Data Analytics and Understanding Big Data

This article explores the definitions and origins of big data analytics in business, including the use of data analytics to identify new trends and develop effective business strategies. It also provides examples of how companies like Tesco use big data to improve their operations and increase profitability. The article concludes by discussing the importance of big data analytics in the retail industry and its potential to improve consumer experiences.

Data Analytics and
Understanding Big
Data

Table of Contents
INTRODUCTION ..........................................................................................................................3
MAIN BODY ..................................................................................................................................3
Section 1: Definitions and origins –............................................................................................3
Data analytics in business – .......................................................................................................3
Big data in business -..................................................................................................................4
Section 2: ........................................................................................................................................4
In this section you should use a business (or no more than three businesses) as an example to
illustrate how big data is used.....................................................................................................4
Section 3: ........................................................................................................................................6
Big data analytics –.....................................................................................................................6
Big data analysis –......................................................................................................................6
CONCLUSION ...............................................................................................................................7
REFERENCES................................................................................................................................8

INTRODUCTION
Big data means any huge and complex record of collected data. It is considered very
huge, diverse data pieces which include both structured and unstructured data, from various
sources, and in various sizes bytes. The process of extracting meaningful and relevant
information from data. The big data analytics is majorly used in big structured organisations. The
big data analytics help in harnessing the data of the organization and in using it to recognize and
grab new opportunities. All this leads to better and smarter moves to run business, efficient and
better operations, happy consumers and higher profitability. Companies with bigger
organizational structure is should prefer big data analytics for the efficiency in working of the
organization. The big data analytics includes collecting data, processing data, cleaning data and
analysing data. In short it is collecting, processing, cleaning, and analysing large data sets to help
organizations operate their data files (Wang and et. al., 2018).
MAIN BODY
Section 1: Definitions and origins –
Data analytics in business –
the process of examining and analysing the data to find out about new trends and further
business strategies. Data analytics basically can only be done in the advanced updated
software and computers. this is mainly done in the commercial industries to bring out
more accurate information about the company and to take decisions quickly, effectively
and efficiently. Executing the data analytics processes in the company can result into
higher revenue, more productivity, betterment In managerial activities. In this era of
rivalry competition, analytics also helps in responding quickly to new trends(Amalina
and et. al., 2019). The technique was found in 19th century. Computers as well as
computing technology being a support system in late 1960s, analytics gathered the more
attention. With the development of new hardware and software, data analytics has also
been evolved. This included, researching, discovery and interpretation of data. There are
many data analytical tools and software available in the market like python, Microsoft
excel and many more.

Big data in business -
big data are basically the sets of structured, unstructured, and semi-structure data which
are complex to deal with traditional methods because of their big length. Example- the New
York stock exchange is generating about 1 terabyte data per day. This basically helps in giving
the complete answers because it contains more information. The concept of big data came in
early 2000s. When anybody combines both the data analytics and the big data, this helps them in
identifying the possibilities of risks, evaluation of risk and more. An analyst, Doug Laney
explained and defined the three Vs of big data which are volume and it means the quantity of
data. Velocity is considered as the rate at which the data can be received. And at last the word
variety is meaning to the various kind of data in availability( Ardito and et. al., 2018) .
Nowadays the big data are the vital part of the businesses as the value they offers comes from the
data which they analyse to increase efficiency and productivity. The origin of big data has
arrived from back to the 1960s when the technology was just evolving.
Section 2:
In this section you should use a business (or no more than three businesses) as an example
to illustrate how big data is used.
Data and information generated by users, sensors, network devices, cell phones, and other
sources are multiplying at exponential rates within any firm. And also, the corporate leaders
should take care of the fact that if the data they collect can be used for other purposes and not
only for increasing the performance. Big data can make billions of dollars for revenue, which can
help the organizations in fuel expansion(Mikalef and et. al., 2019).
The well-known supermarket in the industry faces many challenges at the starting, from changes
in customer behaviour and the management operations to the need to reducing food waste and
compensation for current competitors. When it comes to the food market and services, the reason
the company Tesco is using big data analysis in their administration. The most of the Tesco's
action on data analytics is concentrated on cutting-edge techniques, current data, and real-time
analytics.
The following are the different parts of administration in which Tesco makes effective use of Big
Data:

