Také jste snili o psaní pro luxusní restauraci, sportovní lovebrand nebo kultovní nakladatelství? A pak přišla první strojírenská firma, první e-shop s vrtačkami a první nesrozumitelný software.
Nuda? Ani náhodou. Stačí maličkost. Dívat se na obsah očima zákazníků. A pochopit, že pro ně často "ta divná věc" znamená celý svět.
Ukážu vám, jak se s nudným obsahem vypořádat, a přihodím příklady včetně odkrytých čísel. Na nich uvidíte, jak může na první pohled nudný obsah v nudném oboru uspět a vydělat peníze.
Electronic commerce (ecommerce) is a type of business model, or segment of a larger business model, that enables a firm or individual to conduct business over an electronic network, typically the internet
The purpose of strategic planning
The purpose of strategic planning is to set overall goals for your business and to develop a plan to achieve them. It involves stepping back from your day-to-day operations and asking where your business is headed and what its priorities should be.
Strategic planning is intended to accomplish three important tasks:
to clarify the outcomes that an organization wishes to achieve;
to select the broad strategies that will enable the organization to achieve those outcomes;
to identify ways to measure progress
Leveraging Data for the Internet of Things CLEVER°FRANKE
In an informal workshop hosted by Bob Corporaal, the group looked at the connection between IoT, Digital Transformation and Data Visualization. They explored a step-by-step process that can help create more value with the data from your IoT application.
presented at FITC Toronto 2018
More info at http://fitc.ca/event/to18/
Presented by
Corey Ouellette, Thomson Reuters
Overview
When you think of “data visualization” what is the very first thing that comes to mind? For many, it’s bar graphs, pie charts, and histograms, or maybe some combination thereof. You’re not wrong – but it’s so much more than that. The era of pie and bar charts has come and gone; these traditional visualizations alone are insufficient. Now is the time of data visualized on a rich canvas. A canvas that not only informs, but immerses you in information in much the same way that your favourite book immerses you in its narrative.
Objective
When attendees leave, that they walk away with an understanding of how development, design and data are strongly intertwined with one other. When aligned with customers needs, these aspects create a meaningful and actionable experience.
Target Audience
Designers and developers interested furthering their appetite for visualization
Five Things Audience Members Will Learn
How data visualization can lead to data exploration
Creating an experience with information
New models of data visualization
Telling a story through data
How to blend design and development through data visualization
Také jste snili o psaní pro luxusní restauraci, sportovní lovebrand nebo kultovní nakladatelství? A pak přišla první strojírenská firma, první e-shop s vrtačkami a první nesrozumitelný software.
Nuda? Ani náhodou. Stačí maličkost. Dívat se na obsah očima zákazníků. A pochopit, že pro ně často "ta divná věc" znamená celý svět.
Ukážu vám, jak se s nudným obsahem vypořádat, a přihodím příklady včetně odkrytých čísel. Na nich uvidíte, jak může na první pohled nudný obsah v nudném oboru uspět a vydělat peníze.
Electronic commerce (ecommerce) is a type of business model, or segment of a larger business model, that enables a firm or individual to conduct business over an electronic network, typically the internet
The purpose of strategic planning
The purpose of strategic planning is to set overall goals for your business and to develop a plan to achieve them. It involves stepping back from your day-to-day operations and asking where your business is headed and what its priorities should be.
Strategic planning is intended to accomplish three important tasks:
to clarify the outcomes that an organization wishes to achieve;
to select the broad strategies that will enable the organization to achieve those outcomes;
to identify ways to measure progress
Leveraging Data for the Internet of Things CLEVER°FRANKE
In an informal workshop hosted by Bob Corporaal, the group looked at the connection between IoT, Digital Transformation and Data Visualization. They explored a step-by-step process that can help create more value with the data from your IoT application.
presented at FITC Toronto 2018
More info at http://fitc.ca/event/to18/
Presented by
Corey Ouellette, Thomson Reuters
Overview
When you think of “data visualization” what is the very first thing that comes to mind? For many, it’s bar graphs, pie charts, and histograms, or maybe some combination thereof. You’re not wrong – but it’s so much more than that. The era of pie and bar charts has come and gone; these traditional visualizations alone are insufficient. Now is the time of data visualized on a rich canvas. A canvas that not only informs, but immerses you in information in much the same way that your favourite book immerses you in its narrative.
