Which Of The Following Is A Characteristic Of A Service? Quizlet

Earlier nosotros go to introduction to Big Data, you offset need to know

What is Data?

The quantities, characters, or symbols on which operations are performed by a reckoner, which may be stored and transmitted in the class of electric signals and recorded on magnetic, optical, or mechanical recording media.

Now, let'south learn Big Data definition

What is Big Data?

Big Information is a drove of data that is huge in book, yet growing exponentially with fourth dimension. It is a information with so large size and complexity that none of traditional information direction tools can store information technology or process it efficiently. Large information is too a data but with huge size.

In this Big Data analytics tutorial, you lot will learn,

What is Data?
What is Large Data?
What is an Example of Big Information?
Types Of Big Data
Characteristics Of Big Information
Advantages Of Big Data Processing

What is an Example of Large Data?

Post-obit are some of the Big Data examples-

TheNew York Stock Exchange is an example of Big Information that generates about one terabyte of new trade data per solar day.

Example of Big Data

Social Media

The statistic shows that 500+terabytes of new data get ingested into the databases of social media siteFacebook, every day. This information is mainly generated in terms of photo and video uploads, bulletin exchanges, putting comments etc.

Example of Big Data

A singleJet engine tin generate 10+terabytes of data in thirty minutes of flight time. With many grand flights per day, generation of data reaches up to many Petabytes.

Example of Big Data

Types Of Large Information

Post-obit are the types of Large Data:

Structured
Unstructured
Semi-structured

Structured

Any information that tin can be stored, accessed and candy in the form of fixed format is termed as a 'structured' information. Over the period of time, talent in computer scientific discipline has accomplished 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 information technology. 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.

Do y'all know? x²¹ bytes equal to 1 zettabyte or one billion terabytes forms a zettabyte .

Looking at these figures one can easily empathise why the name Big Data is given and imagine the challenges involved in its storage and processing.

Do you lot know? Information stored in a relational database management system is 1 example of a'structured' information.

Examples Of Structured Data

An 'Employee' table in a database is an case of Structured Information

Employee_ID	Employee_Name	Gender	Section	Salary_In_lacs
2365	Rajesh Kulkarni	Male	Finance	650000
3398	Pratibha Joshi	Female person	Admin	650000
7465	Shushil Roy	Male person	Admin	500000
7500	Shubhojit Das	Male	Finance	500000
7699	Priya Sane	Female	Finance	550000

Unstructured

Any information 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 information 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 information is in its raw form or unstructured format.

Examples Of Un-structured Data

The output returned by 'Google Search'

Semi-structured

Semi-structured data can contain both the forms of data. Nosotros tin see semi-structured data every bit a structured in course just it is really not defined with e.g. a table definition in relational DBMS. Instance of semi-structured data is a data represented in an XML file.

Examples Of Semi-structured Information

Personal information stored in an XML file-

<rec><proper name>Prashant Rao</name><sex>Male person</sex><age>35</historic period></rec> <rec><name>Seema R.</name><sexual activity>Female</sex><age>41</age></rec> <rec><proper name>Satish Mane</name><sex>Male</sexual practice><age>29</age></rec> <rec><proper noun>Subrato Roy</name><sex>Male</sex><age>26</historic period></rec> <rec><name>Jeremiah J.</proper noun><sex>Male</sex><age>35</age></rec>

Data Growth over the years

Please notation that web awarding data, which is unstructured, consists of log files, transaction history files etc. OLTP systems are built to work with structured data wherein information is stored in relations (tables).

Characteristics Of Big Data

Big data can be described by the following characteristics:

Volume
Multifariousness
Velocity
Variability

(i) Book – The proper noun Large Data itself is related to a size which is enormous. Size of data plays a very crucial role in determining value out of data. Likewise, whether a particular information can really be considered as a Big Information or not, is dependent upon the volume of information. Hence,'Volume' is ane characteristic which needs to be considered while dealing with Big Data solutions.

(ii) Variety – The next attribute of Big Data is itsvariety.

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, sound, etc. are as well being considered in the analysis applications. This variety of unstructured data poses sure bug for storage, mining and analyzing data.

(three) 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 information.

Big Information Velocity deals with the speed at which data flows in from sources like business processes, application logs, networks, and social media sites, sensors, Mobile devices, etc. The menstruation 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 beingness able to handle and manage the data effectively.

Advantages Of Big Information Processing

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

Businesses tin can utilize outside intelligence while taking decisions

Access to social information from search engines and sites like facebook, twitter are enabling organizations to fine tune their business strategies.

Improved client service

Traditional customer feedback systems are getting replaced by new systems designed with Big Data technologies. In these new systems, Big Data and natural linguistic communication processing technologies are being used to read and evaluate consumer responses.

Early on identification of risk to the product/services, if any
Better operational efficiency

Large Data technologies can exist used for creating a staging area or landing zone for new data before identifying what data should be moved to the data warehouse. In addition, such integration of Big Data technologies and data warehouse helps an organization to offload infrequently accessed information.

Summary

Large Data definition : Big Data meaning a 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.
Large Data analytics examples includes stock exchanges, social media sites, jet engines, etc.
Big Data could exist 1) Structured, ii) Unstructured, 3) Semi-structured
Volume, Variety, Velocity, and Variability are few Large Data characteristics
Improved customer service, better operational efficiency, Better Determination Making are few advantages of Bigdata