ITECH 3101 Assessment Part 2: IT Assessment Report

This report provides a comprehensive overview of information technology, focusing on emerging technologies, analytics, and business intelligence, with a particular emphasis on decision support systems. It explores location-based analytics, its significance, and how it powers consumer applications, creating opportunities for businesses. The report includes a detailed case study on big data analytics, examining problems, challenges, and proposed solutions within a specific company, Luxottica. It also delves into the principles of the approaches used in the case study. Furthermore, the report reflects on the major learnings from the course, including the impact on current and future learning practices. The conclusion emphasizes the importance of IT in modern organizations and the need to adapt to technological advancements. The report covers various topics such as data warehousing, data mining, and web mining models, providing insights into the field of information technology and its applications.

IT Assessment

Table of Contents

INTRODUCTION...........................................................................................................................1
MAIN BODY...................................................................................................................................2
Emerging technology that may impact analytics, BI and decision support...........................2
Importance of location based analytics..................................................................................2
Ways the analytics are powering consumer applications & creating opportunity for businesses
................................................................................................................................................3
Business intelligence & decision support & case study of big data analytics overview........3
Problems and challenges in the case study of big data analytics...........................................3
Solutions to the problems in the case study of big data analytics..........................................4
Principles of the approaches used in the case study of big data analytics..............................4
Reflection on the major learning taken away from this course..............................................5
Impact it may or may not play on the current or future learning practices............................5
CONCLUSION................................................................................................................................5
REFERENCES................................................................................................................................7

INTRODUCTION
Information Technology can be defined as the use of technical devices which includes the
hardware and software in order to form a system which can help the company to grow and
develop by adopting the advancement in the technology. Nowadays it is becoming very difficult
for businesses to survive without technology and therefore have to adopt better operations and
Management in their organization (Rajaraman, 2018). The following discussion is based on the
emerging Technology at impact analytics and business intelligence along with the decision
support, importance of location based analytics and the ways the analytics are powering
consumer applications and creating opportunities for businesses. Case study on big Data
analytics is also discussed along with the problems and challenges as per the case study and what
can be the solutions that can be drawn out in big Data analytics along with the principles of the
approaches used in the case study. reflection on the major learning taken away from this course
and the impact it may or may not play on the current or future learning practices is also discussed
with proper findings and conclusion.
1

MAIN BODY
Emerging technology that may impact analytics, BI and decision support
Emerging technologies chosen that can impact the analytics and business intelligence
along with the decision support in an organisation is the location based analytics. It is defined as
the analytics which uses the information which is placed on the which layer on a map in order to
interpret the areas of factors and demand which makes it easier to fulfil the demand. By using
this type of analytics the organisation can enhance the customer satisfaction by optimising the
use of resources and even in some cases they can also save lives. It is divided into two parts that
are the organisational oriented and consumer oriented in which they both are classified into
further two groups that is the geospatial static approach and location based dynamic approach.
Geospatial static approach in terms of organisation Oriental defines the examining geographic
size locations and in terms of consumer oriented defines the GPS navigation and data analysis.
Location based dynamic approach in terms of organisation oriented define the live location and
real time marketing promotions and in terms of consumer oriented defines the historical and
current location along with the dynamic analysis and healthcare social networks (Rosenkrans and
Myers, 2018).
Importance of location based analytics
Importance of location based analytics directly impacts the business intelligence and
decision support in the business such as it helps in enhancing the return on investment by
increasing the number of sales and provides the methodology of controlling the cost and renders
a cost efficient technique in operations and Management which assist in boosting the customer’s
satisfaction level to maintain the long-term relationships and loyalty with the customers.
Moreover, this type of analytics helps the business to find out the customer issues and better
investigation about the customer demand in the market along with the research methodologies so
that the better questionnaires can be prepared and analysis can be done with proper examination
and determination in an appropriate manner for better prediction and interpretation of data with
the help of location based analytics. The poet helps in serving the customers better by meeting
their expectations and delivering the promise and identifying the root cause of the customer
service issues (Lifna and Vijayalakshmi, 2020).
2

