This is a presentation I gave on Data Visualization at a General Assembly event in Singapore, on January 22, 2016. The presso provides a brief history of dataviz as well as examples of common chart and visualization formatting mistakes that you should never make.
Silica-Paleontology with graph databases: Rooting through the relics of digit...Nic McPhee
We show how we can use graph databases to store and analyze genealogical data from evolutionary computation runs. In particular we use the Neo4j graph database to examine results of using two different selection mechanisms on a software synthesis problem. We find that lexicase selection has very different behaviors than tournament selection, e.g., there are times where lexicase selects an individual orders of magnitude more times than would ever be possible with tournament selection.
These slides are from our presentation at the 2015 Genetic Programming Theory and Practice (GPTP) workshop hosted by the Center for the Study of Complex Systems at the University of Michigan, May 2015. All this data was collected using the Clojush implementation of the PushGP system
APM event hosted by Midlands Branch on 24 May 2023.
Speaker: Andy Nolan
Estimating is the process of determining the level of cost, effort, resources and schedule you need to successfully implement your project. An accurate budget and schedule has been shown to improve project success - estimating is not only required, it's essential for a successful business. This event was held on 24 May 2023.
Estimating appears in many forms in a project's life from developing the initial budget and schedule, to estimating the duration of tasks in your plan, through to estimating risks and uncertainties.
The Rolls-Royce Heritage centre were available before the event for those wanting to explore the history of Rolls-Royce Aero engine development, this included a large collection exhibit engines from early day piston to modern large turbojet engines.
Attendees had the opportunity to discover and learn about Rolls-Royce products via the Heritage Centre, Network with fellow PM professionals, and grow knowledge of how important estimation is within the project Management function.
https://www.apm.org.uk/news/the-art-of-estimating/
Data Visualisation Design Workshop #UXbneCam Taylor
In this workshop we’ll explore both the art and science of communicating information graphically in the digital world.
With lots of great examples and a hands-on team exercise, the session is intended to make us think about how we can convey information more clearly and efficiently in our apps, presentations, reports, emails and other forms of communication.
This is a presentation I gave on Data Visualization at a General Assembly event in Singapore, on January 22, 2016. The presso provides a brief history of dataviz as well as examples of common chart and visualization formatting mistakes that you should never make.
Silica-Paleontology with graph databases: Rooting through the relics of digit...Nic McPhee
We show how we can use graph databases to store and analyze genealogical data from evolutionary computation runs. In particular we use the Neo4j graph database to examine results of using two different selection mechanisms on a software synthesis problem. We find that lexicase selection has very different behaviors than tournament selection, e.g., there are times where lexicase selects an individual orders of magnitude more times than would ever be possible with tournament selection.
These slides are from our presentation at the 2015 Genetic Programming Theory and Practice (GPTP) workshop hosted by the Center for the Study of Complex Systems at the University of Michigan, May 2015. All this data was collected using the Clojush implementation of the PushGP system
APM event hosted by Midlands Branch on 24 May 2023.
Speaker: Andy Nolan
Estimating is the process of determining the level of cost, effort, resources and schedule you need to successfully implement your project. An accurate budget and schedule has been shown to improve project success - estimating is not only required, it's essential for a successful business. This event was held on 24 May 2023.
Estimating appears in many forms in a project's life from developing the initial budget and schedule, to estimating the duration of tasks in your plan, through to estimating risks and uncertainties.
The Rolls-Royce Heritage centre were available before the event for those wanting to explore the history of Rolls-Royce Aero engine development, this included a large collection exhibit engines from early day piston to modern large turbojet engines.
Attendees had the opportunity to discover and learn about Rolls-Royce products via the Heritage Centre, Network with fellow PM professionals, and grow knowledge of how important estimation is within the project Management function.
https://www.apm.org.uk/news/the-art-of-estimating/
Data Visualisation Design Workshop #UXbneCam Taylor
In this workshop we’ll explore both the art and science of communicating information graphically in the digital world.
With lots of great examples and a hands-on team exercise, the session is intended to make us think about how we can convey information more clearly and efficiently in our apps, presentations, reports, emails and other forms of communication.
“Do I use a pie chart, a bar graph, or just a really big font size?” This presentation will cover a few tried-and-true and many novel ways to effectively present and leverage data to groups of students, parents, teachers, administrators, community members, and school board members. The presentation will also demonstrate some useful ways make data-driven decisions, and you will learn how to build a data wall displaying 350 students in a single weekend!
North Raleigh Rotarian Katie Turnbull gave a great presentation at our Friday morning extension meeting about data visualization. Katie is a consultant at research and advisory firm, Gartner, Inc.
