India is among the fastest growing economies in the world and is considered an emerging superpower. While on one hand, India’s central location and the trans-Indian Ocean routes have contributed to this growth, on the other hand, its large and complex border poses numerous challenges which need to be addressed for India’s continued growth. The volume, variety and velocity of data will keep growing, increasing the gap between big data and relevant data. Border protection agencies need all the information they can get, but also need tools and systems to get to the relevant data. They need actionable information culled out from peta bytes of data, to guide decision making in the fastest time. Thus the need of the hour is the use of analytics to sift through peta bytes (01 peta byte = 10,00,000 gigabytes of data) of data being captured, generated and collated from various sensors that have been deployed.

Descriptive analytics, as the word suggests, records happenings in the past and in the present but cannot establish a relationship between events. Diagnostic analytics looks for relationships in the data and can provide clues to causes and effects of events. Intelligence analysts use diagnostic analytics, for example, to determine whether money being moved by a terrorist group is intended to buy weapons. Predictive analytics is built on the foundation of higher-level descriptive and diagnostic analytics. Raw data is sorted and made comprehendible in the form of spreadsheets, charts, reports and presentations using descriptive analytics. As organisations become adept at Predictive Analytics, they can begin to move to the next phase, ‘Prescriptive Analytics’.

The border forces have deployed numerous sensors to carry out surveillance and monitoring. For example, to enhance coastal security, 74 Automatic Identification System (AIS) receivers have been deployed forming an AIS chain, in addition a chain of overlapping 46 coastal radars will cover the coastal areas apart from VTMS connectivity at Gulf of Kutch and Gulf of Khambhat. Border Security organisations are also collating surveillance data from numerous cameras, ground sensors, etc. Data on immigration, migrants, etc is also available. This data along with analytics can be used to make more insightful, forward-looking decisions in regard to actionable intelligence, logistics, manpower, and a host of other critical security concerns. Seamless integration of strategic intelligence with operational and tactical Intelligence across defence services and other agencies is needed and this can be made feasible using Big Data analytics. Border Security Agencies need a data integration layer, that can connect all of the disparate databases residing across the agency, department or other central, state & local government entities – a single layer that can link a comprehensive set of data from multiple data sources into a single dashboard in real time. To effectively analyse vast amount of granular data, the data infrastructure must be able to:

Big Data is the answer to this! Big Data Analytics is “the process of examining large data sets containing a variety of data types” – i.e., Big Data – to uncover hidden patterns, unknown correlations, trends and anomalies – anti-social events, terrorist activities, fishing barges, etc. and other useful information. There are various types of tools that may fall under the umbrella of Big Data Analytics or serve to improve the process of analysing data: data collection, storage and management, integration, cleaning, mining, transforming, analysing, and visualisation. The actual approach used will depend on the volume of data, the variety of data, the complexity of the analytical processing workloads involved, and the responsiveness required by the organisation.

India being a service-oriented economy relies heavily on the movement of goods and people. However, if these movements are uncontrolled, less regulated or unsupervised then smuggling, trafficking, crime, terrorism and illegal migration can increase. Additionally, India has a large and complex land border covering 15106.7 km and a long coastline of 7517 km, with difficult and varied terrain, peculiar conditions related to each terrain, varied climatic conditions, geo-political standpoints, which further complicate the border management and presents the need for the use of technology to move towards smarter ways of managing our borders. Use of technology in terms of cameras, night vision devices, radars and other sensors notwithstanding, the use of big data and predictive analytics is a solution to optimise the available data and to put it to good and intelligent use. Dovetailing of predictive analytics with the use of sensor technologies would not only optimise the use of effective force at the right time and the right place but would also help in savings to the exchequer. Big data and predictive analytics is being used world over in a number of domains to enable better decision making and commercial gains. It is also being used by developed countries like the US, China, Russia, etc in the domain of military and security to enable proactive surveillance by predicting the nature, location and time of the threat.

Big data and predictive analysis require infrastructure to support capturing of this huge amount of data that is generated. When MPP databases and in-memory databases (IMDBs) are coupled together, the concept in which fast data meets Big Data becomes a reality. This is particularly important when the real- time location of an entity is desired, or, for instance, data is flooding in from millions of sensors in the battlefield and needs to be correlated with vast quantities of historic data. The FOUR big data strategies – namely, Performance Management, Data Exploration, Social Analytics and Decision Science, are very much required to capture and create value from big data, and use the best & most suitable predictive analytics tool on the data by modelling it to meet the requirement.

This article highlights the use of big data and predictive analytics and also brings out a number of use cases which can be implemented for the management of our borders in a more efficient and smarter way. Use of Big Data and Predictive Analytics can this find great application in efficient border management.

Kausik Saha is a partner in the Business Advisory Services, with a focus on Analytics practice. He is a regular speaker at various B Schools and other events on aAnalytics.

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