Objective
When attendees leave, that they walk away with an understanding of how development, design and data are strongly intertwined with one other. When aligned with customers needs, these aspects create a meaningful and actionable experience.
Target Audience
Designers and developers interested furthering their appetite for visualization
Five Things Audience Members Will Learn
How data visualization can lead to data exploration
Creating an experience with information
New models of data visualization
Telling a story through data
How to blend design and development through data visualization
Data visualization has become increasingly more important and sits at the center of how people learn about and experience the world. We process information about politics, business insights and every day decisions through “visual soundbites”. As data journalists, we have incredible power to both positively influence as well as misguide conversations with the choices that we make when presenting graphical results.
In this presentation, we will share some of the best practices that help deliver stories that matter and avoid creating those that mislead.
Most presenters have many misconceptions when it comes to presenting data, especially to their senior management. This presentation busts 3 common myths and provides 3 recommendations for presenting data clearly and effectively.
The ultimate guide to data storytelling | MaterclassGramener
Gramener collaborated with Nasscom to conduct an online masterclass session on "Storytelling With Data." Gramener's CEO, S Anand, led the masterclass and shared some important slides on how to make data stories and how to drive storytelling.
The slides talk about the structure of data stories and how to find meaning full insights from data. There are real-time examples of data analysis and visualizations we created a Gramener to communicate insights as stories.
This is an ultimate guide on data storytelling that offers tips to create data stories, things to keep in mind while making storylines, and choosing designs to make a design-led data story.
Know more about Gramener's data storytelling workshop for analysts and data scientists at https://gramener.com/data-storytelling-workshop
Susan Moore, whose global work and results were published in the book, Wake Me Up When the Data is Over, has held senior management positions with Microsoft and Eastman. Elissa Fink is the Senior Vice President of Tableau Software. Together, these two dynamic business leaders addressed the fundamental shift in how we see and process data.
SOCS185N-11504 Assignments Week 5 Assignment: Essay - Yo…!
Total Points: 175.0
Week 5 Assignment: Essay - You
Decide
Due Monday by 1:59am Points 175
Submitting a file upload
Week 5 Essay Grading Rubric - 175 pts
Criteria Ratings Pts
10.0 pts
10.0 pts
35.0 pts
50.0 pts
20.0 pts
20.0 pts
10.0 pts
20.0 pts
Submit Assignment
Required Resources
Read/review the following resources for this activity:
Textbook: Chapter 9
Lesson
Link (website): Pew Research Center
Click on the Social Trends tab.
Click on the Interactives tab.
Locate the following link: How Census Race
Categories Have Changed Over Time
Click on "1790" to see two columns comparing the
1790 Census categories with the 2010 Census
categories.
Minimum of 4 outside scholarly sources
Instructions
In this week's lesson, you learned about the U.S. Census
Bureau's most recent racial and ethnic categories. For this
assignment, consider the racial and ethnic categories used in
the 2010 Census with the four racial, ethnic, and gender
categories used in the 1790 Census: Free white males, free
white females, all other free persons, slaves (Pew Research
Center, 2015). Analyze the concepts of race, ethnicity, and
gender as social constructs, just as sociologists do, by
addressing the following:
1. Explain how you might have been categorized by the
1790 Census and how you would have been
categorized by the 2010 Census.
2. Compare and contrast the two potential categorizations
and explain how this exercise shows that the concepts
of race, ethnicity, and even gender change over time.
Most importantly, explain how this exercise shows that
the concepts of race, ethnicity, and gender are social
constructs.
3. Determine and describe what ethnic, racial, and/or
gender categories, if any, would be best, in your view,
for the 2020 Census or the 2030 Census, to most
accurately show the diversity of the U.S. population.
What categories would be best to reveal the segments
of the U.S. population most vulnerable to racial, ethnic,
and/or gender inequalities or discrimination? What
categories could be listed in the 2020 Census or the
2030 Census that might best educate the U.S.
population on differences between race and ethnicity?
Explain your decisions.
Include headings for each of the three main sections of the
paper:
What the Census Might Have Called Me
Social Constructs
Better Future Census Categories
Each of the three main sections of your paper must contain
scholarly support in the form of quotes or paraphrases with
respective citations from assigned reading (the
textbook/lesson) and the outside scholarly source that you
identify on your own.
