Skip to main content

Data Discovery and Analysis Patterns

  • Chapter
  • First Online:
Big Data Application Architecture Q & A
  • 3197 Accesses

Abstract

Big data analysis is different from traditional analysis as it involves a lot of unstructured, non RDBMS types of data. This type of analysis is usually related to text analytics, natural language processing. Areas like video and image analytics are still evolving. Big data analysis attempts to interpret and find insightful patterns in the customer behavior that perhaps the sales force already had some idea about, but did not have the data to support it. Big data analysis methods are used to analyze social media interactions, bank transactions for fraud patterns, customer sentiments for online product purchases, etc. Let’s look at some patterns that may help discover and analyze this unstructured data.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 44.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Nitin Sawant

About this chapter

Cite this chapter

Sawant, N., Shah, H. (2013). Data Discovery and Analysis Patterns. In: Big Data Application Architecture Q & A. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4302-6293-0_6

Download citation

Publish with us

Policies and ethics