Project Work Answers of General Data Management Operations

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MIS609 Data Management and Analytics
Name:
University:
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Table of Contents
Introduction: ………. …

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MIS609 Data Management and Analytics
Name:
University:
Page 2 of 11
Table of Contents
Introduction: …………………………………………………………………………………………………………………… 3
Kind of data that would be managed by the organisation: …………………………………………………….. 3
Management strategy: ……………………………………………………………………………………………………… 3
General data management operations: ……………………………………………………………………………….. 4
Number of staff members and team hierarchy: ……………………………………………………………………. 4
Required resources from the retailer: …………………………………………………………………………………. 5
Deliverables to the retailer: ………………………………………………………………………………………………. 5
Data management policy and implementation plan: …………………………………………………………….. 6
Management plan for metadata and data quality: ………………………………………………………………… 6
Auditing plan for data management practices: ……………………………………………………………………. 6
Process of collecting user and business requirements from the clients: ………………………………….. 7
Data architecture and platforms to be used: ………………………………………………………………………… 7
How would legacy data be taken care of: …………………………………………………………………………… 7
Process of managing the risks: ………………………………………………………………………………………….. 8
Benefits that the retailer will be having as a result of outsourcing this service to your
organisation: …………………………………………………………………………………………………………………… 8
Conclusion: ……………………………………………………………………………………………………………………. 9
References: …………………………………………………………………………………………………………………… 10
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Introduction:
The purpose of this paper is to propose a data management and analytics plan for Slow fashion
which is a fast growing retailer of cloths. The organisation is doing their busing traditionally
from physical stores as well as they are having a fast growing online platform based business.
The management strategies for the entire business will be proposed in this paper. Along side that
the data management policy and implementation plan will be also discussed in this paper.
Kind of data that would be managed by the organisation:
As the company named Slow Fashion Pty Ltd one of the fastest growing online business as
clothing retailer. They are also having 50 outlets in all over New Zealand and Australia as well
as they are getting a sale of 500 per day in their online store. As they want to focus on the online
business the customer data along with the most searched products should be analysed so that
they can focus more on the online platform (Yoboue, Yi, & Antwi, 2018). For that SEO methods
will be suitable enough as they will need to review with the other competitors too. Google
analytics can be used to get a better result about the mentioned things from the site.
Management strategy:
The organisation can utilize strategic data management which can allow the organisation in
managing their data proactively for helping to deliver on the business objectives. The
organisation can utilize data analysis with tools like power BI or tableau for identifying and
predicting which offerings will better suite for the consumer needs in future. A better
understanding about the customer requirement and expectations will also increase the consumer
satisfaction and retention and as the result the ecommerce business will grow for Slow Fashion
Pty Ltd. The relevant sources for the big data will include costing of the products, offers of other
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competitors, prices of them, sales data, stock level, all of the possible aspects for advertising and
last but not he least the consumer data. Finding the right technology and identifying the business
growth will help the organisation in creating billions of data points per day.
General data management operations:
For the growing of business in online section, the data management will be needed to be
included with the software tools for management (Yoboue, Yi, & Antwi, 2018). The data should
be managed in such as way so that the business will be able to pinpoint the possible consumers
as well as can determine the strategies for pushing them through the sales funnel on the basis of
the information that is already in hand. The operations will help organisations and people and
connected things to optimize the usage of data for making better and informed type of decisions
which will yield maximum number of benefits.
Number of staff members and team hierarchy:
As the organisation is having around 50 stores in two countries and along side that they are
moving towards the online ecommerce section so they will need a large number of team
members. However, there will be different roles and responsibilities for the staffs and members.
The operations will be done in both ways. There will be 2 operational managers in both online
and offline operation. They will be having roles to manage the entire process of offline and
online process respectively. The staff members required for the organisation will be:
Director of eCommerce.
Web Developer.
Digital Operations Manager.
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IT Technician.
Logistics Manager.
Inventory Manager and Team of Inventory Associates.
Digital Marketing Manager.
Customer Service Representatives.
Required resources from the retailer:
The retailer is having a huge number of existing customers as well as the retailer growing base
for online consumers too (Mki, & Toivola, 2021). The organisation has planned to outsource
data management functions for the reputed organisation which is capable to manage their own
data. The retailers will supply products to the online platform as well as to the offline stores so
that the customers can get all products from anywhere they want.
Deliverables to the retailer:
The offline stores will remain the same as they were operating however in each of the offline
store there will be a system which will keep track about the stock of products so that when
buying online the customers will not be having any issues. The customers will place the order
online and then the order will be confirmed from the nearest stores of customer location else it
will be confirmed from the store where stock is available (Eine, Jurisch, & Quint, 2017). After
confirmation the customer will need to make the payment and provide the address for shipping.
Then the logistic team will pick the product from the retailer and payment will be done to retailer
as well.