Ways the analytics are powering consumer applications & creating opportunity for businesses
Analytics are powering the consumer applications and creating opportunities for businesses
because they are helping the business to better understand their customers by evaluating different
campaigns along with personalized content and by creating the content strategies along with the
development of products. businesses are using analytics in order to boost their performance and
enhance their bottom line. This is because analytics supports the business in market research and
proper investigation of the customers’ demands as per the needs and requirements so that the
company can produce the products and services accordingly. Not only in the marketing, analytics
also supports the research and development department along with the information technology
and human resource along with the finance and operations department for better analysis of the
cost and budgeting along with the inventory management and logistics with skilled people and
strategic recruitment. Therefore, analytics is helping the business increasing the opportunities
and powering the consumer applications in the form of better operations and functioning of the
company (Huang, Gartner, Krisp and Van de Weghe, 2018).
Business intelligence & decision support & case study of big data analytics overview
Big Data analytics can be defined as the field of study in which the analysing is done in a
systematic manner in order to extract the information from the large amount of data sets which is
stored in a complicated manner and this is done by data processing application. The case study is
all about how big Data analytics has helped Luxottica improve its marketing effectiveness. It is
one of the leading international manufacturing company in the Italian eyewear conglomerate
eyewear industry headquartered in Italy. The case study is based on the improvement in the
marketing strategies of the company with the help of Big Data analytics and the specialised and
skilled people supporting the company in order to achieve the sales and marketing functioning
and department in an organisation. The following discussion is based on the relationship between
big data and the company along with the challenges faced by the company and the proposed
solution with the results (Ghani, Hamid, Hashem and Ahmed, 2019).
Problems and challenges in the case study of big data analytics
In the company, they have used big data which contains everything about the customer
interactions in the form of click streams and product reviews along with the transactions and the
social media postings. They were trying to grab the opportunity in order to constitute the source
of business intelligence for the products and services they are providing to the customers along
3

with the marketing and sales opportunities. Problems and challenges in the case study of Big
Data analytics for the company is that because of the outsourcing of promotional campaign
development along with the data storage and management by the company, defined the
disconnection between the marketing execution and the Data analytics. Moreover, they were
facing the lakh in competitive posture and strategic growth initiatives which has resulted in the
compromised situation of individualized view of the customers and capabilities to act in a device
and consistent manner on the areas of data and information generated by each and every retail
channel of the company (Silva, Diyan and Han, 2019).
Solutions to the problems in the case study of big data analytics
Solutions to the problem in the case study of big Data analytics is that the company has
developed the customer intelligence appliance from IBM business partner aginity llc. This is the
software which is developed on the pure data system for analytics by IBM. This is a proposed
solution which is generated by the company which supported the organisation to segment the
consumer behaviour in an appropriate manner and render the platform along with the smart data
bases for the execution systems which helps in marketing for example camping management
along with the email services and other kinds of direct marketing. Other benefits are such that
there is an enhancement in the marketing effectiveness by 10% along with the better
identification of the highest value of customers and appropriateness in the ability to focus on the
customers who are targeted based on the history and preference of the company's needs and
requirements (Saggi and Jain, 2018).
Principles of the approaches used in the case study of big data analytics
Principles of the approaches used in the case study of Big Data analytics involves the
different types of consideration such as a clear business need is important to identify to operate
the application which is introduced by the company. A strong committed sponsorship is highly
required for better capital and budgeting of the organisation. Company has aligned its businesses
and information technology strategies in an appropriate manner. They have created a fact based
decision making culture so that the proper process can be followed for judgement. They have
developed a strong data infrastructure which is strictly followed by the people who were
operating the software developed by the company for big Data analytics. They have imposed the
right analytics tools in their software and in their information technology department so that they
can be used in the right manner for better investigation. And the main principle is that the
4

