Manage the big data efficiently using our big data sources PowerPoint deck. These 25 slides presentation deck gives you the access to highlight the information related to the most complex topic in the most desired manner. This PPT deck has been designed by our creative and proficient designers who have great designing skills and knowledge about the concept of big data. Our PPT deck helps you make your people understand that from where the data comes and where it gets stored. Every individual today is using one or another device to accomplish their day to day tasks but only few know how they can assure to protect their data and how it is saved in the cloud storage. To make a presentation where you have to share the information about big data sources you can use this big data sources PowerPoint deck. Some key presentation slides that are included in the deck are cloud, web, internet of things, media, databases, data warehouse appliances etc. Disprove exaggerated claims with our Big Data Sources PowerPoint Presentation Slides. Force the boastful to accept their error.

1. Big
Data
Sources
Your Company Name
1

2. 2
Media
Media is the most popular source of big data, as it
provides valuable insights on consumer
preferences & changing trends
Generic media like images, videos, audios, and
podcasts that provide quantitative and qualitative
insights on every aspect of user interaction
Media includes social media
and interactive platforms, like
Google, Facebook, Twitter,
YouTube, Instagram
www.company .com

3. Cloud
3
Text Here
The main attribute of cloud computing is its flexibility & scalability
In this era, companies have moved
ahead of traditional data sources by
shifting their data on the cloud
Cloud storage accommodates
structured & unstructured data &
provides business with real-time
information & on-demand insights.
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4. Web
4
The public web constitutes big data that is widespread & easily accessible.
Data on the Web or ‘Internet’ is commonly available to individuals &
companies alike. Moreover, web services such as Wikipedia
provide free & quick informational insights to everyone
The enormity of the Web ensures for its diverse usability
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5. Internet of Things
5
IoT is now gaining momentum and includes big data generated, not only from computers and
smartphones, but also possibly from every device that can emit data
Internet
of
Things
Machine-generated content or
data created from IoT constitute a
valuable source of big data
This data is usually generated
from the sensors that are
connected to electronic devices
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6. 6
Databases
Businesses today prefer to use an amalgamation of traditional &
modern databases to acquire relevant big data
This integration paves the way for a hybrid data model and
requires low investment and IT infrastructural costs.
These databases can then provide for the extraction of insights
that are used to drive business profits.
Popular databases include a variety of data sources, such as MS
Access, DB2, Oracle, SQL, & Amazon Simple, among others.
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attention.
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7. Social network Profiles
7
Tapping user profiles from Facebook, LinkedIn, Yahoo, Google, and specific-interest social
or travel sites, to cull individuals’ profiles and demographic information, and extend that to
capture their hopefully-like-minded networks
This requires a fairly straightforward API integration for importing
pre-defined fields and values – for example, a social network API
integration that gathers every B2B marketer on Twitter
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8. Social Influencers
8
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Editor Posts
Analyst Reports
Subject-matter Experts
Blog Comments
User forums
Twitter & Facebook “likes,”
Yelp-style catalog
Review sites
Other review-centric sites like
Apple’s App Store, Amazon,
ZDNet, etc
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9. Activity-Generated Data
9
Computer and mobile
device log files i.e. “The
Internet of Things.”
This category includes
web site tracking
information, application
logs, and sensor data –
such as check-ins and
other location tracking –
among other machine-
generated content
The data generated by the
processors found within
vehicles, video games,
cable boxes or, soon,
household appliances
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10. Data Warehouse Appliances
10
Teradata, IBM Netezza, EMC Greenplum, etc. are
collecting from operational systems the internal,
transactional data that is already prepared for analysis
These will likely become an integration target that will
assist in enhancing the parsed and reduced results from
your Big Data installation
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www.company .com

11. Big Data Sources
11
Legacy Documents
Media
Cloud
Web
Internet of
Things
Social network profiles
Social Influencers
Activity Generated
Data
Data warehouse
appliances
Network and in-stream
monitoring technologies
Databases
Big Data
Sources
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12. Network and in - Stream Monitoring Technologies
12
Packet
Evaluation
Email Parsers
Distributed Query
Processing-like
Applications
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13. Legacy Documents
13
Archives of
Statements
Insurance
Forms
Medical
Record
Customer
Correspondence
There are still multiple untapped resources. Some of them are
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14. Big Data Sources Icon Slide
14
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15. 15
Additional
Slides
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16. Combo Chart
16
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8
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10
0
10
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30
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50
60
70
80
90
100
FY' 11 FY' 12 FY' 13 FY' 14 FY' 15 FY' 16 FY' 17 FY' 18
GrowthRate(%)
MarketSize(RMB100Million)
This graph/chart is linked to excel, and changes automatically based on data. Just left click on it and select “Edit Data”. c
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17. Area Chart
17
0
10
20
30
40
50
60
70
80
90
100
2015 2016 2017 2018
Profit(InHundreds)
Product 1
Product 2
This graph/chart is linked to excel, and changes automatically based on data. Just left click on it and select “Edit Data”.
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18. Radar Chart
18
0
5
10
15
20
25
30
35
03-05-2018
05-05-2018
08-05-2018
12-04-2018
15-05-2018
17-05-2018
Product 1
Product 2
This graph/chart is linked to excel, and changes automatically based on data. Just left click on it and select “Edit Data”.
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19. Clustered Bar
19
0 10 20 30 40 50 60 70 80 90 100
Q1
Q2
Q3
Q4
Unit Count
Product 1
Product 2
Product 3
This graph/chart is linked to excel, and changes automatically based on data. Just left click on it and select “Edit Data”.
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20. 20
Our Mission
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21. 21
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Meet Our Team
Anita Parker
Web Designer
Tom Torres
Ceo
Robin Carter
Manager
Jasmin Smith
Editor
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22. www.company .com
22
About Us
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23. Comparison
23
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Male
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Female
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Minimum
40%
Medium
60%
Maximum
80%
Financial
24
www.company .com

25. www.company .com
25
# Street Number, City, State
Address:
Emailaddress123@gmail.Com
Email Address:
0123456789
Contact Number:
Thank You