How can you use infographics as a teaching tool? How can you go further and inspire your students to make infographics to show what they have learned? This presentation will help take you down that path to bring infographics into your elementary, middle or high school classroom.
What Is Good DataViz Design? Presented at the Big Design 2016 conference in Addison, TX.
Good DataViz Design means going beyond the charting templates and designing visualizations that reveal insights and tell stories to your audience. There are hundreds of ways to visualize data, and once you have chosen an appropriate visualization style for your data, you must customize the design to make sure your audience quickly and easily understands your message. You need your own toolbox of applications and websites to create different visualizations and charts, and they will all benefit from these core principles of good dataviz design.
Links from the presentation are all available here: http://www.coolinfographics.com/bigd16
AMES 2016 - The Human Side of AnalyticsStephen Tracy
Last year the global analytics industry was estimated to be worth $125 billion in hardware, software and services revenue. Consequently the market has been flooded with more tools, platforms and tech than you can shake a calculator at. When it comes to data, the core challenge many businesses face today seems to have less to do with analytics technology and infrastructure and more to do with finding the right people, talent and skills. In this presentation Stephen will share 10 lessons for building a successful analytics program through a ‘people-first’ strategy.
AS 6 years of my personal TIBCO Spotfire Community come to an end in 2019 I thought it would be a nice idea to collect some of the Spotfire dashboards I have created and shared during this time. Have fun with it. And thanks to the 165 followers on this channel!
Data Storytelling - Game changer for Analytics Gramener
50 Percent of Data Science Projects Fail at
Consumption: Can Storytelling Be Your Game
Changer
Growth of Self Service BI has generated a lot of
dashboards, but “lots” does not always mean “good” or
“useful”.
• While advances in AI/ML lead to deeper insights,
business teams struggle with the adoption of
algorithms and consumption
• How can data officers and analytics leaders
get better business ROI from their data science
investments?
• This session will show you how to unleash the
power of data storytelling for business decision-
making, using industry examples
Creating a Data-Driven Government: Big Data With PurposeTyrone Grandison
The U.S. Department of Commerce collects, processes and disseminates data on a range of issues that impact our nation. Whether it's data on the economy, the environment, or technology, data is critical in fulfilling the Department's mission of creating the conditions for economic growth and opportunity. It is this data that provides insight, drives innovation, and transforms our lives. The U.S. Department of Commerce has become known as "America's Data Agency" due to the tens of thousands of datasets including satellite imagery, material standards and demographic surveys.
But having a host of data and ensuring that this data is open and accessible to all are two separate issues. The latter, expanding open data access, is now a key pillar of the Commerce Department's mission. It was this focus on enhancing open data that led to the creation of the Commerce Data Service (CDS).
The mission at the Commerce Data Service is to enable more people to use big data from across the department in innovative ways and across multiple fields. In this talk, I will explore how we are using big data to create a data-driven government.
This talk is a keynote given at the Texas tech University's Big Data Symposium.
This is a MUST-VIEW highlighting 6 STRATEGIES essential for any manager who must present complicated DATA & CHARTS at meetings, presentations or public speeches. As an added incentive, the slides are presented with wit and humour by a special MASTER of CEREMONIES! ENJOY!
p.s. You have to Download the PPT to witness how effective animation can actually be when presenting!
Estes são os slides resumindo o MeetUp de fevereiro na Tis Tech Angola, em 17/02/2018. Nele apresentei uma visão geral sobre o "Big Data" e coloquei muitos links para pesquisa. É um bom ponto de partida para quem gostaria de saber mais sobre o assunto (baseado em muita informação recebida no MBA+ da FIAP) e em cursos online (Edx, Coursera e Datacamp) feitos após a conclusão do curso, em 2016.
Obs: procurei citar todas as fotes de pesquisa e respeitar a autoria das informações, o que deixou o material rico em referências para estudo.
Keynote provided at the NYS GeoSpatial Summit. Attempted to generate an interactive discussion and encourage the audience to think of geo in a different way. Questions were crowd sourced using Google Moderator and Google Docs. #NYGSS
Dirty data science machine learning on non-curated dataGael Varoquaux
These slides are a one-hour course on machine learning with non-curated data.
According to industry surveys, the number one hassle of data scientists is cleaning the data to analyze it. Here, I survey what "dirtyness" forces time-consuming cleaning. We will then cover two specific aspects of dirty data: non-normalized entries and missing values. I show how, for these two problems, machine-learning practice can be adapted to work directly on a data table without curation. The normalization problem can be tackled by adapting methods from natural language processing. The missing-values problem will lead us to revisit classic statistical results in the setting of supervised learning.
