How to create a Poster Presentation1What is a poster

How to create a Poster Presentation
1
What is a poster presentation?
A poster presentation is a visual communication tool.
People can present their work, ideas, research work, advertised
products, etc.
Such practises are highly used in professional settings.
Hess, Tosney, & Liegel (2009)
2
What is a poster presentation?
A poster is a condensed version of a written work.
It is primarily conducted with visual displays of data.
Includes the most important information from your work.
It summarizes the sections of your work therefore, needs to be
split into similar sections accordingly.
3
Tips for effective poster development
The most important thing is the poster's title.
Use large text for the title
Do not use all capital letters in the title
Below the title, add the author(s) name
The body of the poster needs to be short, use declarative
sentences to explain the main findings, highlighting why it

matters.
The methods section should be limited.
Emphasize graphics (e.g., charts, graphs and pictures) in order
to make
your poster easier to understand.
4
Tips for effective poster development
Remember to choose colors wisely. Simple is better and
stay with 2-3 colours that contrast nicely with the
background.
White space is important. Leaving space between the sections of
the poster help the audience to read the poster more easily.
7. Use a font size that is large enough and contrasts with the
background.
Never use dark backgrounds.
5
Additional Tips for effective poster development
Symmetry is important (e.g. if you add a graph on the top right,
try to add another on the bottom left).
Design your information in columns that follow a logic order
(introduction, main body, conclusion). You can add numbers to
your sections and include simple flowchart marks to help the
reader follow your work.

Mind the details. Include your full contact information
(university’s name, etc.)
6
Additional Tips for effective poster development
You can use bullet or punctuate section headers
Use italics and not underlining
Use single spacing throughout the poster
Remember that the reader may not be familiar with the topic.
Define difficult terminology.
7
8
TITLE OF THE PAPER
NAME OF THE AUTHOR(S)
INTRODUCTION
AND
METHOD
RESULTS
TABLE
GRAPHS
IMAGES
DISCUSSION
CONCLUSION
Example: Poster Layout

9
Final Steps of Effective Poster Preparation
The text should not be more than 300-400 words
Format the type (consistent style, group sections appropriately)
(tip: use left justification for your text)
Prepare graphs, tables images, etc.
Design the poster’s layout
Choose the colours
Proofread your written text.
10
How to create a Poster in Power Point
1. Open a PowerPoint document
2. Go to DESIGN- PAGE SETUP
3. You can set the dimensions you like for your poster
4. To add colors and background, go to DESIGN, then
BACKGROUND STYLES, and then FORMAT BACKGROUND
5. When selecting a color for your background, remember that
light is best. Avoid using a very bright or dark backgro und.You
will start with two boxes on your slide. The long rectangular
box can be moved to the top to accommodate your title.
11
How to create a Poster in Power Point
7. To add more boxes, go to INSERT-TEXT BOX. You can
drag your box
around until you have it where you want it and then re-
size it. You
might want to start with 5 boxes: one for your title, one
for your
intro, one for methods, one for results, and one for your

discussion.
You can add a chart or graph to your presentation by clicking in
a box and going to INSERT-CHART. From here you can also
insert relevant pictures or clip art.
When you need to cite information on your poster, it is easier to
write your citations in a regular word document and then copy
the text into a text box. The font for this can be significantly
smaller. If you cite a photo, it’s easier to drag the text box just
under the photo.
Remember to include a text box for the References in your
paper.
12
How to create a Poster in Microsoft Word
1. Open Microsoft Office, and go to BLANK PAGE SIZES
2. To customize your poster size, go to PAGE SETUP and type
in the size in inches. Posters cannot be larger than 48 inches by
48 inches.
3. To set margins, click “Margins” and determine the size of
margins you need to ensure a professional looking poster.
4. To insert a Text Box, click the “Insert” tab. Then click the
Text Box icon. You can resize the Textbox and then type in
your content into the box or copy and paste text from another
document.
5. You can add pictures and graphs by clicking in a box and
going to INSERT-CHART.
6. To set up your background, go to the Page Design tab and
then click BACKGROUND.
13
How to create a Poster in Microsoft Word
7. To add a graph or chart, click in your text box, then go to
INSERT OBJECT. Click “Create New” and choose the format
you’d like you to use. You can then design your own chart.

