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3. Web Link

Link:    http://ec2-18-232-201-103.compute-1.amazonaws.com/#/home

4. About the Author

Debanil Majumdar is a senior business analyst and project lead and comes with a total of 4.5 years of professional experience and 2 years of extensive experience in Digital Aptech Private Limited. He has completed Master’s degree in Business Administration (Leipzig University, Germany) and B.Sc. & M.Sc. Degree in Computer Science. He has worked in IT industry for the entire career. He has vast experience in end-to-end program project management, requirements planning and management, requirements elicitation, requirements analysis and documentation, requirements communication, solution assessment and validation. He has worked in domains such as E-commerce solution for product based in B2C and B2B sector, WebRTC based online communication system, Online Banking system, Regression Analysis, Fractal Analysis, Logistic regression, Supervised Machine learning and Manufacturing and Sports Sector.

5. About the Domain

The subject discussed in this paper relates to the development and the challenges faced in the process of creating a property listing web & mobile application for our client, but the catch was to create an analytical rich application along with customized dashboard for each user based on their activity in the website also we were requested to create an activity tracker which would allow the site admin to create new marketing campaigns. This tracker is placed throughout the website. The primary objective of the Business Analyst team and Development Team is to provide research, analytical support, documentation for the implementation of this solution in Django Framework as backend and Angular 4 as frontend with MySQL database.

6. Context

As an Enterprise expands its business and adds IT systems, factors influencing the performance of the Enterprise become more distributed and dynamic. The biggest challenge for long-term growth of the property listing with advanced analytics Based solution for big & dynamic business is currently

• Ongoing service level and stability challenges with current platform
• Continuing delays in the deployment of a global model that supports the functions of the key features

In order to facilitate rapid growth from implementation purpose, usability purpose and ensure continued up-gradation, the Enterprise has partnered with the DAPL team:

• To develop the system in Django framework which is based in Python programming language and also using Angular frontend framework for parsing huge amount of data in a single page application.
• To be faster and more nimble along with proper scalability, robustness and security.
• For the analytics we have also used strong Python libraries like NumPy and Pandas to create the analytics and incorporate it into the website.
• We have also created, a supervised machine learning model for the lifestyle search option, where the users are matched along with the property pertaining & matching to their lifestyle.

It is the ability to adapt to changes rapidly and smoothly, which decides success of a business.

7. Responsibilities of the DAPL Team

A significant responsibility of the DAPL team is to assure that the business analysis artefacts are prepared with the highest level of quality.

DAPL needs to assume leadership in formalizing the expected quality, format, and presentation of the artefacts. Such a levelling of quality is approached initially through training and the creation of artefact templates. In addition, standardization of all tools used by the Business Analyst increases the levelling of quality. Furthermore, support of projects by the DAPL team ensures that the same care and level of professionalism are applied to all the projects within the organization. Finally, assistance in conducting post-project retrospectives allows the DAPL team to discover the areas where there are scopes for betterment, resulting in continuous quality improvements:

DAPL Team Workflow:

• Facilitate management of complex and dispersed business ideas through a single Business Requirement Document (BRD)
• Well adaptation of cross-functional environments, where geographical diversity is the key issue
• Focused solution approach, helping Enterprises to strategically control information, thereby improving the performance
• Sharing of information in a well-defined and controlled manner
• Improved documentation on information and better tracking updates on processes and assigned tasks
• Accountability and follow through on assigned goals and action plans
• Better coordination of work efforts, with reduced errors and schedule slippage
• Better inter-team as well as intra-team interactions and leveraging improved sharing of information, communication and team management
• Streamlining business processes to meet objectives and timelines
• Assisting in pre-sell launch of products, facilitating the calls, meetings and much more
• Support beta testing, application testing, and end user testing in the following ways:
  • Outlining the UAT strategy planning
  • Designing test cases: Test cases are designed to cover all the functional scenarios of the software in real-world usage. They are designed in a simple language and manner to make the test process easier for the testers
  • Executing test cases and documenting: The testing team executes the designed test cases. Sometimes they also execute some relevant random tests. All bugs are logged in a testing document with relevant comments
  • Bug fixing: Responding to the bugs found by the testing team, the software development team makes final adjustments to the code in order to make the software bug-free
  • Sign-off: When all bugs have been fixed, the testing team indicate acceptance of the software application. This shows that the application meets user requirements and is ready to be rolled out in the market
• Define graphs/charts for volume projections and data analysis
• Follow the development process – Ideation, Conceptualization, Approval, Implementation

8. Development Process

For Web Development:

• Language: Python
• Framework: Django
• Database: MySQL
• Frontend: Angular 4

For Data Analysis:

• Language: Python
• Framework: MySQL
• Database: NumPy, Pandas
• Frontend: D3JS

9. Challenges Faced

• No Developers were provided initially, so the work got delayed
• Client was not satisfied with the design
• Getting the collection on time for the Sales team
• Building and integrating real time user activity tracker
• Fetching data using the activity tracker and creating real-time analysis
• Building the user Dashboard completely customized in accordance with the user activity and behaviour
• Creating a Machine Learning Algorithm to match the buyers with their perfect lifestyle homes

10. Extensions Used

• BING MAP SDK - To create the drawing over the map and getting the area and the listed properties
• Rest was custom development

11. About the Customer

The customer is the owner of a leading Real Estate Listing website where one can search for the properties they are looking for. It implements advanced analytics and a customer-oriented analytical dashboard, making it easier for them to search properties.

12. Customer/Client Partner Feedback

• DAPL Deliverables :    Consistent and quality deliverables in development mode. Client is extremely satisfied with DAPL deliverables till date.

• Feedback on DAPL Team :    Client is satisfied with current DAPL team performance. Client would like to consider DAPL as a preferred partner for their future needs.

• Future Plans and Opportunities :    Depending on expansion for Enterprise, BA engagement has high visibility. Will need to consistently manage the Client expectations.

• Risks :    No risk in terms with current Magento 2.x perspective, only issue with proper stability from Magento 2 support team, so that the version two in community edition is stable and error free.

13. Acknowledgements

I would like to thank my clients Mr. Troy Fernandes, Rajat Kodali (VP – Web Division), Abhisek Roy, Tiotama Mitra, Dipankar Halder, Jeet Ghosh, Sima Kundu and all my team members for encouraging me to write this paper, providing their guidance and their valuable comments which have helped me in expanding my knowledge.

14. References

• https://www.djangoproject.com/
• https://www.realtor.ca/
• https://en.wikipedia.org/wiki/Analytics
• https://docs.python.org/3/tutorial/