Catalant CEO and Co-Founder, Rob Biederman, presented at the Future of Work Austin event in March of 2017. In this presentation, he shares his thoughts on the history of work and what changes we can expect in the coming years. Work is being reimagined; learn how your company can get ahead of this shift.
Talk at Pune Data Conference 2018 on the topic - Make Data Speak. Focus of the talk is to demonstrate how the outputs from a data analysis using various technologies can be made more consumable.
Bring to attention the Ethical aspects of making data speak.
This presentation was for Social Media Week Berlin on Tuesday, 24th September. It was targeted at NGOs, NPOs, activist organisations and charities who have important key messages to share with the community. The event will combine elements of a presentation and workshop. We will examine case studies of campaigns that have successfully used data visualisation in tandem with social media and content marketing techniques to spread information and ideas, and to counteract prevailing myths about climate change and renewable energy technology. We will then allow time for participants to split up into small working groups. Structured discussion tasks and group feedback will allow participants to investigate how these strategies can apply to their own organisation or issue. Participants will learn practical steps for identifying important messages, researching and developing content, incorporating data visualisation in a powerful and meaningful way, and promoting their data visualisation campaigns through social media and email outreach. In particular, the event will focus on developing powerful stories that will attract the support of influential sharers and thought leaders from a range of backgrounds, from activism through to industry, so as to maximise the campaign's reach and impact.
Storytelling for analytics | Naveen Gattu | CDAO Apex 2020Gramener
Chief data and analytics officers (CDAO) Apex Winter 2020 conference in Orlando was an intimate gathering of analytics leaders from across the world.
Gramener's Co-founder and COO, Naveen Gattu, spoke about the importance of storytelling on easy data consumption and impact on data-driven decision making for business users.
“Do I use a pie chart, a bar graph, or just a really big font size?” This presentation will cover a few tried-and-true and many novel ways to effectively present and leverage data to groups of students, parents, teachers, administrators, community members, and school board members. The presentation will also demonstrate some useful ways make data-driven decisions, and you will learn how to build a data wall displaying 350 students in a single weekend!
North Raleigh Rotarian Katie Turnbull gave a great presentation at our Friday morning extension meeting about data visualization. Katie is a consultant at research and advisory firm, Gartner, Inc.
How can you use infographics as a teaching tool? How can you go further and inspire your students to make infographics to show what they have learned? This presentation will help take you down that path to bring infographics into your elementary, middle or high school classroom.
What Is Good DataViz Design? Presented at the Big Design 2016 conference in Addison, TX.
Good DataViz Design means going beyond the charting templates and designing visualizations that reveal insights and tell stories to your audience. There are hundreds of ways to visualize data, and once you have chosen an appropriate visualization style for your data, you must customize the design to make sure your audience quickly and easily understands your message. You need your own toolbox of applications and websites to create different visualizations and charts, and they will all benefit from these core principles of good dataviz design.
Links from the presentation are all available here: http://www.coolinfographics.com/bigd16
AMES 2016 - The Human Side of AnalyticsStephen Tracy
Last year the global analytics industry was estimated to be worth $125 billion in hardware, software and services revenue. Consequently the market has been flooded with more tools, platforms and tech than you can shake a calculator at. When it comes to data, the core challenge many businesses face today seems to have less to do with analytics technology and infrastructure and more to do with finding the right people, talent and skills. In this presentation Stephen will share 10 lessons for building a successful analytics program through a ‘people-first’ strategy.
AS 6 years of my personal TIBCO Spotfire Community come to an end in 2019 I thought it would be a nice idea to collect some of the Spotfire dashboards I have created and shared during this time. Have fun with it. And thanks to the 165 followers on this channel!
Data Storytelling - Game changer for Analytics Gramener
50 Percent of Data Science Projects Fail at
Consumption: Can Storytelling Be Your Game
Changer
Growth of Self Service BI has generated a lot of
dashboards, but “lots” does not always mean “good” or
“useful”.
• While advances in AI/ML lead to deeper insights,
business teams struggle with the adoption of
algorithms and consumption
• How can data officers and analytics leaders
get better business ROI from their data science
investments?
• This session will show you how to unleash the
power of data storytelling for business decision-
making, using industry examples
Creating a Data-Driven Government: Big Data With PurposeTyrone Grandison
The U.S. Department of Commerce collects, processes and disseminates data on a range of issues that impact our nation. Whether it's data on the economy, the environment, or technology, data is critical in fulfilling the Department's mission of creating the conditions for economic growth and opportunity. It is this data that provides insight, drives innovation, and transforms our lives. The U.S. Department of Commerce has become known as "America's Data Agency" due to the tens of thousands of datasets including satellite imagery, material standards and demographic surveys.
