Infographics Key Data KPI presentation slides

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Infographics of key data values and KPIs - inspirative of creative slide design templates. Flat style diagrams and geometric shapes. Inspiration how to present a text formal data in an unique visual way. Graphics is in modern metro UI graphical style, easily redoable and editable in PowerPoint.

Données & analyses Présentations et discours publics Design

www.infoDiagram.com 2015
1
Infographics
shapes & diagrams
55% 70% 40%

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Want to present
your key data values, KPIs
in an attractive way?

www.infoDiagram.com 2015
Want to present
your key data values, KPIs
in an attractive way?
Use key data
visualization
shapes and diagrams

www.infoDiagram.com 2015
Want to present
your key data values, KPIs
in an attractive way?
Get inspired
by the following examples…
Use key data
visualization
shapes and diagrams

www.infoDiagram.com 2015
Key data presentation
diagram placeholders

www.infoDiagram.com 2015
How to show important values in creative way?
Use infographics diagrams for presenting data

www.infoDiagram.com 2015
How to show important values in creative way?
Use infographics diagrams for presenting data
“This year key performance indicators include 123 456
products in stock, with average value of package $ 2831.
We managed to process 350 000 products in total…“
Products
processed
350 000123 456
Products
in stock
$ 2831
Product package
value

www.infoDiagram.com 2015www.infoDiagram.com 2015
123 456
Data value
name
Data value
name
Data value
name
123 456 123 456
Status of …
Some other infographics placeholders for data:

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Your description of the main measure
indicator
Key Performance
Indicator measure
explanation
KPI 3KPI 1
Key Performance
Indicator measure
explanation
KPI 2
Key Performance
Indicator measure
explanation
33%
market share

www.infoDiagram.com 2015www.infoDiagram.com 2015
Clients
acquired
New
countries
covered
Corporate
clients
acquired
Profit est. in
2015
Turnover est.
in 2015
Growth
rate
3 014 15 241
$ 100 000$2 439 021
39%

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Key data 2
Key data 3
Key data 1

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55% 70% 40% 60%
Your sample
text here
Your sample
text here
Your sample
text here
Your sample
text here

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55% 70% 40% 60%
TITLE
Your sample
text here.
Your sample
text here.
TITLE
Your sample
text here.
Your sample
text here.
TITLE
Your sample
text here.
Your sample
text here.
TITLE
Your sample
text here.
Your sample
text here.

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75% 50% 25%
Your sample
text here
Your sample
text here
Your sample
text here

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70%
50%
90%
40%
Mobiles
Notebooks
Tablets
Station

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Your
sample
text here
Your
sample
text here
Your
sample
text here
Your
sample
text here
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
60%
40%
70%
90%

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Your sample text here, Your sample text here, Your
sample text here
2000 employees (HR related data)
Your sample text here, Your sample text here, Your
sample text here
30% investment in R&D
Your sample text here, Your sample text here, Your
sample text here
300 certified people
Your sample text here, Your sample text here, Your
sample text here
50 satisfied clients

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123 clients…
12 patents
4 cloud apps
Explanation of what this value means
for your business.
Data measure description.
Explanation of what this value means
for your business.
Data measure description.
Explanation of what this value means
for your business.
Data measure description.

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Your sample
text
Your sample description here. Your
sample description here.
Your sample
text
Your sample description here. Your
sample description here.
Your sample
text
Your sample description here. Your
sample description here.

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Enrich your text slides
by using infographics diagrams
to make them stand out.

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Your text Sample text
Enrich your text slides
by using infographics diagrams
to make them stand out.

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Get our free infographics
diagrams at
www.infoDiagram.com
Your text Sample text
Enrich your text slides
by using infographics diagrams
to make them stand out.

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Yilin Xia (yilinx2@illinois.edu), Shawn Bowers (bowers@gonzaga.edu), Lan Li (lanl2@illinois.edu), and Bertram Ludäscher (ludaesch@illinois.edu) Presented at IDCC-2024 in Edinburg. ABSTRACT. We propose a new approach for modeling and reconciling conflicting data cleaning actions. Such conflicts arise naturally in collaborative data curation settings where multiple experts work independently and then aim to put their efforts together to improve and accelerate data cleaning. The key idea of our approach is to model conflicting updates as a formal argumentation framework (AF). Such argumentation frameworks can be automatically analyzed and solved by translating them to a logic program PAF whose declarative semantics yield a transparent solution with many desirable properties, e.g., uncontroversial updates are accepted, unjustified ones are rejected, and the remaining ambiguities are exposed and presented to users for further analysis. After motivating the problem, we introduce our approach and illustrate it with a detailed running example introducing both well-founded and stable semantics to help understand the AF solutions. We have begun to develop open source tools and Jupyter notebooks that demonstrate the practicality of our approach. In future work we plan to develop a toolkit for conflict resolution that can be used in conjunction with OpenRefine, a popular interactive data cleaning tool.

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