Making Sense of Big Data : KT Prasad – Country Sales Director,...

Making Sense of Big Data : KT Prasad – Country Sales Director, Zendesk


Each year, fresh information is collected by companies in various sectors, and this ends up in repositories. A lot of this data is left untouched for years. So how do companies process the wealth of information accumulated over time?

Data analysis is a business intelligence tool that involves inspecting, cleaning, transforming and modelling data, and converting this into need-based usable information. While most companies claim to have data mining and analysis on their agenda, very few are actively involved in implementing such processes within their structures. The volume of data can be overwhelming at times, but it is possible for companies to deal with the information pile-up using big data analysis.

Gathering information from different sources and storing it on a single platform helps data analysis. Deconstructing data can be used to the company’s advantage. Data extraction can be related to simple information or more complex and multidimensional analyses. Not just companies, different sectors like energy, healthcare, and politics, have used big data analysis to assess feasibility plans and possible outcomes based on past projects and figures.

A survey conducted by Reutlingen University in Germany found that big data is a relatively new subject for German companies. The study found that about 50% of the companies had spent less than three years deconstructing big data and about 25% claimed they were ‘afraid’ to deal with it. The study also showed that the marketing department profited the most from data breakdown, especially since it is important to systematically evaluate and know one’s customers in marketing. Due to these reasons, the customer service teams are the biggest profiteers of big data analysis. But these days, not just marketing, most departments can profit from the process.



Collated metadata or the raw data is first deposited into data repositories or warehouses. Such enormous data collected over the years has the potential to aid companies to implement strategic decisions. For example, the customer service department can use collated customer information to respond to client queries on call or social media.


Most BI tools used these days are simpler and can be utilized by those with basic know-how, not just data experts. They are user-friendly and can be used intuitively by new learners seeking information. This saves time and makes it more convenient for users who have the tools at heir disposal for analyzing and obtaining usable data. They do not have to depend on the IT department for the information; this saves the users both time and energy. The tools also help different stakeholders integrate various types of data to arrive at new insights. For example, data generated by interactions with customers on different channels can all be integrated, filtered or customized, and shared with various departments. One can find information on products, operations and buying habits. These tools are easy-to-use and require only a basic technical knowledge rather than highly-skilled expertise.

The BI tools are easy to understand and can help extract the exact information from a jungle of data. For example, a customer care representative can filter, customize and integrate select data from all the information available on social media channels, by phone, email, and chat. This means information is available for evaluation and usage on demand by all stakeholders, not just appropriate departments.

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The new BI tools break down data into simple, understandable graphics without technical complexities. These visual tools help in large, complex, global organizations where easily-available data can help efficient working of departments across the board. The respective managers can authorize automated reports to be sent to colleagues and team members. Permissions can be set for certain types of information, and audiences can be authorized to have access to select information that is relevant to them.


The availability of information helps make strategic and more calculated business decisions on the basis of solid data and not just whims. The data also helps companies identify problems and look for solutions, fix bugs and predict the overall business climate through the identification of set patterns.


Users get to access the result even as the breakdown of data happens behind the scenes. This means users need not be overwhelmed by the sheer numbers and figures. The content from the data cemeteries can be used to revive businesses. So companies need to start looking at data analyses as a necessary accessory to their work since it provides deep insights into the business data. The various analysis tools can be selected to match companies’ needs. A sophisticated interface will involve training costs in the long term.

Decision makers and managers should proactively work towards adapting the best tools to analyze databases to better strategize the working of their company. Never before has so much data been produced and processed. According to a study by the University of San Diego, by 2024, the world’s enterprise servers will yearly process the digital equivalent of a stack of books extending more than 4.37 light-years to Alpha Centauri, our closest nearby star system in the Milky Way Galaxy. And that is why Big Data analysis is here to help.

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