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Building Relationships with Your Data: We Tell You How

Manas Agrawal
CEO, Co-Founder-Affine Analytics
Monday, January 2, 2017
Manas Agrawal
These days, companies of all sizes are hiring consultants to help solve complex business challenges - be it RoI related, brand recognition, product launches or basic education of services and products offered. These challenges are being further entrenched with large amounts of data being manipulated in order to draw tangible results. Whether it is a MNC or a SME, everyone is searching for answers that are deeply rooted in facts, industry figures and hard data. It goes without saying that analytics has become a crucial portion of the consulting industry and is on the verge of becoming one of the desirable skills a consultant can have these days. Huge budgets are drawn out by large consulting firms with talent being hired possessing a wide range of data science and analytics skills. Today, companies look to consultants to provide them with data science skill sets that can tackle a range of consulting projects. Hence the data scientist is fast becoming the jack-of-all-trades in the consulting world.

New Analytics Architecture

As data generation volume rises along with the variety of data, a rising number of tools are capable of dealing with the 'Big Data' issue of analysis of capturing of large amounts of data in order to create value for clients. Larger firms are facing the issue of integrating such new tools into an already complex information system. Having to rely on traditional databases is being found to inferior to keeping up with new forms of data such as Twitter feeds or even call centre records. These days, for example, tools such as the Hadoop Distributed File System are fast becoming the norm in companies' information platforms.

Additionally, new Analytics tools are being created for the purpose of drawing analytical insights and also possess the capability for extraction and sourcing of data from new data storage environments. A few tools focus on those capabilities that can perform advanced analytical processes, like R and Python.

Such platforms are enabling analysts to analyze data in a more interactive manner, which allows the user better understanding of the findings. Analysts are able to quickly change the data they look for as well as the manner in which they look at it. Simple point and click steps on visualizations allow the user to use and access the necessary data minus any knowledge of coding. Various charts and views of the same data source help illustrate ideas behind the data. This allows the user to see the fluid relationship amongst changing variables. Data scientists are able to use analytics techniques in order to display data in the required format by tools such as Tableau. These tools now help render the output into a cleaner visualized format that can be easily consumed by the user.


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