Nivedit Majumdar Nivedit Majumdar

Talking Numbers: Data Analytics Tools in Organisations

Numbers are awesome. They provide quantifiable evidence of any event, and are therefore valuable indicators of things occurring. This point becomes all the more evident in the cases of big organisations, which rely on the deployment and usage of data analytics tools to gather perspective on the progress statistics.

Be it to improve operational efficiency, increase revenue or gain a stronghold over rival competitors in a market teeming with cut-throat competition, data analytics tools are gaining momentum like never before. And that is the focal point of my article here: Big Data Analytics: what are the types, what tools are used by companies and how are they advantageous.


Before we actually delve into the world of organisational analytics tools, it is imperative to gather a perspective on what are the prevalent types of analytics today.



This is the most common type, focusing on statistics and data regarding “what happened?” in a given period of time. It is easily available, and server tools like Google Analytics are very popular in this regard.


A deeper insight into the statistics gathered, to understand “why some things happened?”. Needless to say, this requires a very high level of expertise and has limited abilities, but when done right, it can provide some valuable insights into the driving force behind events.


Based on the data gathered from descriptive and diagnostic analytics, some future events can be predicted. The factor of contextual data and its correlation with other user behaviour datasets comes into play here.


A rare type of analytics type, this takes in the data from the other three types to give suitable recommendations and advice on how to increase the output.



Big data analytics has tremendous potential in the future, with more companies vying for an enhanced presence in the field of data collection and analysis.

There are quite a few analytics tools providers out there.

• Small companies, such as Alpine Data Labs, Angoss, Predixion, RapidMiner, KNIME and Alteryx provide pretty big data analytics products.

• Some companies have adapted the R Language – which is open source and statistical – and have developed suites which use R’s features to provide predictive and prescriptive analytical capabilities.

• There are a lot of open source players out here, such as the Mahout software distribution, that’s part of the famous Hadoop stack, the open source Weka project and others too.


The field of analytics is a booming one, and this is evident from the statistics and projections in this regard.

• This is the worldwide big data market forecast from 2011 to 2017. It is estimated to hit $38.4 billion this year, and it projected to grow to about $50.1 billion by 2017!

(Data Source: Statista)

• A similar estimate can be found from the big data market volume forecast, from 2011 to 2016 in million euros. It is estimated to hit € 11.957 billion this year, and is projected to grow to € 15.732 billion by 2016.

(Data Source: Statista)

• This statistic shows the global big data market year on year growth forecast, from 2012 to 2017. It is going to grow about 35% from 2014’s statistics, in 2015.

(Data Source: Statista)

All in all, the numbers indicate the sheer growth in the field of global big data analytics in the time to come.


Big corps such as Google, Facebook, Yahoo, LinkedIn, eBay and Netflix are big time analytics users. It is also interesting to see the inclination of investment banks towards using analytics tools.

The field of web analytics is a booming one too, with companies using web analytics tools for performance measurement, gathering information regarding visitor data, optimising marketing strategies and optimising content.

All in all, most companies are resorting to the power of analytics to get a better insight into their activities and the resulting statistics.


Analytics is definitely the in-thing, as far as gathering insights and taking measures based on the insights is concerned. It is somewhat homogeneous to the concept of the Quantified Self in an organisation, and it holds immense potential in the future!

Sign up for our monthly mailing list