business issue?

This course takes students from the fundamentals (what should we be measuring and why?) through to the elements of good visualisation design (what does a good chart look like?) through to proficiency in datastorytelling.

By the end of the course, participants will know how to produce engaging, cohesive and memorable data stories using Excel and PowerPoint. The course also teaches attendees the importance of producing statistically robustvisualisations and insights.

This is our most popular course. It’s suited towards any professional who works with data and charts. If you need to tell better stories with your data, then this course is for you.

course 2

12


I.

II.

III.

IV.

V.

VI.

Introductions, Ice Breaker

Audience

Visuals

Viz Arsenal

Interactive workshop task

Workshop presentations and judging

• Making your audience the ‘hero’ of your data story• Chart Junk• Data Ink Ratio• Pre-attentive attributes• The Cleveland McGill Scale• Gestalt Principles of Visual Perception

• Charts v Tables v Impact Metrics• Visualization Selection Framework• Graphic Design Principles for Impact Metrics• Table Design Best Practice

• Bar chart best practices• Pie Chart Best Practices• Line Chart Best Practices• Slopegraphs and Staged Line Charts• Enclosures• Scatterplots

• Instructor will rotate around groups and provide personalized assistance


13


I.

II.

III.

IV.

V.

Color in Data Storytelling

Data

Narrative

Interactive workshop task

Workshop presentations and judging

• Instructor will rotate around to groups and provide personalized assitance

• Color Psychology• The Munsell Color system• Sequential, Diverging and Categorical Palettes• Contrast ratio• Color Blindness

• Cleaning and preparing your data• Metric selection • Missing Values and Outliers• Introduction to pivot tables

• Presentation Medium Selection Framework• Storyboarding• Deck Transformation


14

Excel analyTicsninjaCourse duration:Laptop Specs:Required Software:

2 DaysIntel i3 processor, 4GB RAM. Either Mac or Windows OS.Excel and Powerpoint 2013 or later.

Learn the fundamentals of business analytics in this two day intensive program.

Suitable for

Some executives mistakenly believe that the majority of value in business datasets is only unlocked by applying advanced statistical and machine learning techniques. In practice, most of the value in business data is derived by asking relatively simple questions that can be answered using basic data manipulation and common metrics (e.g. averages, totals, counts and percentages).

That said, the ability to ask the right business questions and answer them with the right metrics is a fundamental anlytics skill that is sorely lacking in the skillset of most data analysts and managers. Why? University statistics and math programs don’t prepare graduates for the challenges and pace of the business setting.

In this Excel based course, participants will learn how to progress through the full data driven decisionmaking process, from identifying the business question through to hypothesis development, data manipula-tion and presenting of results.

This is our second most popular course. It’s suited to any professional who needs to make decisions using business data.

course 3

15

I.

II.

III.

IV.

What is the end goal of this course?

Keys to Effective Analytics: Exploratory Data Analysis (EDA)

Context and Variables: Understanding the Data

Wrangling: Using Formulae, Filtering, and Sorting to Manipulate Data

• What is EDA?• Context: understanding the data and its source• Variables: knowing and classifying data into various data types• Wrangling: performing basic data munging to address missing values, outliers, input errors• Analysis: discovering univariate and bivariate relationships in the data

• Questions to ask of your dataset• What are the different types of data?• Fancy statistics terms vs. their common business meanings• Classifying the variables of the course dataset• Numeric variables: continuous and discrete •• Date variables• Categorical variables •• Categorical variables that appear numeric and vice-versa •• Continuous variables that appear discreet and vice-versa• Dummified data: what they look like and why they exist• Formatting data according to their variable types

• Querying your data• Sorting data according to various dimensions and multiple levels• Identifying and extracting metrics needed to generate or prove certain insights• Manipulating text or string data• Working with dates• Wrangling data through arrays• Optional wrangling: •• Performing a sanity check on the data •• Addressing missing values, outliers, and input errors •• List-wise deletion and case-wise deletion



16

(10:30am - 12:00nn)

(1:00pm - 4:00pm)

(4:00pm - 4:15pm)

(4:15pm – 5:00pm)

V.

