big-data-basics
Career Education

What is big data?: How data turns to big data

What is DATA?

Generally data is nothing but information which exist in various forms like numbers, words, images and videos, ect. Technically data is converted into a form which computer can process, that is machine-readable. Here are few different types of structured data which tends to get the most attention:-

  • Personal data: Personal data refers to information which is related to you. It covers your email address, identification number, location and other identifying factors.
  • Transactional data: Transactional data is a sequence of information that is generated due action you perform like: visiting on a web page, clicking on add, online purchase, ect.
  • Web data: Web data represent a set of collective information that is extracted from the activities what you perform online. This type of data is very informative for research purposes.
  • Sensor data: Sensor data is the output data which we get from the sensing devices. This type of information can be used as the feedback unit or to provide input to another system.

How does DATA turns into BIG DATA?

In computing and business, all types of data mentioned above integrate among themselves and contribute to big data. Officially there is no fixed size which will make data big. Big data represent the continuous accumulation of various forms of data. There are three parameters that differentiate data from big data: Volume, Variety and Velocity. Therefore big data is not just about more data. It represent large amount of data that is so mixed and accumulated very fast and continuously. The size of the big data is so huge that traditional technique and methodology including normal software do not really work.

General categories of BIG DATA

Big data can be categorised into two forms as:-

  • Structured
  • Unstructured

Structured: Any data which can be represented in a defined format or patterns is termed as structured data. This type of data are machine-readable to which computers can easily access. In order for a program to perform instructions on data, that data must have uniform structure so that computer can derive value out it. It is also known as Machine-readable data.

Unstructured: Any data which cannot be represented in a defined format or patterns. Manner in which this type of data organised and modeled are unknown. There is a big difficulty in processing unstructure data and deriving value out of it. Unstructured data comes from the heterogeneous data source which contains a mixture of text, numbers, images, videos, ect. It refers to the information that generally humans can understand and interpret for the study purposes. Therfore it is also known as Human-readable data.

Characteristics of BIG DATA

  • Volume: From the term itself we can conclude that the size of the big data is too huge. Volume of data plays an important role in performing any kind of computing operation and deriving value out of it. Also, the size of the data determines how it can be handled and processed conveniently.Hence volume is one of the important characteristics of big data.
  • Variety: It reprsent the various types of data accumulated at a particular time. During earlier times, forms in which data is accessed are limited. But currently data available is the form of emails, photos, videos, audio, PDFs, ect. This various forms of unstructure data are difficult to store, access and process.
  • Velocity: The term velocity represent the speed at which data is getting accumulated. The flow of data is massive and continuous. Velocity of flow of data is one of the important factor in deciding the size of  data accumulated withing a paticular time.
  • Veracity: Simple meaning of veracity is truthfulness and accuracy. So in big data it represent, conformity to facts. This gives the idea about the data that is being stored and mined is meaningful to the problem being analysed.

Benefits of big data

Due to big data we are enable to extract enormous amount of information related to bussiness organisation. There is a need to understand that how your bussiness will be more competitive, profitable and customer-focused. We can apply big data science to make our organisation more efficient.

The advantages of big data are as follow:

  • Causes of failure can be known instantly: Due to the use of big data, identification of root causes of failures and issues can be done easily. This can save the operation from failing completely.
  • Frauds can be detected easily: In this financial world, problem of hacking is a common case and it is increasing day by day. Frauds can be easily identified by the IT security departments due to the implentation of big data.
  • Time saving: The high speed big data tools can easily access large amount of data for business analysis in a less time relative to traditional techniques and softwares. This help us to make quick decisions based on the outcomes.
  • Cost savings: The implementation of Real-time big data analytics can be expensive but it will be cost saving in long run. Big data tools saves enormous amount of data and helps us in identifying most efficient ways to do business.
  • Customer satisfaction: Real-time big data analytics allows to do customization of products according to the trends of customer. This will make more customer-focused.
  • Knowing the market condition: With the help of big data you can know the current market condition and accordingly make new strategies. Real-time big data analytics will make you one step ahead of competition.

How does it work?

We are in the era of big data. In computing and business it is not just about collecting and storing of data. Rather it is more about how you access that particular data and extracts output out of it. This is what big data is: its all about analysing every bit of data which is generated due to different types of technology.

Main purpose of big data:

  • Big data comes from the text, images, videos, audio, ect.
  • Various companies collect this kind of data and utilises to improve thier performance by discovering the patterns.
  • Billions of gigabytes are generated every day due to the use of technology and this information is use to find the trends in customers and even human behavior.
  • Big data tools access the data from the various healthcare machineries and analyse it to improve our daily lives.

Why BIG DATA analytics is so important?

Nowadays big data analytics is boosting in business market and have created a big revolution in the field of information technology. This concept is evolved in the early of 21st century and giant companies are using big data as a tool of analysing their business activities. There is a huge requirement of big data anlytics in different fields. This help you to make the stategic decisions to withstand the competitive market. The primary focus of companies is on the customer satisfaction and big data will help you in knowing the customers trend.

Application of BIG DATA

Big data can be applied in various areas like:

  1. Banking and Securities
  2. Communications, Media and Entertainment
  3. Healthcare providers
  4. Education
  5. Government
  6. Transportation
  7. Energy and Utilities
  8. Insurance
  9. Manufacturing and Natural Resources
  10. Retail and Whole sale trade

Conclusion

  1. There is big demand of Real-time big data analytics in co-operate business.
  2. Giant companies are very eager to implement the big data concepts to analyse their business activities.
  3. It you want to master this art:
    • Understand the flow and pattern of data created.
    • Find out the challenge in the organisation and convert into data form.
    • Match the market needs with your capabilities and solutions.
  4. This method is very flexible and hence useful in many areas.
premratan
Mechanical Engineer turned career enthusiast. After facing issues in finding the right job for myself and then realising that despite my degree I don't completely understand the significance of various profiles in the industry, I decided to make career out of helping others in finding the right path

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