But having a host of data and ensuring that this data is open and accessible to all are two separate issues. The latter, expanding open data access, is now a key pillar of the Commerce Department's mission. It was this focus on enhancing open data that led to the creation of the Commerce Data Service (CDS).
The mission at the Commerce Data Service is to enable more people to use big data from across the department in innovative ways and across multiple fields. In this talk, I will explore how we are using big data to create a data-driven government.
This talk is a keynote given at the Texas tech University's Big Data Symposium.
This is a MUST-VIEW highlighting 6 STRATEGIES essential for any manager who must present complicated DATA & CHARTS at meetings, presentations or public speeches. As an added incentive, the slides are presented with wit and humour by a special MASTER of CEREMONIES! ENJOY!
p.s. You have to Download the PPT to witness how effective animation can actually be when presenting!
Estes são os slides resumindo o MeetUp de fevereiro na Tis Tech Angola, em 17/02/2018. Nele apresentei uma visão geral sobre o "Big Data" e coloquei muitos links para pesquisa. É um bom ponto de partida para quem gostaria de saber mais sobre o assunto (baseado em muita informação recebida no MBA+ da FIAP) e em cursos online (Edx, Coursera e Datacamp) feitos após a conclusão do curso, em 2016.
Obs: procurei citar todas as fotes de pesquisa e respeitar a autoria das informações, o que deixou o material rico em referências para estudo.
Keynote provided at the NYS GeoSpatial Summit. Attempted to generate an interactive discussion and encourage the audience to think of geo in a different way. Questions were crowd sourced using Google Moderator and Google Docs. #NYGSS
Dirty data science machine learning on non-curated dataGael Varoquaux
These slides are a one-hour course on machine learning with non-curated data.
According to industry surveys, the number one hassle of data scientists is cleaning the data to analyze it. Here, I survey what "dirtyness" forces time-consuming cleaning. We will then cover two specific aspects of dirty data: non-normalized entries and missing values. I show how, for these two problems, machine-learning practice can be adapted to work directly on a data table without curation. The normalization problem can be tackled by adapting methods from natural language processing. The missing-values problem will lead us to revisit classic statistical results in the setting of supervised learning.
Catalant CEO and Co-Founder, Rob Biederman, presented at the Future of Work Austin event in March of 2017. In this presentation, he shares his thoughts on the history of work and what changes we can expect in the coming years. Work is being reimagined; learn how your company can get ahead of this shift.
Talk at Pune Data Conference 2018 on the topic - Make Data Speak. Focus of the talk is to demonstrate how the outputs from a data analysis using various technologies can be made more consumable.
Bring to attention the Ethical aspects of making data speak.
This presentation was for Social Media Week Berlin on Tuesday, 24th September. It was targeted at NGOs, NPOs, activist organisations and charities who have important key messages to share with the community. The event will combine elements of a presentation and workshop. We will examine case studies of campaigns that have successfully used data visualisation in tandem with social media and content marketing techniques to spread information and ideas, and to counteract prevailing myths about climate change and renewable energy technology. We will then allow time for participants to split up into small working groups. Structured discussion tasks and group feedback will allow participants to investigate how these strategies can apply to their own organisation or issue. Participants will learn practical steps for identifying important messages, researching and developing content, incorporating data visualisation in a powerful and meaningful way, and promoting their data visualisation campaigns through social media and email outreach. In particular, the event will focus on developing powerful stories that will attract the support of influential sharers and thought leaders from a range of backgrounds, from activism through to industry, so as to maximise the campaign's reach and impact.
Storytelling for analytics | Naveen Gattu | CDAO Apex 2020Gramener
Chief data and analytics officers (CDAO) Apex Winter 2020 conference in Orlando was an intimate gathering of analytics leaders from across the world.
Gramener's Co-founder and COO, Naveen Gattu, spoke about the importance of storytelling on easy data consumption and impact on data-driven decision making for business users.
Data Visualization for Policy Decision Making (impulse talk)Jose Berengueres
Agile Government: Becoming Future-Proof
InterContinental Dubai Festival City
17 - 18 February 2020
Impulse talk
more info can be found at https://www.uaepublicpolicyforum.ae/
Oprah Winfrey: A Leader in Media, Philanthropy, and Empowerment | CIO Women M...CIOWomenMagazine
This person is none other than Oprah Winfrey, a highly influential figure whose impact extends beyond television. This article will delve into the remarkable life and lasting legacy of Oprah. Her story serves as a reminder of the importance of perseverance, compassion, and firm determination.
The Team Member and Guest Experience - Lead and Take Care of your restaurant team. They are the people closest to and delivering Hospitality to your paying Guests!