1. To save money on lights and heating
The company is using big data to save money on heating and lighting. The firm often collaborate
with their suppliers to connect heating and lighting regulators from its stores in the locality to
data warehouses via internet.
To analyse the performance of each store and examine which ones are operating perfectly fine,
which ones are over heating, and which ones are under heating Tesco make use of Google Maps.
The way for tesco to energy and cost savings is that it could turn on the heating three hours later
and still have proper temperature at the stores for opening time.
2. To enhance the value chain
To create data-driven power in all aspect of the organizations value chain, from supply chain to
revenue and service, the Big data analytics is being handy to Tesco. To give reorder warnings in
advance through the help of supply chain and logistics threads, the company is using the Real-
time analytics combined with predictive analytics.
Big Data seems to be a multi-channel strategy for tesco for working according to future trends in
consumer shopping behaviour, addressing users' wish to access the physical stores, mobile
devices, and desktop computers all other tasks at once (Pappas and et. al., 2018).
For example, internet network at any store can be used by the users to order things to pick up in
the store, or use a cell phone to order deliverable food from the stores.
3. predicting future developments
Many functions can be done such as monitoring freezers and the refrigerators temperature with
the efficient use of connected devices that create vast amounts of data, each firm, including
Tesco, uses these sensors.
The usage of open -source technology to predict future trends, and to assist the open-source, is
the result of encouragement of the developers and data scientists in the organisation.
The big data helps the organization to gain the knowledge about the consumers taste and the
preferences which will help the organization to grow.
4. Sales forecasting
the most important area of research and operation where the company put their data first is Sales
forecasting.
According to the clustering approaches and data analytics the Customer data modelling states
many complications like "how people buy at a store over the course of a week?" or "how they

shop for each item?" even "The way products are bought together is not truly the way the items
behave,"(Sedkaoui, 2018).
Section 3:
Big data analytics –
nowadays big data plays an important role in every organisation as weather it is a
healthcare industry or insurance industry. Mainly companies use big data to take effective and
efficient decisions. This also encourages the company increase a better market. Big data also
makes the business's internal operations smooth and effective. This studies about the consumers
pattern and then they use it in increasing the brand loyalty. Lastly this helps in serving the best
products and services to the customers. In context to the chosen company Tesco, a multinational
retailer of groceries. Which was founded in 1919 by jack Cohen and serves into UK, Ireland
Hungary and many more countries(Mariani and Wamba, 2020). They also use big data in their
company as well to check up on their business. There are some ways the Tesco uses big data
efficiently, like in controlling the lighting and heating cost. They always keep an eye on their
stores, which are running cooler and which are overheated. Secondly in the betterment of value
chain, Tesco uses big data to transfer the data. Thirdly, they use the analytics as a strategy to
know about the trends in the environment according to the consumer behaviour (Tabesh,
Mousavidin and Hasani, 2019).
Big data analysis –
basically, the organisations take quick and better decisions after using the big data in the
company. They take smarter moves, increase their productivity and also the growth of revenue
increases which results in good profit margin. Analyse and study about the consumer behaviour
and get acknowledged about their needs and wants. Basically, the organisation study all over the
business positions, changes they can make, risks they can avoid. Same the chosen company
Tesco did they understood the consumers behaviour as well as nature. Also, they have reduced
wastage of food at the stores after the analytics. The information based on the analytics is more
factual and real and also it is according to the past experiences of the firm.

CONCLUSION
Big data is known as a vast amount of data which can be used to uncover patterns, trends, and
relationships, precisely in the relation of human behaviour and interactions. Big data analytics is
extremely important in the retail industry. The ability to improve consumer experiences to the
retailers is the gift of big data analytics. Big Data Analytics will assist merchants in anticipating
client demand, which will allow them to make better, careful and customer-centric decisions and
this will help the company to customize their marketing techniques and methods on the basis of
consumer data. Tesco, the UK's largest food store, is on the cutting edge of data and technology
visualisation.The usage of a loyalty card system to track consumer activity and securely control
the transition to online retailing was very firstly done by tesco. However, big data and analytics
are feasible remedies to make efficiency plausible, from tackling significant difficulties to
enhancing performance using the latest technology. The big data analytics is helping such
organizations to overcome such problems in administrating the organization.

REFERENCES
Books and Journals
Amalina, F and et. al., 2019. Blending big data analytics: Review on challenges and a recent
study. Ieee Access, 8, pp.3629-3645.
Ardito, L and et. al., 2018. A bibliometric analysis of research on Big Data analytics for business
and management. Management Decision.
Mariani, M.M. and Wamba, S.F., 2020. Exploring how consumer goods companies innovate in
the digital age: The role of big data analytics companies. Journal of Business
Research, 121, pp.338-352.
Mikalef, P and et. al., 2019. Big data analytics and firm performance: Findings from a mixed-
method approach. Journal of Business Research, 98, pp.261-276.
Pappas, I.O and et. al., 2018. Big data and business analytics ecosystems: paving the way
towards digital transformation and sustainable societies. Information Systems and e-
Business Management, 16(3), pp.479-491.
Sedkaoui, S., 2018. Data analytics and big data. John Wiley & Sons.
Tabesh, P., Mousavidin, E. and Hasani, S., 2019. Implementing big data strategies: A managerial
perspective. Business Horizons, 62(3), pp.347-358.
Wang, J and et. al., 2018. Industrial big data analytics: challenges, methodologies, and
applications. arXiv preprint arXiv:1807.01016.