Big Data Analytics: Use Cases in Developing CountriesMachine learning based models ensure governance, risk mitigation, quality service, automated and intelligent controls to enable retail and BFSI businesses to save up to 30per cent on the energy bills

ByYasir Wani

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Computing is already a necessity after -- oxygen, water, electricity, gas and telephones. It has risen up the ladder of social utility due to various service models for cloud computing like Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), Infrastructure-as-a-Service (IaaS) and now even Analytics-as-a-Service (AaaS). In this article, we will focus specifically on Big Data. In layman terms, Big data analytics is a process which includes examining large and varied data sets. Predominantly, it caters to business organisations as it easily brings to the fore -- hidden patterns, customer preferences, market trends and unknown correlations which in turn help these corporate giants make informed decisions resulting in profits. This technology is now being increasingly used in other industries such as – agriculture, health, education and supply chain-logistics to name a few.

Magical Things That it Can do

In developing economies, there is a lack of proper infrastructure and a scarcity of inclusive data keeping techniques which cover even the remotest of regions and rural areas. Big Data can help us reach even those not so easily accessible places and compile data which can then be added to the collated dataset of a country. All this is possible because of the Internet of Things. To simplify, interrelated devices such as computing and digital machines, objects, people as well as animals are bestowed with unique identifiers along with the ability to automatically transfer data over a network. This eliminates the need for human clerical work of feeding in numbers. We are not talking about the distant future or of technology being used in developed nations but about our own country where many startups are already working in this domain. One startup makes use of Internet of Things (IoT), Cloud computing, Big Data analytics, and mobility, to refine the established agricultural supply chain parameters -- milk production as well as procurement, cold storage chain, and animal insurance. Another Indian data-driven energy efficiency startup is utilizing advanced machine learning to ensure significant energy savings for its consumers. They use machine learning based models which ensure governance, risk mitigation, quality service, automated and intelligent controls to enable retail and BFSI businesses to save up to 30per cent on the energy bills.

In The Healthcare

Healthcare sector has tapped the potential of Big data analytics potential and has begun to make use of this technique to help preventing epidemics (by keeping a record of symptoms, medications given, medical reports of a larger pool of people), curing diseases, and also cutting down costs as each organization does not have to update and maintain individual databases. Big data can further highlight the gap between the requirement and supply of medical facilities in the regions by the means of statistics. This path-breaking method aids in collecting data and converting it into critical insights with can be used as a reference by the future generations as it is also a way of documenting medical history.

在所谓的第三世界国家,大数据can also help in collecting data and combining various digital resources without personal bias and prejudices hence, reducing human-introduced errors as well as encouraging data journalism which will consequently break the back of corruption and fake news. Consequently curbing the menace of irrelevant gibberish floating in the media and social circles. Finally, we might have a solution to the biggest problem which erupted at the advent of twentieth-century - Too much, untrustworthy information being circulated to confuse and manipulate mankind.

Efficient collection of accurate data will highlight what the public desires and will also minimise the time taken in decision making. Slower decision making and policy implementation is often a complaint of people residing in democracies especially in a diverse country like India. The governing bodies can gather a vast extent of information such as demographic trends from the internet, applications, social media as well as other digital platforms which can be further used in their policy-making process. With in-depth information at their disposal, the government can bring about changes to boost the economy faster. In the light of India's tryst with Aadhar Card and the constant potential threat of leak of the citizen's personal information to malicious groups; Big data will also create a centralized system of data thus improving its security and accessibility to a great extent. As a result of the reduced risks, it will be easier to implement policies and less politicization and opposition.

Agriculture Sector

在农业领域,大数据是establishing a cyber-physical farm management cycle. Yes, it isn't a sci-fi fantasy but a huge volume of diverse data can be captured for study and analysis which will aid the farmer's decision-making process. A Startup, turns satellite captured data into high-resolution images which can be used by the farmers to monitor crop health; and draw attention to various other needs as fertilizer, pest management and water. It also warns against a sudden change in operational conditions like weather or spreading of crop disease. Another company, Blue River makes use of machine learning and robotics to guide about farm inputs. Big data can help with complicated needs such as choosing business partners, buyers, sellers etc. And is also the solution to simple problems on the field. This technology can even help in soil health monitoring.

And against the illusion breaking argument about humans losing jobs to machines -- Such analysis and technology do not reduce human involvement rather increases human presence and control in strategical capacity and supervisory roles. Big data analysis directly helps the stakeholders of the agricultural sector along with maintaining a database having the required information about the crops, methods of region-specific farming, the base price of crops, damage control techniques used, issues troubling the farmers, which certainly helps in formulating better targeting agricultural welfare schemes.

In Education Sector

Big data is touching many facets of human life including education. This sector is of primary importance to humans and their civilization. The aforementioned technology helps in gaining a better insight into individual student's behaviour which becomes a foundation stone in creating a learning environment which is conducive for all the students. Further, Big data can help in the uphill task of monitoring student actions -- how much time they require to answer a question, the sources they refer to for exam preparation, questions they generally skip, etc. Such information can help the teachers formulate remedial actions which might bring down the dropout rate in schools and colleges alike. The database can also track and store information regarding the performance of students after school or college, in the job market. This would also guide the next batch of students in choosing the right course and college.

While there are so many pros of Big data, some researchers believe that such algorithms will swallow jobs and unemployment rates would reach its pinnacle. It is true that they efficiently procure a great volume of data in lesser time than a human employee but we still require a skilled human brain to link the stats to other factors and form conclusive figures which can actually help as opposed to the raw data shared by the algorithm. Like all other technological advancements it is to make the human being's work more convenient and life a lot easy.

Yasir Wani

Product Analytics Specialist

Yasir is a multipotentialite who craves for brain-stimulating problems faced by digital consumers. He has a knack for Consumer Centricism keeping a close eye on what data has to say. Previously worked at Flyin.com where he built the BI and Web Analytics team from scratch creating huge business impact and shaping a data-driven culture in the organization. This achievement helped him work closely with C-level executives of the company ranging from Managing Director, Chief Finance Officer, Chief Product Officer and Marketing Director. The main areas of work included: Data-Driven product strategy, Setting of Success KPIs for new features, benchmarking, Web Analytics strategy, Enterprise-wide Data Dashboards, Hypothesis Testing using A/B & Multivariate Tests, Customer Behavior analysis, Visual Analytics, UX & Content Auditing and Product change management.

Recently relocated to Riyadh, where Yasir is helping HungerStation align with the DeliveryHero Analytics Team to setup state-of-art Analytics Strategy and implementation.

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