#InterView
Data, big data and data driven decision making strategy
Dr. ANIMESH ACHARJEE,
Data Sceintist,
Cambridge University,
UK
Dr. Animesh Acharjee, PhD Senior Biostatistician,
Healx Limited, St John’s Innovation Centre,
Cowley Road, Cambridge, UK Visiting Scientist,
Department of Biochemistry, University of
Cambridge, Sanger Building, 80 Tennis Court Road,
Cambridge, UK Visiting Investigator Scientist,
MRC Elsie Widdowson Laboratory, 120 Fulbourn
Road, Cambridge, UK Visiting Faculty, NIT-Calicut,
School of Management Studies, Calicut, India
http://www.bigdata.cam.ac.uk/directory/dr-
animesh-acharjee
https://www.linkedin.com/in/animesh-acharjee-
3a291716?trk=hp-identity-name
Introduction
Data became an essential part of our everyday
life starting from personal to business aspects.
In this digital age with vast amount of data
(also called as big data), organisations in almost
every domain are focused on exploiting data
for many reasons. Some of them are: effective
decision making, competitive advantage, market
growth predictions etc. Extensive investments in
business infrastructure improved the
ability to collect data throughout the
enterprise. Virtually every aspect of
business is now open to data collection
and often even instrumented for data
collection for optimum functions in
operations, manufacturing, supply-
chain management, customer behavior,
marketing campaign performance,
workflow procedures, and so on. At
the same time, information is now
widely available on external events
such as market trends, industry news,
and competitors’ movements. Massachusetts
Institute of Technology (MIT) from USA did
a study on the data driven decision making
and they found data-driven decision making
environments had 4% higher productivity
and 6% higher profits than other businesses
did. http://searchbusinessanalytics.techtarget.
com/news/2240035852/MIT-study-Data-driven-
decisions-mean-higher-productivity-profits
Data analytics is a process
Data analytics or data analysis is a process,
meaning we need to follow certain rules and
steps and make our decision accordingly. In the
figure 1, I tried to summarize the broad steps
need to follow to make use of data. In each
phase, we need to check certain key aspects
regarding data and finally make decision which
need to feed into the questions we are asking
before any data analysis.
Figure 2: Flow diagram of different phases of
(big) data analytics and finaly decision making
process. This outcome will again feedback into
the initial process which is questions we are
asking before we collect our data.