*This assignment is adapted from Glaser (2018).
Writing Requirements (APA format)
Length: 3-4 pages (not including references page)
1-inch margins
Double spaced
12-point Times New Roman font
Running header in the upper left of all pages
Page number in the upper right of all pages
Minimum of 3 headings (centered, bold, & title case)
Parenthe.
Data visualization & Story Telling with DataDr Nisha Arora
Storytelling with data using the appropriate visualization is a skill that is well sought-after for data-driven decision making and it spans many industries and roles (technical/non-technical).
In this presentation, we will briefly discuss the importance of understanding the context, selecting the right visuals, key points for effectively using those for storytelling, design dos, and don’ts, etc.
“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!
Leenke De Donder presentation at Meetup Big Data and Ethics at DigitYser Brus...IntoTheMinds
presentation given at the first meetup on Big Data and Ethics given at DigitYser Brussels. Find more about this event on our blog at www.intotheminds.com/blog/en
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
2. What data is…
Data needs
Design Designers
Need to have mindset to communicate it
to others
3. What data is…
Data
weird
Just like
your
undergrad
thesis
People not needing it
People are not obliged to read your work
no matter how brilliant it is
There was a disconnect between really
good analysis vs. the academia and
research institutions
Standardized
collection of
Stories
Meaning
4. How data is processed…
Data
Standardized
collection of
stories
Add context
How bad really is Kuliat Public School in
relation to other public schools?
5. Say, Schools
Rows Columns
How bad really is Kuliat Public School in
relation to other public schools?
How is it
staffed?
No. of
rooms
No. of
students
dropped out
Stories of
each school
Budget per
student
6. Say, Schools
Rows Columns
How bad really is Kuliat Public School in
relation to other public schools?
How is it
staffed?
No. of
rooms
No. of
students
dropped out
Stories of
each school
Budget per
student
How is it in relation to other populations?
7. Say, Schools
Rows Columns
How bad really is Kuliat Public School in
relation to other public schools?
Add more context to the story…
9. Looking at tweets,
Rows Columns
it reflects on how a business is run.
.. … ….
How much
they talk
about
certain
topics
Presidents
Create interesting stories…
See the bigger picture instead of one the individual story
10. Looking at tweets, it reflects on how a business is run.
Create interesting stories…
See the bigger picture instead of one the individual story
Emotion
polarity of
tweets
Air Asia Cebu Pacific PAL
11. 5 steps to story telling…
Define row/
protagonists
Define
elements of the
story
Collect data Tell the story Visualize
1 2 3 4 5
12. 5 steps to story telling…
Define row/
protagonists
1
1 2 3 4 5
Schools Country
13. 5 steps to story telling…
Define elements of the
story.
2
1 2 3 4 5
What do you want to
know of the
protagonists?
14. 5 steps to story telling…
Collect data
3
1 2 3 4 5
Define what you want
to do
15. 5 steps to story telling…
Tell the story
4
1 2 3 4 5
16. 5 steps to story telling…
Visualize
5
1 2 3 4 5
Why need this?
Builds trust
Keeps abstraction to
a minimum
Facilitates info
assessment
Beneficiaries vs.
Population of poor
areas
Cognitive overload
when reading a
table instead
17. Ways to analyze data…
Exploratory Descriptive
Inferential/
Predictive
a b c
18. Ways to analyze data…
Exploratory Descriptive
Inferential/
Predictive
a b c
Display all info available
without removing info
Leads to higher trust No bias Less control
19. Ways to analyze data…
Exploratory Descriptive
Inferential/
Predictive
a b c
Processed to show
subset of data
Less trust
Processed to make it
useful
20. Ways to analyze data…
Exploratory Descriptive
Inferential/
Predictive
a b c
Lots of control to show
audience
Making conclusions
21. Visualizing
Cartesian
Elements – deliberate design
Polar
coordinates
Points
Columns
Bars
Coordinates Geometries Aesthetics
Color
Size
Width
Shape
Mapped to a data value
Should represent
something
25. Why do this?
Filipinos have problem with
scale
Most organizations have
small windows to get to see
what people are doing.
They do well in coordination
but once it increases in size,
dysfunction settles in
Lacks trust
Lack of common
data/ info
available
Bureaucracy Nationalism
Patronage
politics
Little kingdoms Control