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Illustrations toolbox
Volume Velocity
VeracityVariety
Social
media
Mobile
M2M
Big Data Diagrams
Copyright: infoDiagram.com
Big data is high volume,
high velocity, and/or high variety
information assets that require new
forms of processing to enable
enhanced decision making, insight
discovery and process optimization.
Doug Laney, Gartner, 2012
(@Doug_Laney)
Definition: Gartner’s 3V of Big Data
Copyright: infoDiagram.com
V V
V
Variety
Big data is high volume,
high velocity, and/or high variety
information assets that require new
forms of processing to enable
enhanced decision making, insight
discovery and process optimization.
Doug Laney, Gartner, 2012
(@Doug_Laney)
Definition: Gartner’s 3V of Big Data
Copyright: infoDiagram.com
3V of Big Data explained
Copyright: infoDiagram.com
Volume
Huge data size,
terabytes – petabytes
3V of Big Data explained
Data
Volume
Data
Variety
Data
Velocity
V
VV
Copyright: infoDiagram.com
Volume
Huge data size,
terabytes – petabytes
Velocity
High speed of data
flow, data change and
data processing
3V of Big Data explained
Data
Volume
Data
Variety
Data
Velocity
V
VV
V
VV
Copyright: infoDiagram.com
Volume
Huge data size,
terabytes – petabytes
Velocity
High speed of data
flow, data change and
data processing
Variety
Various data sources
(social, mobile, M2M,
structured and unstructured data)
3V of Big Data explained
Data
Volume
Data
Variety
Data
Velocity
V
VV
V
VV
V
VV
Copyright: infoDiagram.comCopyright: infoDiagram.com
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Just leave me a comment.
Copyright: infoDiagram.comCopyright: infoDiagram.com
This is part of IT presentations toolbox.
Your feedback is welcomed.
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presentation visuals at
infoDiagram.com
Copyright: infoDiagram.comCopyright: infoDiagram.com
Read on…
This is part of IT presentations toolbox.
Your feedback is welcomed.
Just leave me a comment.
See more
presentation visuals at
infoDiagram.com
Copyright: infoDiagram.com
Velocity
High speed of data
flow, change
and processing
Volume
Huge data size,
terabytes - petabytes
Variety
Various data sources (social,
mobile, M2M, structured
and unstructured data)
Extended definition: 4 Vs of Big Data
V V
V V
Copyright: infoDiagram.com
Velocity
High speed of data
flow, change
and processing
Volume
Huge data size,
terabytes - petabytes
Variety
Various data sources (social,
mobile, M2M, structured
and unstructured data)
Extended definition: 4 Vs of Big Data
V V
V V
Veracity
Various levels of data
uncertainty and reliability
Copyright: infoDiagram.com
Big Data Volume
• increasing data amount
• handling Terabytes – Petabytes
• 1 TB
= 1 000 000 000 000 bytes
= 1012bytes
= 1000 gigabytes
• 1 PB = 1 000 000 000 000 000 B
= 1015bytes
= 1000 terabytes
4 Vs of Big Data: Volume
Volume Velocity
VeracityVariety
Copyright: infoDiagram.com
Velocity of data processing
Need to process data in a fast way,
considering their huge amount (TB, PB)
and variety (distributed, mix of structured
and unstructured data)
E.g.