Make the call, and we can assist you.
408-784-7371
Foodservice Consulting + Design
Artificial intelligence (AI) offers new opportunities to radically reinvent the way we do business. This study explores how CEOs and top decision makers around the world are responding to the transformative potential of AI.
Modern Database Management 12th Global Edition by Hoffer solution manual.docxssuserf63bd7
https://qidiantiku.com/solution-manual-for-modern-database-management-12th-global-edition-by-hoffer.shtml
name:Solution manual for Modern Database Management 12th Global Edition by Hoffer
Edition:12th Global Edition
author:by Hoffer
ISBN:ISBN 10: 0133544613 / ISBN 13: 9780133544619
type:solution manual
format:word/zip
All chapter include
Focusing on what leading database practitioners say are the most important aspects to database development, Modern Database Management presents sound pedagogy, and topics that are critical for the practical success of database professionals. The 12th Edition further facilitates learning with illustrations that clarify important concepts and new media resources that make some of the more challenging material more engaging. Also included are general updates and expanded material in the areas undergoing rapid change due to improved managerial practices, database design tools and methodologies, and database technology.
6. data > information > kn > wisdom
many --------------------> one
many ----------------------> scarce ?
-----------------------------> value arrow ?
1 What is data?
7. data > information > kn > wisdom
many --------------------> one
many ----------------------> scarce ?
-----------------------------> value?
1 What is data?
9. data > HOW ? > wisdom
2 How to arrive to wisdom?
10. data > HOW ? > wisdom
2 How to arrive to wisdom?
Synthesis process: the dialectic combination of thesis and antithesis into a
higher stage of truth
20. 6 Exercise! Visualize the following Gender statistic
Of all the 23,859 respondents
of the 2018 kaggle data science survey 4,513
said they were female.
38. 11 Execisie! Salary distribution of data scientists...
#HMW make more meaning?
https://www.kaggle.com/headsortails/what-we-do-in-the-
kernels-a-kaggle-survey-story/report
39. How to use gravity to convey power?
< -- ? -- >
52. Schedule
13:30 Intro
13:40 (1) Making sense of data
14:10 break
14:20 (2) Communicating w/ charts
14:50 break
15:00 (3) Strategy Mapping
53. 12 Cultural locales
• color meaning by country
• color awarenes by gender
• color awarenss by profession
• sexism awareness by country
• Right to left languages
54. 13 Storytelling patterns
Patterns of succesful storytelling
• A/B (testing, advertising)
• What is... What could be (duarte)
• Aha moment! (Welch)
• Heroes journey (duarte)
55.
56. 14 Storytelling patterns in charts: symbolic charts
1. Winners
2. Visualizing ALL OR NOTHING relationships
3. Expressing Enormity
4. Empathy & Personas
5. Log vs. Volumetric charts
62. 17 Expressing enormity. Exercise! How would you express the follwowing..
• # of chart in the universe 102,023,342,012
• # of those charts which are great 9,993
68. 19 Age bias in arrests in USA. Exercise! HMW empathise this chart?
https://www.kaggle.com/harriken/police-dogs-and-grey-hair-will-save-you-from-jail
70. 19 Gender & Violence in in arrests in USA. Exercise! HMW empathise this
chart?
https://www.kaggle.com/harriken/police-dogs-and-grey-hair-will-save-you-from-jail
80. [1] https://www.aauw.org/research/solving-the-equation/
[2] https://www.theverge.com/2018/11/2/18057716/google-walkout-20-thousand-employees-ceo-sundar-pichai-meeting
[3] https://www.forbes.com/sites/womensmedia/2017/08/03/breaking-down-the-gender-gap-in-data-science/#129d1bb74287
[4] https://www.kaggle.com/paultimothymooney/2018-kaggle-machine-learning-data-science-survey
[5] https://en.wikipedia.org/wiki/Generations_in_the_workforce
[6] Sinton, E (2011). ‘Baby boomers are very privileged human beings’ https://www.telegraph.co.uk/finance/personalfinance/pensions/8840963/Baby-
boomers-are-very-privileged-human-beings.html retrieved October 23, 2013 from www.telegraph.co.uk
[7] Ken Blanchard Companies. (2009). Next Generation of
workers. http://www.kenblanchard.com/img/pub/Blanchard_Next_Generation_of_Workers.pdf Retrieved October 14, 2013, from kenblanchard.com
[8] Adecco Group UK and Ireland. (n.d.). Managing the modern workforce. http://www.adeccogroupuk.co.uk/SiteCollectionDocuments/Adecco-Group-
Workplace-Revolution.pdf Retrieved October 13, 2013, from www.Adeccouk.co.uk
ref. needed
[10] https://en.wikipedia.org/wiki/Affluence_in_the_United_States
[11] https://www.epi.org/blog/top-1-0-percent-reaches-highest-wages-ever-up-157-percent-since-1979/
[12] J. Berengueres, Sketch thinking. 2016
[13] https://en.wikipedia.org/wiki/Marimekko#Marimekko_chart
[14] ref. needed
[15] https://www.kaggle.com/ash316/kaggle-journey-2017-2018
[16] https://en.wikipedia.org/wiki/BRICS
[17] https://www.kaggle.com/harriken/brics-growth
[18] See primary vs. secondary color in https://material.io/design/color/the-color-system.html#color-theme-creation
[19] Dutta, S., Reynoso, R.E., Garanasvili, A., Saxena, K., Lanvin, B., Wunsch-Vincent, S., León, L.R. and Guadagno, F., 2018. THE GLOBAL INNOVATION
INDEX 2018: ENERGIZING THE WORLD WITH INNOVATION. GLOBAL INNOVATION INDEX 2018, p.1.
