Big data(History,Examples,Platforms,Features ,Characteristics, Benefits)

Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. It's what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.

According to Gartner, the definition of Big Data – 

“Big data” is high-volume, velocity, and variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.”

History of Big Data

In 2005 Roger Mougalas from O'Reilly Media coined the term Big Data for the first time, only a year after they created the term Web 2.0. It refers to a large set of data that is almost impossible to manage and process using traditional business intelligence tools. 2005 is also the year that Hadoop was created by Yahoo!.

Data Originate

Data analysis, data analytics and Big Data originate from the longstanding domain of database management. It relies heavily on the storage, extraction, and optimization techniques that are common in data that is stored in Relational Database Management Systems (RDBMS).

Real World Big Data Examples

• Discovering consumer shopping habits.
• Personalized marketing.
• Fuel optimization tools for the transportation industry.
• Monitoring health conditions through data from wearable.
• Live road mapping for autonomous vehicles.
• Streamlined media streaming.
• Predictive inventory ordering.

Digital data can be classified into three forms:

• Unstructured Data.

Unstructured data refers to the data that lacks any specific form or structure whatsoever. This makes it very difficult and time-consuming to process and analyze unstructured data. Email is an example of unstructured data. Structured and unstructured are two important types of big data.

• Semi-Structured Data.

Semi structured is the third type of big data. Semi-structured data pertains to the data containing both the formats mentioned above, that is, structured and unstructured data. To be precise, it refers to the data that although has not been classified under a particular repository (database), yet contains vital information or tags that segregate individual elements within the data. Thus we come to the end of types of data. 

• Structured.

Structured is one of the types of big data and By structured data, we mean data that can be processed, stored, and retrieved in a fixed format. It refers to highly organized information that can be readily and seamlessly stored and accessed from a database by simple search engine algorithms. For instance, the employee table in a company database will be structured as the employee details, their job positions, their salaries, etc., will be present in an organized manner.

"Digital data jumps from one value to the next in a step by step sequence ."

Big data platform

Big data platform is a type of IT solution that combines the features and capabilities of several big data application and utilities within a single solution.

It is an enterprise class IT platform that enables organization in developing, deploying, operating and managing a big data infrastructure /environment.

Big Data Platform is integrated IT solution for Big Data management which combines several software system, software tools and hardware to provide easy to use tools system to enterprises.

It is a single one-stop solution for all Big Data needs of an enterprise irrespective of size and data volume. Big Data Platform is enterprise class IT solution for developing, deploying and managing Big Data.

There are several Open source and commercial Big Data Platform in the market with varied features which can be used in Big Data environment.

Features of Big Data Platform

Here are most important features of any good Big Data Analytics Platform:

• Big Data platform should be able to accommodate new platforms and tool based on the business requirement. Because business needs can change due to new technologies or due to change in business process.
• It should support linear scale-out
• It should have capability for rapid deployment
• It should support variety of data format
• Platform should provide data analysis and reporting tools
• It should provide real-time data analysis software
• It should have tools for searching the data through large data sets

Characteristics Of Big Data: 

Big data can be described by the following characteristics:

• Volume

• Variety

• Velocity

• Variability

(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. Also, whether a particular data can actually be considered as a Big Data or not, is dependent upon the volume of data. Hence, 'Volume' is one characteristic which needs to be considered while dealing with Big 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. 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. This variety of unstructured data poses certain issues for storage, mining and analyzing data.

(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.
Big Data 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 flow of data is massive and continuous.

(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

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

• Businesses can utilize outside intelligence while taking decisions

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

• Improved customer service

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

• Early identification of risk to the product/services, if any

• Better operational efficiency

Big Data technologies can be 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 data.

Summary

• Big Data definition : 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.

• Big Data analytics examples 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 Big Data characteristics.

• Improved customer service, better operational efficiency, Better Decision Making are few advantages of Bigdata.