An Introduction to Big Data Concepts and Terminology
An Introduction to Big Data Concepts and Terminology
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What is Big Data?
Big Data is also data but with a huge size.
Big Data is a term used to describe a collection of data that is huge in volume and yet growing exponentially with time.
In short such data is so large and complex that none of the traditional data management tools are able to store it or process it efficiently.
Types Of Big Data
BigData’ could be found in three forms:
Structured
Unstructured
Semi-structured
Structured
Any data that can be stored, accessed and processed in the form of fixed format is termed as a ‘structured’ data.
Examples Of Structured Data
An ‘Employee’ table in a database is an example of Structured Data
Employee_ID Employee_Name Gender Department Salary_In_lacs
2365 Male Finance 650000
3398 Female Admin 650000
7465 Male Admin 500000
7500 Male Finance 500000
7699 Female Finance 550000
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
Examples Of Un-structured Data
The output returned by ‘Google Search’
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.
Examples Of Semi-structured Data
Personal data stored in an XML file-
Characteristics Of Big Data
(i) Volume – The name Big Data itself is related to a size which is enormous. Size of data plays a very crucial role in determining value out of data.
(ii) Variety – The next aspect of Big Data is its variety.Variety refers to heterogeneous sources and the nature of data, both structured and unstructured.
(iii) Velocity – The term ‘velocity’ refers to the speed of generation of data. How fast the data is generated and processed to meet the demands, determines real potential in the data.
(iv) 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
Businesses can utilize outside intelligence while taking decisions
Improved customer service
Early identification of risk to the product/services, if any
Better operational efficiency
Big Data is defined as data that is huge in size. Bigdata is a term used to describe a collection of data that is huge in size and yet growing exponentially with time.
Examples of Big Data generation includes stock exchanges, social media sites, jet engines, etc.
Big Data could be 1) Structured, 2) Unstructured, 3) Semi-structured
Volume, Variety, Velocity, and Variability are few Characteristics of Bigdata
Improved customer service, better operational efficiency, Better Decision Making are few advantages of Bigdata
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