BIG DATA

Kotireddykasu
3 min readSep 20, 2020
Big data tree

As the name says big data is nothing but the huge data . The bigdata could be 1.STRUCTURED

2.UNSTRUCTURED

3.SEMI-STRUCTURED

1.STRUCTURED

Any data that can be stored, accessed and processed in the form of fixed format is termed as a ‘structured’ data. Over the period of time, talent in computer science has achieved greater success in developing techniques for working with such kind of data (where the format is well known in advance) and also deriving value out of it. However, nowadays, we are foreseeing issues when a size of such data grows to a huge extent, typical sizes are being in the rage of multiple zettabytes.

EXAMPLE OF STRUCTURED DATA

2.UNSTRUCTURED

Any data with unknown form or the structure is classified as unstructured data. In addition to the size being huge, un-structured data poses multiple challenges in terms of its processing for deriving value out of it. A typical example of unstructured data is a heterogeneous data source containing a combination of simple text files, images, videos etc. Now day organizations have wealth of data available with them but unfortunately, they don’t know how to derive value out of it since this data is in its raw form or unstructured format.

EXAMPLE — if we search “mobile” in google , the google reply by displaying with many results and wide range of mobiles.

3.SEMI-STRUCTURED

Semi-structured data can contain both the forms of data. We can see semi-structured data as a structured in form but it is actually not defined with e.g. a table definition in relational DBMS. Example of semi-structured data is a data represented in an XML file.

EXAMPLE — <name>koti</name><age>20</age>

CHARACTERISTCS OF BIGDATA

(1)VOLUME — This is the major factor to be remembered while dealing with bigdata .Huge data to be used.

(2)VARIETY — Variety refers to heterogeneous sources and the nature of data, both structured and unstructured. During earlier days, spreadsheets and databases were the only sources of data considered by most of the applications. Nowadays, data in the form of emails, photos, videos, monitoring devices, PDFs, audio, etc. are also being considered in the analysis applications.

(3)VELOCITY — The term ‘velocity’ refers to the speed of generation of data .The flow of data is massive and continuous.

(4)VARIABILITY — This refers to the inconsistency which can be shown by the data at times, thus hampering the process of being able to handle and manage the data effectively.

BENEFITS OF BIG DATA PROCESSING;

Ability to process Big Data brings in multiple benefits, such as-

  • Businesses can utilize outside intelligence while taking decisions
  • Improved customer service
  • Early identification of risk to the product/services, if any
  • Better operational efficiency

MAJOR CHALLENGES IN BIG DATA

  • ELECTRICAL INFRASTRUCURE
  • POWER AND COOLING
  • DATA CENTER STORAGE
  • NETWORK
  • DATA PATTERN
  • SECURITY

referred from guru99

A NOTES ON BIGDATA

BY KASUKOTIREDDY

VIVEKANANDA GLOBAL UNIVERSITY

JAIPUR

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