It is important due to its applications in many fields(as given below).
Basics of the ‘Big Data’
Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating and information privacy.
The data could be from social networks, web server logs, traffic flow sensors, satellite imagery, broadcast audio streams, banking transactions, MP3s of rock music, the content of web pages, scans of government documents, GPS trails, telemetry from automobiles, financial market data and so on.
It answers specific questions such as the need of the customers, their opinion and image of the brand
For organisations, analysis of this hidden data may give an insight into things which were previously hidden due to its bulk and the subsequent cost required for its process. This is done by collecting, organizing and analysing large sets of data to discover patterns and other useful information.
For instance, analysis of shoppers’ transactions, social and geographical data gives the analyst knowledge about peer influence on customers, greatly reducing the time that would otherwise require for sampling followed by extensive investigations.
It also enables new products and services, by combining a large number of signals from a user’s actions and those of their friends, Facebook has been able to craft a highly personalized user experience and create a new kind of advertising business.
With the right big data analytics platforms an enterprise can boost sales, increase efficiency, and improve operations, customer service and risk management.
One of the fundamental reasons for opposition of Big Data is centered on privacy since massive amounts of personal data is collected and analysed without a consideration to the person in question.
The large volume of information being collected may be used by finance companies to personalise various schemes for maximisation of their benefits thereby leading to indiscrimination against a certain group of people.
Applications based on ‘Big Data’ Technology
Seed Selection – Big-data businesses can analyse varieties of seeds across numerous fields, soil types, and climates and select the best.
Crop disease – Similar to the way in which Google can identify flu outbreaks based on where web searches are originating, analysing crops across farms helps identify diseases that could ruin a potential harvest.
Irrigation – Precision agriculture aids farmers in tailored and effective water management, helping in production, improving economic efficiency and minimising waste and environmental impact.
Weather – Advanced analytics capabilities and agri-robotics such as aerial imagery, sensors help provide sophisticated local weather forecasts can help increasing global agricultural productivity over the next few decades.
Climate change – Since, climate change and extreme weather events will demand proactive measures to adapt or develop resiliency, Big Data can bring in the right information to take informed decisions.
Food processing – They help in streamlining food processing value chains by finding the core determinants of process performance, and taking action to continually improve the accuracy, quality and yield of production. They also optimise production schedules based on supplier, customer, machine availability and cost constraints.
Loss control – In India, every year 21 million tons of wheat is lost, primarily due to scare cold-storage centres and refrigerated vehicles, poor transportation facilities and unreliable electricity supply. Big Data has the potential of systematisation of demand forecasting thus reducing such losses.
Pricing – A trading platform for agricultural commodities that links small-scale producers to retailers and bulk purchasers via mobile phone messaging can help send up-to-date market prices via an app or SMS and connect farmers with buyers, offering collective bargaining opportunities for small and marginal farmers.
How can it be a Challenge?
The challenges and opportunities of data is immense in a country like India with 638,000 villages and 130 million with 140 million hectares of cultivable land under 127 agro climatic regions capable of supporting 3,000 different crops and one million varieties.
Self-driven vehicles can already drive themselves across fields using Global Positioning System (GPS) signals accurate to less than inch of error thus helping farmers plant more accurately.
But the real potential is what happens when this data from thousands of tractors on thousands of farms is collected, grouped and analysed in real time.
There is need to formulate a business model wherein value can be captured from the scale of data being captured by different players in the agri-supply chain.
Companies must act now to focus, simplify and standardise big data through an enterprise-wide data management strategy.
Q.) The age of Big Data, the growing pervasiveness of Aadhaar, and the government’s push towards a cashless and digital economy has led to a re-emergence of interest in privacy and data protection in India. In your opinion, what are the key elements that should drive the design of a privacy law (when it is actually enacted), or laws that have an impact on privacy? Discuss.