VI.

VII.

VIII.

Univariate and Multivirate Analysis: Leveraging Excel Features for Analyzing Data

Workshop

Group Work Submission Deadline

Group Presentations, Feedback and Wrap

• Querying your data to make relevant analysis •• e.g. top x%, above/below average, between x and y, contains x• Choosing the right metrics, according to the insight to be supported •• Apples-to-apples metrics: proportions or averages •• Absolute size metrics: counts or totals• Calculating percentages and understanding their meanings •• rates, % breakdowns or % contributions, growth rates• Summarizing your data into logical groupings• Other ways to summarize your data •• Increases/decreases •• Running totals •• Rankings



17


Day 1 Recap

Using Elegant Data Visualization for Reporting

Workshop



• Lessons from Day 1 workshop• Apples-to-apples metrics, absolute size metrics, trends• Using data visualization for analysis •• Multi-metric relationships via data bars •• Multi-metric relationships via scatterplots, bubble charts •• Trends via sparklines •• Spotting patterns using color scales

• When to use and how to create non-standard data visualizations• Reference lines to support your insight• Funnel Charts to show sequential steps and subsets• Tornado / Divergent Bar / Bi-Directional Bar Charts to show comparisons• Optional charts for advanced audiences •• Burndown Charts to show usage of depleting resources •• Bullet graphs to show targets vs. actuals

I.

II.

III.

IV.

V.


18

Advanced ViZ& dashboard designCourse duration:Laptop Specs:

Required Software:

2 Days

Windows 7/8/10 or MacOS El Capitan/Sierra.At least 4GB RAM.Minimum 2GB free disk space.

Microsoft Excel 2013 or later.Tableau Public or Power BI

Take your visualization and dashboardskills to the next level

Suitable for

Advanced Visualization and Dashboard Design is aimed at the professional who already possesses funda-mental data visualization and data storytelling skills. A natural continuation point from our Data Storytelling for Business and Excel Analytics Ninja courses, this course provides participants with the skills needed to produce stunning, understandable business dashboards and graphs.

Taught using a variety of visualization tools including PowerBI and Tableau, the course covers the keys to designing for interactivity and drill down effects. The course also covers less commonly used but valuable visualization methods, including methods for visualizing networks and flows. Dashboard design is covered in detail, with participants creating a dashboard ‘makeover’ during the class practical workshop.

This course is suitable for any professional who wants to analyze and extract value from business data using sophisticated data visualization and interactive dashboards that convey insights with clarity.

course 4

19


Introductions

Workshop



Grammar of Graphics

Visualizing Comparisons

Visualizing Comparisons (cont’d)

Visualizing Parts

Visualizing Trends

• Think like a graph• Look at bars, lines, and scatter plots from new perspective• Learn the intuition of visualization software

• Expand your visual vocabulary beyond bar charts• Compare more than one metric simultaneously •• Trellis displays / small multiples •• Scatterplots •• Bubble charts

• Expand your visual vocabulary beyond bar charts• Compare more than one metric simultaneously •• Trellis displays / small multiples •• Scatterplots •• Bubble charts

• Treemaps

• Calendar heatmap• Optional: seasonality plot

I.

VII.

VIII.

IX.

II.

III.

IV.

V.

VI.

ADVANCED VIZ & DASHBOARD DESIGN

20

Workshop


Group Presentations, Feedback and Wrap Up

• Examples of Good vs. Bad Dashboards• Keys to Effective Dashboards: UX & Interactivity, Metrics, Visuals & Design

• Overview of Interactivity: tooltips, sorting, filtering, highlights, zoom, force• Hands-On: building interactivity in Tableau and Power BI• Tooltips and Visual Tooltips

• Sorting• Filtering• Highlights• Overriding default filtering and highlight actions

• Layout and positioning• Focusing attention in dashboards •• Size •• Color •• Big numbers •• Human forms• The Bullet Graph

• What is a good metric? •• Action & Accountability •• Context: via goals, via time period comparisons, via relatable units •• Comprehensibility

VII.