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Data management policy and implementation plan:
The data management policy will describe the rules to control the integrity, quality, security and
utilization of data during the state change and life cycle. The data management policy will be
included with the understanding about the business process, security level, values and risks for
the staffs as well as for the consumers as well (Eine, Jurisch, & Quint, 2017). The role of data
management system will be needed to be defined as well as the data quality will be needed to be
ensured. The customer data and payment data should be encrypted so that hackers cannot get
access to that.
Management plan for metadata and data quality:
Good quality of data is started with meta data as it can characterise data by providing
documentation such that the data can be understood as well as it can be consumed readily by the
organisation (Geetha et al., 2021). The metadata will need to provide answers for who, what,
when, where, why, and how questions for identifying the users of data.
Auditing plan for data management practices:
The preparation of a quality audit is consisted of three major stages such as preliminary activities
that will be involved with finding about the company, senior management team and industry.
There will be several operations which will be included with the audit plan such as:
Analysis of organisational data for better improvement in online sales.
Accessing data management and reporting for online retailers (Mahmud et al., 2021).
Helping to check the ability of the system for collecting and reporting data.
Checking if proper system for data quality management is applied to the system or not.
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Process of collecting user and business requirements from the clients:
The requirement gathering is actually the procedure to determine the needs and requirement of
the project for the business. The process of collecting user and business requirements will be:
Establishing the goals and objectives for the project.
Documenting each and every activity of requirement elicitation.
Be transparent while making the documentation of requirement (Permatasari, & Kuswadi,
2017).
Taking to the right users and stakeholders for online operations.
Assumptions should not be made about any of the requirements.
Data architecture and platforms to be used:
The data architecture platform will design a comprehensive type of computer system to store,
deliver and optimize a variety of information usually in the online based format. For the data
analysis SAP can be used, and for analysing the customer data and SEO google analytics will be
needed to be used (Mki, & Toivola, 2021). Amazon AWS will be needed to be implemented as
cloud platform. Data integration will be needed to be implemented for measuring data
interactions among two or more data systems.
How would legacy data be taken care of:
For taking care of legacy data a web based security archiving tool will be needed to be
implemented so that customer records, order details, payment details can be retained. The
systems should not be modernized ahead of the curve (He et al., 2020). For reutilization the
business logic will be needed within the systems. A digital backbone will be needed to be built
for servicing architecture.
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Process of managing the risks:
For the management of cyber risks a firewall will be needed to be implemented in the system.
The Firewall will detect all the unauthorised activities and after that it will block them for
making the system secured. The process of managing risks are:
Applying fraud screening.
Building internal fraud prevention (Yoboue, Yi, & Antwi, 2018).
Focusing on risk reduction
Developing essential website content.
Benefits that the retailer will be having as a result of outsourcing this service
to your organisation:
The retailers will be having several benefits as a result of outsourcing this service to the
organisation such as:
Overcoming the geographical limitations.
Gaining new consumers along with visibility of search engine.
The cost will be lower.
Locating the products in quicker ways.
Eliminating the time and cost of the travel.
Providing comparison for the shopping (Zope et al., 2021).
Enabling deals, coupons, bargains as well as group buying options for better sales.
Providing abundant information.
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Conclusion:
Thus, it can be stated from the report that a data management strategy has been created for the
company named Slow Fashion Pty Ltd. It can be assumed that after following this strategy the
organisation will be able to grow their business in online ecommerce section. The importance of
data can be seen across all of the areas in the business which will ensure about the business for
making a positive impact.
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References:
Eine, B., Jurisch, M., & Quint, W. (2017). Ontology-based big data management. Systems, 5(3),
45.
Geetha, V., Gomathy, C. K., Charan, K. S., & Koushik, M. A Secure Based Preserving Social
Media Data Management System.
He, G., Yang, Y., Jiang, Z., Kang, Y., Liu, X., & Lu, W. (2020, August). Implicit Products in the
Decentralized eCommerce Ecosystems. In Proceedings of the ACM/IEEE Joint
Conference on Digital Libraries in 2020 (pp. 451-452).
Mahmud, B. U., Bose, S. S., Majumder, M. M. R., Arefin, M. S., & Sharmin, A. Ecommerce
Product Rating System Based on Senti-Lexicon Analysis.
Mki, M., & Toivola, T. (2021). Global Market Entry for Finnish SME eCommerce
Companies. Technology Innovation Management Review, 11(1).
Permatasari, A., & Kuswadi, E. (2017). The impact of social media on consumers’ purchase
intention: A study of ecommerce sites in Jakarta, Indonesia. Review of Integrative
Business and Economics Research, 6, 321.
Yoboue, W., Yi, K., & Antwi, M. O. (2018). An Empirical Analysis of Ecommerce Adoption in
Cte d’Ivoire Using an Extended UTAUT Model. American Journal of Multidisciplinary
Research, 7(1).
Zope, L., Yadav, R., Yadav, N., Pandav, A., & Bhopatrao, D. (2021). Sentiment Analysis of
Ecommerce Website.
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