[20] CSV file global innovation in https://www.globalinnovationindex.org/analysis-indicator
[21] World Bank, https://data.worldbank.org/indicator/SP.POP.TOTL
[22] https://en.wikipedia.org/wiki/Kendall_rank_correlation_coefficient
[23] https://www.pinterest.com/pin/281615782925970581/?lp=true
[24] https://en.wikipedia.org/wiki/Regression_toward_the_mean
[25] https://www.kaggle.com/harriken/residuals-fig8b-test
[26] https://www.kaggle.com/harriken/police-dogs-and-grey-hair-will-save-you-from-jail
References
Editor's Notes
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
the dialectic combination of thesis and antithesis into a higher stage of truth
the dialectic combination of thesis and antithesis into a higher stage of truth
the dialectic combination of thesis and antithesis into a higher stage of truth
olution
Reflection:
Wisdom is not kn.
Wisdom is not here.
Wisdom not just a summary, it is something more. Context?
Reflection:
Wisdom is not here.
Wisdom not just a summary, it is something more (recall sythesis definition). Context?
not a summary:
not a summary:
not a summary:
not a summary:
the pyramid represnts power and scarcity at the same time.
the pyramid represnts power and scarcity at the same time.
A 2015 survey showed that only 26% of data jobs are held by women [1]. However, lack of feminine perspective creates blind spots such as the #googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents
A 2015 survey showed that only 26% of data jobs are held by women [1]. However, lack of feminine perspective creates blind spots such as the #googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents
A 2015 survey showed that only 26% of data jobs are held by women [1]. However, lack of feminine perspective creates blind spots such as the #googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents
A 2015 survey showed that only 26% of data jobs are held by women [1]. However, lack of feminine perspective creates blind spots such as the #googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents
A 2015 survey showed that only 26% of data jobs are held by women [1]. However, lack of feminine perspective creates blind spots such as the #googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents
A 2015 survey showed that only 26% of data jobs are held by women [1]. However, lack of feminine perspective creates blind spots such as the #googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents
A 2015 survey showed that only 26% of data jobs are held by women [1]. However, lack of feminine perspective creates blind spots such as the #googleWalkout [2] and is bad business - says Forbes [3]. In Fig. 1 (above), we use superhero-themes #batman #wonderwoman to visualize the heavy topic of #gender_equality in #datascience. See a bar chart for a more accurate breakdown [4]. Source: survey question Q1 - What is your gender? Sample size = 23,859 respondents
What can we learn from our data scientist uncle? Fig. 2 is user distribution by age. We use a two-color scheme [18] to highlight which age-group won most competitions per user*. However, just a few too many age bins can overwhelm any reader. A way to declutter and structure the bins into usable knowledge is to reduce their numbers and group them in a familiar, relatable form. One way is to group the bins by generations. In this case, we used the Generations in the workforce (the gen X, Y, Z and the Boomers [5]) and we are interested to see which group is the most productive in terms of competitions and cash prizes per user. Because everyone belongs to a generation this chart can become very personable. What can we learn from the wisdom that each generation offers?
