Big Data Use Cases in Retail Market

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Executive Summary
WoolWorths Pvt ltd is a largest Australian retail company and wants to expand their business
by using the current big data trends. Here we are introducing the use cases for the big data
and critical analysis of this big data technologies and solution. To stand with the capacity to
analyse, access and manage the huge volume of data when the information architecture is
rapidly evolving is really critical to any retailer like Woolworths to improve their business
performance and efficiency. (Chaudhuri, 2014)
But Favourable Customer experience, operational efficiency, loyalty and retention of
customers is their key of success, but expected demand is really important for more efficient
cash management, inventory management and gross profitability. As Woolworths is a larger
and diverse supermarket so here the data is also become large and diverse so this type of data
management becomes more complex. So we need to analyse the data to better understand
about what products gives the highest profit per square foot. So the retailers have collect the
data of customers from their respective loyalty cards from which we analyse about the
previously purchasing of customers, from this analysis we can monitor their buying patterns,
but still we cannot predict of future demand exactly. But by gathering and utilizing data from
other sources retailers can better understand about the customer future demand which only
possible by big data. By applying big data technologies retailer can gain a better view to
understand the customer and their families’ network and buying patterns. (Chaudhuri,
2014)
The Business analyst desired to have huge data to investigate at higher rates , also stored for
longer and like to analyse it faster, then the Big data is the solution to meet all these
requirements. Here I am representing the overview of Big Data used by the Woolworths
supermarket and analytic capabilities as part of the architecture which needs to meet all the
requirements of dynamic Woolworth’s supermarket. (Chaudhuri, 2014)

Table of Contents
Contents
Introduction............................................................................................................... 3
Key Business Challenges.............................................................................................. 4
Big Data Use Cases..................................................................................................... 5
Critical Analysis of Big Data Technologies........................................................................6
Data Modelling Techniques........................................................................................ 7
Big Data Architecture Solution..................................................................................... 10
Conclusion.............................................................................................................. 13
References.............................................................................................................. 14

Introduction (Katal, 2013)
Big data is introduced to handle and scale the unstructured data. It would give the flexible
database so no need to the referential integrity concept. It can deal with de-normalized data
and do not need any joins. So no need to apply ACID properties as it supports CAP
Properties that is Consistency, Availability, and partitioning. Out of these 3 only any two will
applicable. Instead of ACID, it supports by BASE that is Basically Available Soft state,
Eventual consistency(BASE) . An example of Big Data tools is BigTable, HBASE,
Cassandra etc.
As mentioned in the Australian Food and Grocery Supply Chain Report 2016 there “ hees
been huge focus on customers loyalty , as customers are increasingly purchasing from
multiple stores and the retailer have to work hard to attract the customers”. Woolworths are
well known Australian supermarket among various retailers and big data gives them the
better opportunity to understand customer needs and improve consumer faith. Since many
years they invested in big data to capture the customers by ensuring they are able to make
fact based decisions.
Today now the big data is getting more popular because of its application prospects and
broad research. As the use of big data is increasing so the effort is also increasing to analyse
and store this data. Earlier DBMS works only the structure data but today’s data is having
some unstructured components and analysis of these unstructured components is play very
important role for decision making. Today maximum data is unstructured and to store and
manage this type of data is still a challenge, so before analysis on this data it should be
modelled, this modelling is also important in big data as it contains structured, semi-
structured and unstructured data in the data base. For mapping of all these types of data we
modelling also plays important role for data analytics.