Big Data


First go through the text (given after the questions) and then attempt the questions.


QUES 1 . What do you understand by Big Data? Discuss about the challenges and significance of Big Data.


What is Big Data?

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. Big data can be analyzed for insights that lead to better decisions and strategic business moves.

Big data challenges

Big data are so voluminous and complex that traditional data-processing application software are inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source.

Term is new not the act

While the term “big data” is relatively new, the act of gathering and storing large amounts of information for eventual analysis is ages old. The concept gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three Vsvolume, variety, velocity.

Dimensions of big data
1 . Volume

Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data.

2 . Velocity

Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.

3 . Variety

Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.

Two additional dimensions can be considered in today’s context-

4 . Variability

In addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks.

5 . Complexity

Today’s data comes from multiple sources, which makes it difficult to link, match, cleanse and transform data across systems.

Standardization in Big data

Standardization in Big data is going to play a major role in facilitating the exchange and sharing huge volume of data across multiple platforms, multiple applications and multiple sectors. With proper standardization in place, huge volume of data generated within a system can be effectively utilized by other systems/services and applications.

Significance of Big Data

In the recent past, the topic ‘Big data’ have gained significant popularity globally because of its capability to revolutionize the businesses and services. In fact, Big data has an impact on every aspect of our daily life.

The emerging technology areas like Internet of Things (IoT), Artificial intelligence, machine learning are fuelled by Big data and analytics only.

Advancements in big data analysis offer cost-effective opportunities to improve decision-making in critical development areas such as health care, employment, economic productivity, crime, security, and natural disaster and resource management.

The use and adoption of big data within governmental processes allows efficiencies in terms of cost, productivity, and innovation.

In India also Big data has become the major focus of scientists and technologists because of government’s new initiatives like ‘Digital India’.