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Big Data Diagrams and Visuals Toolbox infodiagram PPT

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Big Data diagrams and icons visuals:
- Big Data definition 3V, 4V: Volume, Velocity, Variety, Veracity
- Big Data New Business Opportunities: Mobile, Social media ...
- Big Data Technologies: Software and Hardware
- Data sizes table: Small, Large, Big data

Published in: Data & Analytics, Technology
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Big Data Diagrams and Visuals Toolbox infodiagram PPT

  1. 1. Copyright: infoDiagram.comCopyright: infoDiagram.com Illustrations toolbox Volume Velocity VeracityVariety Social media Mobile M2M Big Data Diagrams
  2. 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. 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. 4. Copyright: infoDiagram.com 3V of Big Data explained
  5. 5. Copyright: infoDiagram.com Volume Huge data size, terabytes – petabytes 3V of Big Data explained Data Volume Data Variety Data Velocity V VV
  6. 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. 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. 8. Copyright: infoDiagram.comCopyright: infoDiagram.com This is part of IT presentations toolbox. Your feedback is welcomed. Just leave me a comment.
  9. 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. 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. 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. 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. 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. 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. 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. 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. 17. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications
  18. 18. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance
  19. 19. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research
  20. 20. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco
  21. 21. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco Energy & Utilities
  22. 22. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco Energy & Utilities Automotive production
  23. 23. Copyright: infoDiagram.com Big Data: Application areas Big Data Applications Banks & Insurance Healtcare & Research Telco Energy & Utilities Automotive production Retail
  24. 24. Copyright: infoDiagram.com Big Data Opportunities & Infrastructure Business Opportunities Technology Infrastructure Big Data
  25. 25. Copyright: infoDiagram.com Business Opportunities Big Data Opportunities & Infrastructure HardwareSoftware Technology Infrastructure Big Data
  26. 26. Copyright: infoDiagram.com Big Data Opportunities & Infrastructure HardwareSoftware New products Cheaper operations Business Opportunities Technology Infrastructure Big Data
  27. 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. 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. 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. 30. Copyright: infoDiagram.com Big Data: Technology areas Big Data
  31. 31. Copyright: infoDiagram.com Big Data: Technology areas Cloud apps & tech Big Data
  32. 32. Copyright: infoDiagram.com Big Data: Technology areas Cloud apps & tech SaaS Software as a Service Big Data
  33. 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. 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. 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
  36. 36. Copyright: infoDiagram.comCopyright: infoDiagram.com Presenting on Big Data topics?
  37. 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. 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. 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

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