All articles by Indra Giri

Manufacturing industries as the major source of air pollution in India

Air contamination is defined as the presence of toxins that affect the environment (Vallero 2011). India, as a rapidly developing nation, needs to manage its ecological issues well to minimise contamination of air, water and soil. The major factors for air pollution in the country are:

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Major initiatives by different stakeholders for affordable housing in India

Housing is a challenging issue all over the world, particularly in developing nations like India. It has turned into a top need of the administration and the society at large to address this issue. According to recent research, by 2025 over half of the Indian population will live in urban settlements looking for steadiness and wage (Anon n.d.). Read more »

Behavioral approach of measuring performance of employees

There are various methods which organisations adopt to measure employee performance such as:

  • comparative approach,
  • attribute approach,
  • behavioural approach,
  • result approach and
  • quality approach.

Behavioural approach is the most commonly adopted approach and comprises of vertical scales which are based on certain parameters. Organisations use following techniques to measure employee performance:

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R software and its useful tools for handling big data

In recent years, industries such as finance, healthcare and Information and communication technology (ICT) industries have witnessed dramatic changes as a result of big data phenomenon.  In fact, a recent report by Consumer News and Business Channel (CNBC) (2015) highlighted the role of big data in the real estate sector and explained its evolution. This then has provided analysts with opportunities to restructure raw data and offer related solutions (Catella, 2015). Hence, the role of R software in identifying basic patterns in unstructured big data cannot be underestimated. This is because it helps in standardization of unfamiliar characteristics as well as estimation of important parameters (CoreLogic, 2013) . Read more »

Distribution system of payment terminals in India and their growth opportunities

The contemporary digitized era has welcomed the innovative ways of transactions in the market. Today’s market boasts of speed, safety and convenience. Consumers are flooded with vast array of digital payment platforms, online shopping and cashless transactions. In addition sellers too are offered the equal opportunities of handling and managing their sales (Reserve Bank of India 2016). One such unique feature of conducting digital transactions is through payment terminals.

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Big companies are using big data analytics to optimise business

Big data applications are vital for storing and processing large amounts of data. Depending on the type of organisation, big data sets can be used to better understand customer needs and preferences. Amazon stores, for example are using big data applications to process data of its customers and provide them with recommendations for future purchases. Its advertisements are also tailored with customer purchasing trends and their history.

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Importing data into hadoop distributed file system (HDFS)

Hadoop is one of the applications for big data analysis, which is quite popular for its storage system that is Hadoop distributed file system (HDFS). It is a Java-based open source framework which stores big datasets in its distributed file system and processes them using MapReduce programming model. Since the last decade, the size of big datasets has increased exponentially, going up to exabytes. Furthermore, even in a small organisation, big datasets range from hundreds of gigabytes to hundreds of petabytes (1 petabyte = 1000 gigabytes). When the size of datasets increase, it becomes more difficult for traditional applications to analyse them. That is where frameworks like hadoop and its storage file system come into play (Taylor, 2010).

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Advantages of using R statistical software for predictive modelling

Predictive modelling is a data driven, induction based modelling that is continuously used by big sized companies to gain useful insights into trends and risks budding in the future. The modelling on the basis of data extraction, cleansing and analysis helps in predicting the value of a target variable (Fortuny, Martens, & Provost, 2013). Most of the analytical softwares developed are used to efficiently understand how things move for an organisation as per trends indicated by a relevant factor. One of the software that helps in prediction is R, summarization and estimation of the target variable with respect to different factors (Varian, 2014). The software holds a wide scope to develop predictive models.

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