8. Include a section for references.
14
Suggested Reading
Hess, G. R., Tosney, K. W., & Liegel, L. H. (2009). Creating
effective poster presentations: AMEE Guide no. 40. Medical
teacher, 31(4), 319-321.
http://www.tandfonline.com/doi/abs/10.1080/014215909028251
31
The International Honor Society in Psychology. ( 2013).
Creating an effective Conference Presentation. Retrieved from
https://www.psichi.org/?page=042EyeWin00cKarlin&hhSearchT
erms=%22poster+and+presentations%22#.WA_TkuB961s
15
BCO216 · Managing Information Systems Task brief &
rubrics Final Assignment Fall 2021
Task
The student will have to answer 3 open questions and work on a
case study and answer its 5 questions by himself without
employing copy and paste practices or
working in teams. Cover sheet, table of content and in-text
References and Bibliography are expected and will be graded.
The work needs to be converted into a pdf file before uploading

to the submission point in Moodle.
Questions
1. Explain in your own words what a Filter Bubble is. How can
that lead to a ‘Web of One’?
2. List at least 5 different AI systems from ‘simplest’ to most
developed. Explain at least one business application for
everyone. Include in every explanation
a challenge the system faces.
3. Digital systems are more and better connected as
development progresses. Users and businesses have increasingly
remote access to all kinds of data.
a. List at least 3 challenges to privacy and best practices to
mitigate the threats.
b. List at least 3 challenges to security and best practices to
prevent security breaches.
Case Study Big Data · Big Data – Big Rewards
Today’s companies are dealing with an avalanche of data from
social media, search, and sensors as well as from traditional
sources. In 2012, the amount of
digital information generated is expected to reach 988 exabytes,
which is the equivalent to a stack of books from the sun to the
planet Pluto and back. Making

sense of “big data” has become one of the primary challenges
for corporations of all shapes and sizes, but it also rep-resents
new opportunities. How are
companies currently taking advantage of big data opportunities?
The British Library had to adapt to handle big data. Every year
visitors to the British Library Web
site perform over 6 billion searches, and the library is also
responsible for preserving British Web sites that no longer exist
but need to be preserved for historical
purposes, such as the Web sites for past politicians. Traditional
data management methods proved inadequate to archive millions
of these Web pages, and
legacy analytic tools couldn’t extract useful knowledge from
such quantities of data. So, the British Library partnered with
IBM to implement a big data solution
to these challenges. IBM Big Sheets is an insight engine that
helps extract, annotate, and visually analyze vast amounts of
unstructured Web data, delivering the
results via a Web browser. For example, users can see search
results in a pie chart. IBM Big Sheets is built atop the Hadoop
framework, so it can process large
amounts of data quickly and efficiently. State and federal law
enforcement agencies are analyzing big data to discover hidden
patterns in criminal activity such as
correlations between time, opportunity, and organizations, or
non-obvious relationships (see Chapter 4) between individuals
and criminal organizations that

would be difficult to uncover in smaller data sets. Criminals and
criminal organizations are increasingly using the Internet to
coordinate and perpetrate their
crimes. New tools allow agencies to analyze data from a wide
array of sources and apply analytics to predict future crime
patterns. This means that law
enforcement can become more proactive in its efforts to fight
crime and stop it before it occurs. In New York City, the Real
Time Crime Center data warehouse
contains millions of data points on city crime and criminals.
IBM and the New York City Police Department (NYPD)worked
together to create the warehouse,
which contains data on over 120 mil-lion criminal complaints,
31 million national crime records, and 33 billion public records.
The system’s search capabilities
allow the NYPD to quickly obtain data from any of these data
sources. Information on criminals, such as a suspect’s photo
with details of past offenses or
addresses with maps, can be visualized in seconds on a video
wall or instantly relayed to officers at a crime scene. Other
organizations are using the data to go
green, or, in the case of Vestas, to go even greener.
Headquartered in Denmark, Vestas is the world’s largest wind
energy company, with over 43,000 wind
turbines across 66 countries. Location data are important to
Vestas so that it can accurately place its turbines for optimal

wind power generation. Areas without
enough wind will not generate the necessary power, but areas
with too much wind may
damage the turbines. Vestas relies on location-based data to
determine the best spots to install their turbines. To gather data
on prospective turbine locations,
Vestas’ wind library combines data from global weather systems
along with data from existing turbines. The company’s previous
wind library provided
information in a grid pattern, with each grid measuring 27 x 27
kilometers (17 x 17 miles). Vestas’ engineers were able to bring
the resolution down to about 10 x
10meters (32 x 32 feet) to establish the exact wind flow pattern
at a particular location. To further increase the accuracy of its
turbine placement models, Vestas
needed to shrink the grid area even more, and this required 10
times as much data as the previous system and a more powerful
data management platform. The
company implemented a solution consisting of IBM Info Sphere
Big Insights software running on a high-performance IBM
System x iDataPlex server. (Info Sphere
Big Insights is a set of software tools for big data analysi s and
visualization and is powered by Apache Hadoop.) Using these
technologies, Vestas increased the
size of its wind library and is able manage and analyze location
and weather data with models that are much more powerful and
precise. Vestas’ wind library

