Big Data in Business Analytics: A Roadmap for Research
Why would I even write it?
I called this blog as a result of my long observation of a word that is widely used in this decade under various contexts “data”. In Today’s world, data is like a currency. Data itself has a meaning and a value associated with it. But when this data is so large, generating a meaning and a value out of it is often a tedious task. Word “Big Data” evolves as a result of this problem.
Extremely large data sets that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
“Much IT investment is going towards managing and maintaining big data”
Objectives for Big Data Analytics
Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings. Like traditional analytics, it can also support internal business decisions. The technologies and concepts behind big data allow various organizational models to achieve a variety of objectives, but most of the organizational models we came across in past few decades (like e-Commerce, e-Trade and e-Business) were focused on one or two.
Process in which the effect or output of an action is ‘returned’ (fed-back) to modify the next action. Feedback is essential to the working and survival of all regulatory mechanisms found throughout living and non-living nature, and in man-made systems such as education system, online shopping system and economy. As a two-way flow, feedback is inherent to all interactions, whether human-to-human, human-to-machine, or machine-to-machine. In an organizational context, feedback is the information sent to an entity (individual or a group) about its prior behaviour so that the entity may adjust its current and future behaviour to achieve the desired result. Feedback occurs when an environment reacts to an action or behaviour. For example, ‘customer feedback’ is the buyers’ reaction to a firm’s products and policies.
Based on the feedback value we rate the promising items. Then find out the promising items. Candidate item sets can be generated efficiently with only two scans of database. Mining high utility item sets from database refers to the discovery of item sets with high utility like profit. So the user feedback base to product purchase. This will be useful for the new user to buy the product.
“In this blog, we have examined the innovative topic of big data, which has recently gained lots of interest due to its perceived unprecedented opportunities and benefits. In the information era we are currently living in, voluminous varieties of high velocity data are being produced daily, and within them lay intrinsic details and patterns of hidden knowledge which should be extracted and utilized. Hence, big data analytics can be applied to leverage business change and enhance decision making, by applying advanced analytic techniques on big data, and revealing hidden insights and valuable knowledge.”
Rajbahadur Singh Rajput :Software Developer Trainee
iInterchange Systems Pvt Ltd
Disclaimer: The views expressed in this blog are the writer’s and are not an indication of the company’s view, action or strategy.