• Searching Twitter posts
• Fast analysis of video streams (Youtube),
• Image recognition (real-time augmented
reality, online photo faces recognition),
• Sound analysis (speech recognition)
• Text analysis (Internet search)
4 Vs of Big Data: Velocity
Volume Velocity
VeracityVariety
Copyright: infoDiagram.com
Huge variety of big data
• Data from various data sources
• Social media (Facebook, Twitter)
• Mobile data (location, texting)
• Machine to Machine systems
(GPS, logs, RFID…)
• Database systems
• Handling various data types
• Structured
• records in databases (customers,
billing, stock exchange data…),
Machine logs
• Unstructured
• free text, video, sounds
4 Vs of Big Data: Variety
Volume Velocity
VeracityVariety
Social
media
Mobile
M2M
Copyright: infoDiagram.com
Veracity of big data
Various data uncertainty and reliability
• Imprecision of data (especially of
unstructured data – e.g. text message can
have double meaning)
• Different level of data quality of structured
data (data values are certain and precise)
and unstructured data (fuzzy interpreting
of images, free text, speech wording …)
• Technical data quality issues (various
formats, source availability, updates)
4 Vs of Big Data: Veracity
Volume Velocity
VeracityVariety
Copyright: infoDiagram.com
Big Data: Application areas
Big Data
Applications
Copyright: infoDiagram.com
Big Data: Application areas
Big Data
Applications
Banks
& Insurance
Copyright: infoDiagram.com
Big Data: Application areas
Big Data
Applications
Banks
& Insurance
Healtcare
& Research
Copyright: infoDiagram.com
Big Data: Application areas
Big Data
Applications
Banks
& Insurance
Healtcare
& Research
Telco
Copyright: infoDiagram.com
Big Data: Application areas
Big Data
Applications
Banks
& Insurance
Healtcare
& Research
Telco
Energy
& Utilities
Copyright: infoDiagram.com
Big Data: Application areas
Big Data
Applications
Banks
& Insurance
Healtcare
& Research
Telco
Energy
& Utilities
Automotive
production
Copyright: infoDiagram.com
Big Data: Application areas
Big Data
Applications
Banks
& Insurance
Healtcare
& Research
Telco
Energy
& Utilities
Automotive
production
Retail
Copyright: infoDiagram.com
Big Data Opportunities & Infrastructure
Business Opportunities
Technology Infrastructure
Big Data
Copyright: infoDiagram.com
Business Opportunities
Big Data Opportunities & Infrastructure
HardwareSoftware
Technology Infrastructure
Big Data
Copyright: infoDiagram.com
Big Data Opportunities & Infrastructure
HardwareSoftware
New products Cheaper operations
Business Opportunities
Technology Infrastructure
Big Data
Copyright: infoDiagram.com
Business Opportunities of Big Data
New products Cheaper operations
Business Opportunities
Big Data
Localization
services
Mobile
services
Social media
services
Augmented
reality
Realtime
information
…
Copyright: infoDiagram.com
Business Opportunities of Big Data
New products Cheaper operations
Business Opportunities
Big Data
IT in the cloud
(e.g. salesforce.com,
Google docs, Microsoft
Office 365…)
Copyright: infoDiagram.com
Technology Infrastructure of Big Data
HardwareSoftware
Technology Infrastructure
Big Data
Data Analytics &
Visualizations, BI
• Qlikview, Tableau,
SAS, GoodData …
Databases
• Oracle, IBM, Cloudera,
HortonWorks, EMC2,
AWS, Windows Azure
Technologies
• Hadoop
• MapReduce
• NoSQL
• Apache HBase
Copyright: infoDiagram.com
Big Data: Technology areas
Big
Data
Copyright: infoDiagram.com
Big Data: Technology areas
Cloud
apps
& tech
Big
Data
Copyright: infoDiagram.com
Big Data: Technology areas
Cloud
apps
& tech
SaaS
Software as a
Service
Big
Data
Copyright: infoDiagram.com
Examples Characteristics Typical tools
Analytical
methods
Small Data
(megabytes)
Sales records,
Customers
database (small
and medium
companies)
Hundreds –
thousands of
records
Personal computer,
Excel, R, other
basic statistics
software
Simple statistics
Data sizes
Examples Characteristics Typical tools
Analytical
methods
Copyright: infoDiagram.com
Examples Characteristics Typical tools
Analytical
methods
Small Data
(megabytes)
Sales records,
Customers
database (small
and medium
companies)
Hundreds –
thousands of
records
Personal computer,
Excel, R, other
basic statistics
software
Simple statistics
Large Data
(gigabytes-
terabytes)
Customer
databases (big
companies)
Millions of records,
mostly structured
data
Server workstation
computer,
Relational
database systems,
data warehouses
Advanced
statistics, business
intelligence, data
mining,
Data sizes
Examples Characteristics Typical tools
Analytical
methods
Copyright: infoDiagram.com
Examples Characteristics Typical tools
Analytical
methods
Small Data
(megabytes)
Sales records,
Customers
database (small
and medium
companies)
Hundreds –
thousands of
records
Personal computer,
Excel, R, other
basic statistics
software
Simple statistics
Large Data
(gigabytes-
terabytes)
Customer
databases (big
companies)
Millions of records,
mostly structured
data
Server workstation
computer,
Relational
database systems,
data warehouses
Advanced
statistics, business
intelligence, data
mining,
Big Data
(terabytes –
petabytes)
Customer
interactions (social
media, mobile),
multimedia (video,
images, free text),
location-based
data, RFIM
Over millions of
records,
distributed,
unstructured
Cloud, data
centers,
Distributed
databases, NoSQL,
Hadoop
MapReduce,
Distributed File
Systems
Data sizes
Examples Characteristics Typical tools
Analytical
methods
Copyright: infoDiagram.comCopyright: infoDiagram.com
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on Big Data
topics?