currently stores 2.8 petabytes of data and includes
approximately 178parameters, such as barometric pressure,
humidity, wind direction, temperature, wind
velocity, and other company historical data. Vestas plans to add
global deforestation metrics, satellite images, geospatial data,
and data on phases of the moon
and tides. The company can now reduce the resolution of its
wind data grids by nearly 90 percent, down to a 3 x 3 kilometer
area (about 1.8 x 1.8 miles). This
capability enables Vestas to forecast optimal turbine placement
in 15 minutes instead of three weeks, saving a month of
development time for a turbine site and
enabling Vestas customers to achieve a return on investment
much more quickly. Companies are also using big data solutions
to analyze consumer sentiment.
For example, car-rental giant Hertz gathers data from Web
surveys, e-mails, text messages, Web site traffic patterns, and
data generated at all of Hertz’s 8,300
locations in 146 countries. The company now stores all of that
data centrally instead of within each branch, reducing time
spent processing data and improving
company response time to customer feedback and changes in
sentiment. For example, by analyzing data generated from
multiple sources, Hertz was able to
determine that delays were occurring for returns in Philadelphia
during specific times of the day. After investigating this
anomaly, the company was able to

quickly adjust staffing levels at its Philadelphia office during
those peak times, ensuring a manager was present to resolve any
issues. This enhanced Hertz’s
performance and increased customer satisfaction. There are
limits to using big data. Swimming in numbers doesn’t
necessarily mean that the right information is
being collected or that people will make smarter decisions. Last
year, a McKinsey Global Institute report cautioned there is a
shortage of specialists who can
make sense of all the information being generated.
Nevertheless, the trend towards big data shows no sign of
slowing down; in fact, it’s much more likely that
big data is only going to get bigger.
Sources: Samuel Greengard,” Big Data Unlocks Business
Value,” Baseline, January 2012; Paul S. Barth, “Managing Big
Data: What Every CIO Needs to Know,” CIO
Insight, January 12, 2012; IBM Corporation, “Vestas: Turning
Climate into Capital with Big Data,” 2011; IBM Corporation,
“Extending and enhancing law
enforcement capabilities,” “How Big Data Is Giving Hertz a Big
Advantage,” and “British Library and J Start Team Up to
Archive the Web,” 2010

Case Study Questions:
1. Describe the kinds of big data collected by the organizations
described in this case.
2. List and describe the business intelligence technologies
described in this case.
3. Why did the companies described in this case need to
maintain and analyze big data? What business benefits did they
obtain?
4. Identify three decisions that were improved by using big
data.
5. What kinds of organizations are most likely to need big data
management and analytical tools? Why?
Formalities:
• Wordcount: 1200 - 1500
• Cover, Table of Contents, References and Appendix are
excluded of the total wordcount.
• Font: Arial 12,5 pts.
• Text alignment: Justified.
• The in-text References and the Bibliography must be in
Harvard’s citation style.
Submission: Week 13 · Sunday January 16th 23.59 CEST – PDF

file Via Moodle (Turnitin).
Weight: This task is a 40% of your total grade for this subject.
It assesses the following learning outcomes:
• Understand what Big Data, Data Mining and Inference Engines
are, and how it can support any business model.
• Understand the basic functioning of AI and its implications.
• Know the elemental threats to privacy and security in IS and
how to prevent or mitigate.
Rubrics
Exceptional 90-100 Good 80-89 Fair 70-79 Marginal fail 60-69
Knowledge &
Understanding
(30%)
Student demonstrates
excellent understanding of
key concepts and uses
vocabulary in an entirely
appropriate manner.
Student demonstrates

good understanding of the
task and mentions some
relevant concepts and
demonstrates use of the
relevant vocabulary.
Student understands the
task and provides minimum
theory and/or some use of
vocabulary.
Student understands the task
and attempts to answer the
question but does not
mention key concepts or uses
minimum amount of relevant
vocabulary.
Application (30%) Student applies fully
relevant knowledge from
the topics delivered in
class.
Student applies mostly
class.
Student applies some
class. Misunderstanding
may be evident.
Student applies little relevant
knowledge from the topics

delivered in class.
Misunderstands are evident.
Critical Thinking
(30%)
Student critically assesses
in excellent ways, drawing
outstanding conclusions
from relevant authors.
Student critically assesses
in good ways, drawing
conclusions from relevant
authors and references.
Student provides some
insights but stays on the
surface of the topic.
References may not be
relevant.
Student makes little or none
critical thinking insights, does
not quote appropriate
authors, and does not
provide valid sources.
Communication
(10%)
Student communicates
their ideas extremely
clearly and concisely,
respecting word count,
grammar and spellcheck

their ideas clearly and
concisely, respecting word
count, grammar and
spellcheck
their ideas with some
clarity and concision. It
may be slightly over or
under the wordcount limit.
Some misspelling errors
may be evident.
Student communicates their
ideas in a somewhat unclear
and unconcise way. Does not
reach or does exceed
wordcount excessively and
misspelling errors are
evident.

How to create a Poster Presentation1What is a poster

Recommended

Recommended

More Related Content

More from LizbethQuinonez813

More from LizbethQuinonez813 (20)

How to create a Poster Presentation1What is a poster