company has approached the personnel with advanced analytical skills which means that hiring
the person who specializes in operating the software and they know how to handle the big Data
analytics in an organisation. Moreover, they have used the in-memory analytics for storing and
processing the complete data set in ram along with the in database analytics for placing the
process of analytics close to the data stored. They have also worked on the grid computing and
machines and processes in parallel which has supported them to combine the technical
appliances such as hardware and software along with their storage in a single unit for better
performance and scalability (Choi, Wallace and Wang, 2018).
Reflection on the major learning taken away from this course
I have taken a lots of learning from this course in the field of information Technology such
as the concepts of foundation of decision making, data warehousing, visual analytics beginner
and advanced, data mining beginner and advanced along with the proficiency, web mining model
based decision making, big Data analytics and emerging trends in business analytics. Moreover,
it has also helped me to explore the emerging technologies which impact the business
intelligence and analytics along with the decision support that is a location based analytics and
its importance. I have learnt about the different case studies based on all these topics especially
in Big Data analytics and investigated the problems and proposed the solutions along with the
results (Hariri, Fredericks and Bowers, 2019).
Impact it may or may not play on the current or future learning practices
These learnings have impacted my current and future learning practices in a more effective
and efficient manner so that I can apply this knowledge potentially in my career growth and
development and moreover in my personal life as well. I have learnt about the presentation and
leadership skills along with the communication skills which has helped me in time management
skills also. Problem solving and research skills along with the analytical skills can help me in my
current and future learning practices for my better career development in information technology
(Vassakis, Petrakis and Kopanakis, 2018).
CONCLUSION
It is concluded that information technology is an important concept to learn and study so that
it can be applied in real world organizations because nowadays Technology is advancing at a
very great pace and therefore the businesses are required to get updates and upgrades of the
5

technology they are using for better safety and security in their functioning. Therefore, it is
important to analyses emerging Technology that impact analytics and business intelligence along
with the decision support. It is essential to examine the importance of location based analytics
and it is necessary to determine the ways in which the analytics are empowering consumer
applications and creating opportunities for business. It is significant to gain the knowledge about
big Data analytics and review the case study so that the problems and challenges can be
identified and solutions can be drawn out in the case study of big Data analytics along with the
investigation on principles of approaches used in the case study for better assessment. reflection
is also made on the learnings from this course and its impact on the current and future learning
practices. hence this report covers all such areas in order to better understand the conception of
information Technology.
REFERENCES
Books and journal
6

Choi, T.M., Wallace, S.W. and Wang, Y., 2018. Big data analytics in operations
management. Production and Operations Management. 27(10). pp.1868-1883.
Ghani, N.A., Hamid, S., Hashem, I.A.T. and Ahmed, E., 2019. Social media big data analytics:
A survey. Computers in Human Behavior, 101, pp.417-428.
Hariri, R.H., Fredericks, E.M. and Bowers, K.M., 2019. Uncertainty in big data analytics:
survey, opportunities, and challenges. Journal of Big Data. 6(1). pp.1-16.
Huang, H., Gartner, G., Krisp, J.M. and Van de Weghe, N., 2018. Location based services:
ongoing evolution and research agenda. Journal of Location Based Services. 12(2).
pp.63-93.
Lifna, C.S. and Vijayalakshmi, M., 2020. Location-Based Alert System Using Twitter Analytics.
In Proceedings of the Third International Conference on Computational Intelligence and
Informatics (pp. 325-336). Springer, Singapore.
Rajaraman, V., 2018. Introduction to information technology. PHI Learning Pvt. Ltd..
Rosenkrans, G. and Myers, K., 2018. Optimizing location-based mobile advertising using
predictive analytics. Journal of interactive advertising. 18(1). pp.43-54.
Saggi, M.K. and Jain, S., 2018. A survey towards an integration of big data analytics to big
insights for value-creation. Information Processing & Management. 54(5). pp.758-790.
Silva, B.N., Diyan, M. and Han, K., 2019. Big data analytics. In Deep Learning: Convergence to
Big Data Analytics (pp. 13-30). Springer, Singapore.
Vassakis, K., Petrakis, E. and Kopanakis, I., 2018. Big data analytics: applications, prospects and
challenges. In Mobile big data (pp. 3-20). Springer, Cham.
7