Nirvign Web Solutions, Jaipur, Raj.
Internship Progress Report: February
Intern Name: Mansi Sanadhya
Internship Position: Data Analyst Intern
Duration: 1st February to 29th February
Introduction: I am pleased to provide an update on my progress during the
second month of my internship as a Data Analyst. Over the past month, I have
continued to build upon the skills and experiences gained in the first month,
actively contributing to projects and furthering my development as a data analyst.
Objectives:
Consolidate and apply skills learned in the first month to real-world projects
and tasks.
Expand knowledge and proficiency in data analysis techniques and tools.
Demonstrate continued growth and contribution to the team's objectives.
Activities Completed:
1. Project Execution and Delivery:
My first job as an intern was to familiarize myself with the literal
hundreds of tables they have in their database. I need to know what
each table is used for, how to use it and how to integrate it with other
tables. Here, I realize that data understanding plays an enormous part
in the data science process.
Another of my tasks in this internship was to make weekly
dashboards. Each chart in a dashboard is built by a SQL script. Hence,
in-depth knowledge of SQL is crucial.
Participated in the execution of data analysis projects, including data
cleaning, preprocessing, analysis, and visualization.
Worked closely with team members to deliver high-quality reports,
dashboards, and insights to stakeholders.
2. Advanced Technical Skills Development:
Advanced Querying Techniques:
i. Subqueries: Learn about nested queries within SQL statements,
including correlated and non-correlated subqueries.
ii. Common Table Expressions (CTEs): Understand how to use
CTEs to create temporary result sets for complex queries.
iii. Window Functions: Explore powerful analytical functions like
ROW_NUMBER, RANK, DENSE_RANK, and NTILE for performing
calculations across rows in a result set.
Performance Tuning and Optimization:
i. Indexing: Learn how to create and use indexes to improve
query performance, especially for large datasets.
ii. Query Optimization: Understand techniques for optimizing SQL
queries, such as query rewriting, query hints, and using
execution plans to identify bottlenecks.
3. Problem-Solving and Decision-Making:
Faced challenges in data analysis tasks and problem-solving,
collaborating with team members to overcome obstacles and find
creative solutions.
Participated in discussions and decision-making processes, providing
input and recommendations based on data insights and analysis.
Challenges Faced:
Managing the complexity of advanced data analysis techniques and
machine learning algorithms required additional time and effort to fully
grasp and implement effectively.
Balancing the demands of multiple projects and deadlines challenged my
time management skills, but I prioritized tasks based on their importance
and impact.
Skills Developed:
Strengthened my SQL skills so as to write efficient and better codes.
Strengthened my ability to interpret and communicate complex data
insights to non-technical stakeholders through visualizations and
storytelling.
Expanded knowledge of data visualization tools and techniques, exploring
advanced features and customization options.
Worked on my individual project and built Customer Behaviour analyser as
a precursor to my main project, “User Engagement Evaluator”
Conclusion: In conclusion, the second month of my internship as a Data Analyst
has been a period of significant growth and learning. I am grateful for the
opportunities to apply my skills and contribute to meaningful projects within the
organization. I look forward to continuing to learn, grow, and make valuable
contributions to the team in the remaining months of my internship.
Rashmi Shrivastava
(Project Mentor)
