First Day of Learning Data Analysis : My Diary

Learning a new skill always keeps you in a good position to start a new career. I am going to make this my diary book to see how far I can go in 3 months' time. I would publish content that fits in the community, and I can keep track of my progression.
So, this is the series Becoming a Data Analyst—I
On my first day, my instructor provided me questions to understand and empathize with the understanding so far to be able to relate with data analysis.

freepik

Question:

Neo Payment Gateway is going through the listed issues; on that behalf, give a hypothetical solution to the problem.

Datasets:

The solved questions and answers were solved with the initial understanding and not on the basis of research:

Core Business Problem of NeoPay:
The entire business has failed in day-to-day operations. This could also happen with a shortage of staff and deviation in company mission, and methods.
Additional problems can be associated with budget, human resources, and client-business relationships. (Finance-Technology-Operation)

KPI Analysis:

• Understand and analyze the reasons for failed transactions.
• Check, monitor, & give feedback on day-to-day Onboarding Activities
• Analyze the Cost per engagement/advertising for daily active users.
• Reconstruct the operational expenses and monitor the spending every fortnight.
• Analyze the requirement of the Responsive team to interact with customers per day.
  
  
  Prepare Questions for Stakeholders:

1. What were your expectations with the application and how far have you come? (Deviation)
2. How are you seeing the project for the future? What are your thoughts on current working methods inside the organization?
   
   
   Create a hypothetical scenario of your understanding and solution to the problem.

Application Functionality & Usage

• Hypothesis:
  The application lacks multi-feature engagement, impacting customer retention.
  UI/UX is not standardized according to the user base.
  Data Needed: Users – Transactions – App Events
  Checks: Device OS, Device type, Age, City, event_type
• Recommendations:
  Action: Improve UI and add additional features like e-marketplace
  Why: Multiple services aligned with business increases daily active users.

Transactional Issues

• Hypothesis:
  This issue could be associated with the cloud server and database.
• Data Needed: User, Transactional
• Checks: User_id, Txn_id, Txn_amount, add money, withdraw,
  Recommendations:
  Action: Decrease Batch processing and Build Robust Database Server
  Why: Zero Transactional Error Tolerance for the application.
  **
  Customer Support Ticket
• Hypothesis:
  Delayed Transactions - Batch processing has increased.
  The app's in-built feature lacks ease of use in respect to UI and UX for users.
• Data Needed: User, Transactions, App_Events
• Checks:
  User_id, Txn_id, txn_date, Error_code , events_Device OS_ , Txn-amount, app_events, issue, type
  Recommendations:
  Action: Add more human resources or AI bots/automation to tackle the customer support
  Why: Prompt Responsive Interaction with the user.

Onboarding:

Manual KYC verification—loss of Leads
Team support and human resources are inadequate.
Data Needed: Users, Transactions
Checks: signup_Data, kyc_update, issue_type
Recommendations:
Action: Automated KYC verification/increase click per engagement on spending.
Why: Onboarding easy quick, and access for service to users get quick

The context is shared to understand and connect with the possibilities I could gather when I re-see it after 3 months and then analyze different contexts to keep my point of view. I will share this diary with my instructor as well.
Please, feel free to share if you have any feedback.

Regards.

Posted Using INLEO