VIII.


Intro: What is a Dashboard?

User Experience and Interactivity

User Experience and Interactivity (cont’d)

Visuals and Design

Metrics

I.

II.

III.

IV.

VI.

V.

ADVANCED VIZ & DASHBOARD DESIGN

21

Data wranglingCourse duration:Laptop Specs:

Required Software:

2 Days

Windows 7/8/10 or MacOS El Capitan/Sierra.At least 4GB RAM.Minimum 2GB free disk space.

Microsoft Excel 2013 or later with Power Query and Power Pivot.Power BI Desktop or Tableau.

Real data is messy.

Suitable for

Learn how to create order from chaos, and to clean, prepare and structure your data so that your team can unlock its full potential. Using little-known but powerful tools such as Power Query and Power Pivot, as well as Tableau or Power BI, this course teaches participants how to prepare data for reporting, as well as munge data for more advanced analysis and for an efficient and more responsive dashboard. You will learn concepts such as data modeling, normalization, unions, joins, schema relationships, data blending, and data hierarchies.

Analysts and business professionals who work closely with complex data sets.

course 5

22

• What are the differences among Data Wrangling, ETL, and Data Analysis?• Purpose, audience, use cases, tools used

• Unnormalized form (UNF)• First normal form (1NF)• What is a Key?• What is Composite Key?• Second normal form (2NF)• Database - Foreign Key• What are transitive functional dependencies?• Third normal form (3NF) • Boyce-Codd Normal Form (BCNF)• Importing CSV and XLS files into Power Query and Tableau• Normalizing a poorly designed table to 3NF using Power Query (unpivot) and Tableau (pivot) •• Power Query: fill down, transpose, merge columns, split columns• Exporting data into CSV and XLS files from Power Query and Tableau

• Crafting a master dataset from separate tables via Joins and Unions• Unions •• Combining multiple data sources with the same variables/ fields •• Combining multiple data sources with different variables/fields• Joins •• Understanding star schema •• Joining normalized tables using Power Query and Tableau •• Understanding fact tables vs. dimension tables •• Knowing what type of join to use | Types of joins and how they work | Cardinality •• Consolidating one-to-one joined tables | Merging queries in Power Query


Introductions, Ice Breaker

What is Data Wrangling

Database Design, Normalization, and Pivot/Unpivot

Data Preparation for Reporting

I.

II.

III.

IV.

DATA WRANGLING

23

• Normalize a poorly designed table; create and join fact tables and dimension tables; filter, group, and summarize into a report. Bonus: visualize the report in an interactive dashboard

Workshop



V.

VI.

VII.

•• Tidying messy data in Power Query (Column from Examples) •• Understanding the quirks of joining when dealing with messy data | Problems of many-to-many relationships (i.e. using factless fact tables) •• Understanding referential integrity •• Creating date tables: why and how •• Filtering, sorting, selecting variables by name, summarizing, group by variable via Power Query (M), Power Pivot (DAX), and Tableau


DATA WRANGLING

24


• What is data blending? Why blend data?• What is the difference between relationships (data blending) and joins?• Demo: how to blend data in Tableau

• Table calculations •• running total, difference from, percent different from, percent of, moving calculation, percent of total, percentile, rank• Window calculations• Level of Detail (LOD) expressions• Understanding calculated fields in blended data

• Avoiding snowflake dimensions / snowflake schemas• Creating data hierarchies in Power Query and Tableau

Data Blending in Tableau

Data Wrangling for Analysis in Tableau

Data Hierarchies

Workshop



I.

II.

III.

IV.

V.

VI.

DATA WRANGLING

25

storyiq.com.ph

[email protected]

7th floor, BA Lepanto Bldg.8474 Paseo de Roxas,Makati City Philippines 1227

+632 8782 5475

Documents

2020 Prospectus - StoryIQ...Our Lead Data Storytelling Trainer and a TEDx speaker, Dom brings a wealth of data storytelling experience to StoryIQ from his career at QBE, one of Australia’s