Generation year brakets and work-ethic attribute
The Baby Boomers, born 1946 - 1964 “often branded workaholics” [6]
Gen X, born 1967 - 1977 “this generation works to live and carry with them a level of cynicism” [7]
Gen Y, “Millennials” born 1980 - 2000 “considered the most educated and self-aware generation in employment” [8]
Gen Z, born 2000 -
Fig. 3 tells a #digitaldivide story. How inclusive are we as a community? Should we pat ourselves on our backs? Again, to create knowledge we need to relate the data to the reader in ways they can connect it to other knowledge they have. Here, one way is to use the income percentiles (see #onepercent). In US, to belong to the 1% elite, one needs to earn more than $422k per year [10]. About 23 respondents declared that they do. In addition, about 6% declared they belong to the 10% percentile, a very inclusive number because 6% is similar to 10%. The 10% percentile income is about $166k in US [11], so if the sample reflects the distribution found in society it means it is at least somehow inclusive. We add a smiley emoji to reassure the reader that yes, this is good.
However, those numbers are for US household incomes. When we look globally, the 1% percentile thereshold is $32k per year. This puts 60% of the respondents in the top 1%. 60% is very different from 1% so globally this datapoint does not support inclusiveness because it does not reflect the global distribution. #Ahamoment. One way to create such moments in the story is to A/Bify the story by switching between two points of view. Source - Q9 : What is your current yearly compensation (approximate $USD)?
Fig. 3 tells a #digitaldivide story. How inclusive are we as a community? Should we pat ourselves on our backs? Again, to create knowledge we need to relate the data to the reader in ways they can connect it to other knowledge they have. Here, one way is to use the income percentiles (see #onepercent). In US, to belong to the 1% elite, one needs to earn more than $422k per year [10]. About 23 respondents declared that they do. In addition, about 6% declared they belong to the 10% percentile, a very inclusive number because 6% is similar to 10%. The 10% percentile income is about $166k in US [11], so if the sample reflects the distribution found in society it means it is at least somehow inclusive. We add a smiley emoji to reassure the reader that yes, this is good.
However, those numbers are for US household incomes. When we look globally, the 1% percentile thereshold is $32k per year. This puts 60% of the respondents in the top 1%. 60% is very different from 1% so globally this datapoint does not support inclusiveness because it does not reflect the global distribution. #Ahamoment. One way to create such moments in the story is to A/Bify the story by switching between two points of view. Source - Q9 : What is your current yearly compensation (approximate $USD)?
Fig. 3 tells a #digitaldivide story. How inclusive are we as a community? Should we pat ourselves on our backs? Again, to create knowledge we need to relate the data to the reader in ways they can connect it to other knowledge they have. Here, one way is to use the income percentiles (see #onepercent). In US, to belong to the 1% elite, one needs to earn more than $422k per year [10]. About 23 respondents declared that they do. In addition, about 6% declared they belong to the 10% percentile, a very inclusive number because 6% is similar to 10%. The 10% percentile income is about $166k in US [11], so if the sample reflects the distribution found in society it means it is at least somehow inclusive. We add a smiley emoji to reassure the reader that yes, this is good.
However, those numbers are for US household incomes. When we look globally, the 1% percentile thereshold is $32k per year. This puts 60% of the respondents in the top 1%. 60% is very different from 1% so globally this datapoint does not support inclusiveness because it does not reflect the global distribution. #Ahamoment. One way to create such moments in the story is to A/Bify the story by switching between two points of view. Source - Q9 : What is your current yearly compensation (approximate $USD)?
Fig. 3 tells a #digitaldivide story. How inclusive are we as a community? Should we pat ourselves on our backs? Again, to create knowledge we need to relate the data to the reader in ways they can connect it to other knowledge they have. Here, one way is to use the income percentiles (see #onepercent). In US, to belong to the 1% elite, one needs to earn more than $422k per year [10]. About 23 respondents declared that they do. In addition, about 6% declared they belong to the 10% percentile, a very inclusive number because 6% is similar to 10%. The 10% percentile income is about $166k in US [11], so if the sample reflects the distribution found in society it means it is at least somehow inclusive. We add a smiley emoji to reassure the reader that yes, this is good.
However, those numbers are for US household incomes. When we look globally, the 1% percentile thereshold is $32k per year. This puts 60% of the respondents in the top 1%. 60% is very different from 1% so globally this datapoint does not support inclusiveness because it does not reflect the global distribution. #Ahamoment. One way to create such moments in the story is to A/Bify the story by switching between two points of view. Source - Q9 : What is your current yearly compensation (approximate $USD)?
is this wis
not a summary:
not a summary:
US-UK-EU gap
The US-EU gap is about 50%. However, the UK mean closer to the EU6 mean than to the US mean. Does this mean we discard language barrier as a explanatory factor for the gap? Note: The BRICS, and EU6 mean is mean of country means, not weighted by respondents.