Copyright: infoDiagram.comCopyright: infoDiagram.com
Presenting
on Big Data
topics?
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Big Data Visuals
PPT Toolbox
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Big Data Diagrams and Visuals Toolbox infodiagram PPT

  • 1. Copyright: infoDiagram.comCopyright: infoDiagram.com Illustrations toolbox Volume Velocity VeracityVariety Social media Mobile M2M Big Data Diagrams
  • 2. Copyright: infoDiagram.com Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization. Doug Laney, Gartner, 2012 (@Doug_Laney) Definition: Gartner’s 3V of Big Data
  • 3. Copyright: infoDiagram.com V V V Variety Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization. Doug Laney, Gartner, 2012 (@Doug_Laney) Definition: Gartner’s 3V of Big Data
  • 4. Copyright: infoDiagram.com 3V of Big Data explained
  • 5. Copyright: infoDiagram.com Volume Huge data size, terabytes – petabytes 3V of Big Data explained Data Volume Data Variety Data Velocity V VV
  • 6. Copyright: infoDiagram.com Volume Huge data size, terabytes – petabytes Velocity High speed of data flow, data change and data processing 3V of Big Data explained Data Volume Data Variety Data Velocity V VV V VV
  • 7. Copyright: infoDiagram.com Volume Huge data size, terabytes – petabytes Velocity High speed of data flow, data change and data processing Variety Various data sources (social, mobile, M2M, structured and unstructured data) 3V of Big Data explained Data Volume Data Variety Data Velocity V VV V VV V VV
  • 8. Copyright: infoDiagram.comCopyright: infoDiagram.com This is part of IT presentations toolbox. Your feedback is welcomed. Just leave me a comment.
  • 9. Copyright: infoDiagram.comCopyright: infoDiagram.com This is part of IT presentations toolbox. Your feedback is welcomed. Just leave me a comment. See more presentation visuals at infoDiagram.com
  • 10. Copyright: infoDiagram.comCopyright: infoDiagram.com Read on… This is part of IT presentations toolbox. Your feedback is welcomed. Just leave me a comment. See more presentation visuals at infoDiagram.com
  • 11. Copyright: infoDiagram.com Velocity High speed of data flow, change and processing Volume Huge data size, terabytes - petabytes Variety Various data sources (social, mobile, M2M, structured and unstructured data) Extended definition: 4 Vs of Big Data V V V V
  • 12. Copyright: infoDiagram.com Velocity High speed of data flow, change and processing Volume Huge data size, terabytes - petabytes Variety Various data sources (social, mobile, M2M, structured and unstructured data) Extended definition: 4 Vs of Big Data V V V V Veracity Various levels of data uncertainty and reliability
  • 13. Copyright: infoDiagram.com Big Data Volume • increasing data amount • handling Terabytes – Petabytes • 1 TB = 1 000 000 000 000 bytes = 1012bytes = 1000 gigabytes • 1 PB = 1 000 000 000 000 000 B = 1015bytes = 1000 terabytes 4 Vs of Big Data: Volume Volume Velocity VeracityVariety
  • 14. Copyright: infoDiagram.com Velocity of data processing Need to process data in a fast way, considering their huge amount (TB, PB) and variety (distributed, mix of structured and unstructured data) E.g. • Searching Twitter posts • Fast analysis of video streams (Youtube), • Image recognition (real-time augmented reality, online photo faces recognition), • Sound analysis (speech recognition) • Text analysis (Internet search) 4 Vs of Big Data: Velocity Volume Velocity VeracityVariety
  • 15. Copyright: infoDiagram.com Huge variety of big data • Data from various data sources • Social media (Facebook, Twitter) • Mobile data (location, texting) • Machine to Machine systems (GPS, logs, RFID…) • Database systems • Handling various data types • Structured • records in databases (customers, billing, stock exchange data…), Machine logs • Unstructured • free text, video, sounds 4 Vs of Big Data: Variety Volume Velocity VeracityVariety Social media Mobile M2M
  • 16. Copyright: infoDiagram.com Veracity of big data Various data uncertainty and reliability • Imprecision of data (especially of unstructured data – e.g. text message can have double meaning) • Different level of data quality of structured data (data values are certain and precise) and unstructured data (fuzzy interpreting of images, free text, speech wording …) • Technical data quality issues (various formats, source availability, updates) 4 Vs of Big Data: Veracity Volume Velocity VeracityVariety
  • 17. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications
  • 18. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance
  • 19. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research
  • 20. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco
  • 21. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco Energy & Utilities
  • 22. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco Energy & Utilities Automotive production
  • 23. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco Energy & Utilities Automotive production Retail
  • 24. Copyright: infoDiagram.com Big Data Opportunities & Infrastructure Business Opportunities Technology Infrastructure Big Data
  • 25. Copyright: infoDiagram.com Business Opportunities Big Data Opportunities & Infrastructure HardwareSoftware Technology Infrastructure Big Data
  • 26. Copyright: infoDiagram.com Big Data Opportunities & Infrastructure HardwareSoftware New products Cheaper operations Business Opportunities Technology Infrastructure Big Data
  • 27. Copyright: infoDiagram.com Business Opportunities of Big Data New products Cheaper operations Business Opportunities Big Data Localization services Mobile services Social media services Augmented reality Realtime information …
  • 28. Copyright: infoDiagram.com Business Opportunities of Big Data New products Cheaper operations Business Opportunities Big Data IT in the cloud (e.g. salesforce.com, Google docs, Microsoft Office 365…)
  • 29. Copyright: infoDiagram.com Technology Infrastructure of Big Data HardwareSoftware Technology Infrastructure Big Data Data Analytics & Visualizations, BI • Qlikview, Tableau, SAS, GoodData … Databases • Oracle, IBM, Cloudera, HortonWorks, EMC2, AWS, Windows Azure Technologies • Hadoop • MapReduce • NoSQL • Apache HBase
  • 30. Copyright: infoDiagram.com Big Data: Technology areas Big Data
  • 31. Copyright: infoDiagram.com Big Data: Technology areas Cloud apps & tech Big Data
  • 32. Copyright: infoDiagram.com Big Data: Technology areas Cloud apps & tech SaaS Software as a Service Big Data
  • 33. Copyright: infoDiagram.com Examples Characteristics Typical tools Analytical methods Small Data (megabytes) Sales records, Customers database (small and medium companies) Hundreds – thousands of records Personal computer, Excel, R, other basic statistics software Simple statistics Data sizes Examples Characteristics Typical tools Analytical methods
  • 34. Copyright: infoDiagram.com Examples Characteristics Typical tools Analytical methods Small Data (megabytes) Sales records, Customers database (small and medium companies) Hundreds – thousands of records Personal computer, Excel, R, other basic statistics software Simple statistics Large Data (gigabytes- terabytes) Customer databases (big companies) Millions of records, mostly structured data Server workstation computer, Relational database systems, data warehouses Advanced statistics, business intelligence, data mining, Data sizes Examples Characteristics Typical tools Analytical methods
  • 35. Copyright: infoDiagram.com Examples Characteristics Typical tools Analytical methods Small Data (megabytes) Sales records, Customers database (small and medium companies) Hundreds – thousands of records Personal computer, Excel, R, other basic statistics software Simple statistics Large Data (gigabytes- terabytes) Customer databases (big companies) Millions of records, mostly structured data Server workstation computer, Relational database systems, data warehouses Advanced statistics, business intelligence, data mining, Big Data (terabytes – petabytes) Customer interactions (social media, mobile), multimedia (video, images, free text), location-based data, RFIM Over millions of records, distributed, unstructured Cloud, data centers, Distributed databases, NoSQL, Hadoop MapReduce, Distributed File Systems Data sizes Examples Characteristics Typical tools Analytical methods
  • 37. Copyright: infoDiagram.comCopyright: infoDiagram.com Presenting on Big Data topics? Check our Big Data Visuals PPT Toolbox (click here to see full set at infoDiagram.com)
  • 38. Copyright: infoDiagram.comCopyright: infoDiagram.com Follow us on Slideshare for more presentations, hit FOLLOW on slideshare.net/infodiagramFollow Suggestions? Cooperation? Contact us www.infoDiagram.com twitter: @infoDiagram
  • 39. Copyright: infoDiagram.comCopyright: infoDiagram.com Follow us on Slideshare for more presentations, hit FOLLOW on slideshare.net/infodiagramFollow Suggestions? Cooperation? Contact us www.infoDiagram.com twitter: @infoDiagram Try free sample of editable PPT graphics