Aesthetic considerations
This color scheme is called the red on grey, it is my favorite scheme for charts. Unlike, other schemes such as purple on grey, it is gender neutral [23]. However, for it to work the red surface must be kept to a minimum, otherwise it comes across as strident. The blue on grey scheme does not have this limitation (See Figs. 1-5). However, the red on grey has one secret advantage. Usually, using three colors in a chart will clutter it, but because the chromatic distance between red and any shade of grey is so large, we can get away by using black (as a gray 85%) as a third color with a small clutter trade-off.
Source - World Bank Population Data 2016, Q11 - Current country of residence [20]
US-UK-EU gap
The US-EU gap is about 50%. However, the UK mean closer to the EU6 mean than to the US mean. Does this mean we discard language barrier as a explanatory factor for the gap? Note: The BRICS, and EU6 mean is mean of country means, not weighted by respondents.
Aesthetic considerations
This color scheme is called the red on grey, it is my favorite scheme for charts. Unlike, other schemes such as purple on grey, it is gender neutral [23]. However, for it to work the red surface must be kept to a minimum, otherwise it comes across as strident. The blue on grey scheme does not have this limitation (See Figs. 1-5). However, the red on grey has one secret advantage. Usually, using three colors in a chart will clutter it, but because the chromatic distance between red and any shade of grey is so large, we can get away by using black (as a gray 85%) as a third color with a small clutter trade-off.
Source - World Bank Population Data 2016, Q11 - Current country of residence [20]
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
US-UK-EU gap
The US-EU gap is about 50%. However, the UK mean closer to the EU6 mean than to the US mean. Does this mean we discard language barrier as a explanatory factor for the gap? Note: The BRICS, and EU6 mean is mean of country means, not weighted by respondents.
Aesthetic considerations
This color scheme is called the red on grey, it is my favorite scheme for charts. Unlike, other schemes such as purple on grey, it is gender neutral [23]. However, for it to work the red surface must be kept to a minimum, otherwise it comes across as strident. The blue on grey scheme does not have this limitation (See Figs. 1-5). However, the red on grey has one secret advantage. Usually, using three colors in a chart will clutter it, but because the chromatic distance between red and any shade of grey is so large, we can get away by using black (as a gray 85%) as a third color with a small clutter trade-off.
Source - World Bank Population Data 2016, Q11 - Current country of residence [20]
US-UK-EU gap
The US-EU gap is about 50%. However, the UK mean closer to the EU6 mean than to the US mean. Does this mean we discard language barrier as a explanatory factor for the gap? Note: The BRICS, and EU6 mean is mean of country means, not weighted by respondents.
Aesthetic considerations
This color scheme is called the red on grey, it is my favorite scheme for charts. Unlike, other schemes such as purple on grey, it is gender neutral [23]. However, for it to work the red surface must be kept to a minimum, otherwise it comes across as strident. The blue on grey scheme does not have this limitation (See Figs. 1-5). However, the red on grey has one secret advantage. Usually, using three colors in a chart will clutter it, but because the chromatic distance between red and any shade of grey is so large, we can get away by using black (as a gray 85%) as a third color with a small clutter trade-off.
Source - World Bank Population Data 2016, Q11 - Current country of residence [20]
all good stories...
US-UK-EU gap
The US-EU gap is about 50%. However, the UK mean closer to the EU6 mean than to the US mean. Does this mean we discard language barrier as a explanatory factor for the gap? Note: The BRICS, and EU6 mean is mean of country means, not weighted by respondents.
Aesthetic considerations
This color scheme is called the red on grey, it is my favorite scheme for charts. Unlike, other schemes such as purple on grey, it is gender neutral [23]. However, for it to work the red surface must be kept to a minimum, otherwise it comes across as strident. The blue on grey scheme does not have this limitation (See Figs. 1-5). However, the red on grey has one secret advantage. Usually, using three colors in a chart will clutter it, but because the chromatic distance between red and any shade of grey is so large, we can get away by using black (as a gray 85%) as a third color with a small clutter trade-off.
Source - World Bank Population Data 2016, Q11 - Current country of residence [20]
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth
Part 1 - Making sense of data. Time: 30 minutes. Dataset: Kaggle 2018 Data science community survey [5-6]. Topics: How to Summarize large amounts of country level data. How to cluster country data. How to use color for visual clarity. How to style chart for impact. How to combine economic kpis in a dataset. How to use scatter plots for prescriptive analytics. Storytelling with regression and the mean reversion.
(10 minutes break)
Part 2 - Communicating effectively with charts. Time: 30 minutes. Dataset: Data Science for Good: Center for Policing Equity dataset. Displaying bivariate correlations and differences.
(10 minutes break)
Part 3 – Strategic policymaking with Wardley maps. Time: 30 minutes. Case study: Designing a curriculum of the future at a university. Using maps for strategic decision making.
the dialectic combination of thesis and antithesis into a higher stage of truth