Data Analyst Business Intelligence

HARI PRASHANTH SUBRAMANIAN DATA ANALYST

Location: Cleveland, OH Email: ***************@*****.*** Phone: +1-216-***-**** LinkedIn SUMMARY

A Data Analyst with over 4 years of experience across all SDLC phases, I excel in designing, developing, and maintaining complex data warehouse applications. My expertise spans data modelling (star/snowflake schemas), various database platforms

(Oracle, SQL Server, etc.), ETL development, business intelligence, and communication with stakeholders. I leverage strong leadership and data modelling tools (ERwin, Power Designer) to deliver results. SKILLS

Data Warehousing Informatica, SSIS, Data Stage 8.x, Oracle, MS SQL Server, UDB DB2, Teradata, MS Access 7 Reporting Tools Business Objects6.5, XIR3, Cognos 8 Suite Data Modeling Star-Schema Modeling, Snowflake-Schema Modeling, FACT and dimension tables, Pivot Tables, Erwin

Testing Tools Win Runner, Load Runner, Test Director, Mercury Quality Center, Rational Clear Quest RDBMS Spring, Spring boot, Spring MVC, Hibernate 3.0, Django and Flask Programming SQL, PL/SQL, UNIX Shell Scripting, VB Script Software: Git, GitHub, Jira, Postman, IDEs (IntelliJ and Eclipse) and MS Office Suite Build Tools Maven, ANT

Methodologies: SDLC, Agile and Scrum

Other Tools TOAD, MS-Office suite (Word, Excel, Project and Outlook), BTEQ, Teradata SQL Assistant EDUCATION

Master’s in Information Technology and Management Aug 2021 –May 2023 Cleveland State University,

GPA -3.83

Bachelor of Engineering in Information Technology Aug 2013 – May 2017 Acharya Institute of Technology, India

GPA – 3.68

EXPERIENCE

ACL Digital

Data Analyst Jul 2023 – Current

I designed and implemented complex MySQL queries (correlated subqueries, window functions, CTEs) to extract and analyse user activity data.

This data encompassed metrics such as retention rate, daily active users, and user behaviour patterns.

Eliminated 30% of duplicate records after rigorous data cleansing, boosting data accuracy

Maximized company profit by 10% through predictive analysis on sales data

Expedited report generation process via SQL scripts automation, reducing time spent by 15%

Harnessed Python for business process automation, resulting in cost savings of $50,000 annually

To automate daily reporting tasks and ensure data accessibility, I constructed efficient data pipelines. These pipelines. Utilized user-defined functions and stored procedures within the MySQL database. I created clear and informative dashboards in Tableau, effectively communicating insights on KPIs and product performance.

These dashboards integrated data from diverse sources including MS Excel, AWS platforms (S3, RDS, Redshift), JSON, and XML. I identified underperforming user segments through data analysis and designed targeted A/B testing strategies.

This involved crafting relevant metrics, monitoring test processes with Tableau dashboards, and interpreting test results to recommend actionable improvements for user experience.

I explored advanced statistical techniques like hypothesis testing, causal inference, and Bayesian analysis to extract deeper insights into user behaviour. Additionally, I developed and implemented machine learning models (Random Forest) using SparkML and Python to predict customer churn. Employer: Clairvoyant, India

Data Analyst Mar 2018 – May 2021

Analysis of functional and non-functional categorized data elements for data profiling and mapping from source to target data environment. Developed working documents to support findings and assign specific tasks Involved with data profiling for multiple sources and answered complex business questions by providing data to business users.

Worked with data investigation, discovery and mapping tools to scan every single data record from many sources.

Performed data mining on Claims data using very complex SQL queries and discovered claims pattern.

Created DML code and statements for underlying & impacting databases.

Extensively used ETL methodology for supporting data extraction, transformations and loading processing, in a complex EDW using Informatica.

Perform data reconciliation between integrated systems.

Metrics reporting, data mining and trends in helpdesk environment using Access

Written complex SQL queries for validating the data against different kinds of reports generated by Business Objects XIR2Extensively used MS Access to pull the data from various databases and integrate the data.

Performed data analysis and data profiling using complex SQL on various source systems including Oracle and Teradata.

Responsible for different Data mapping activities from Source systems to Teradata

Worked in importing and cleansing of data from various sources like Teradata, Oracle, flat files, SQL Server 2005 with high volume data

Boosted website conversion by 15% via trend analysis on user behavior data

Innovation drove business insight generation, reducing decision-making period by 40%

Leveraged Tableau to create compelling dashboards that enhanced internal data visualization NOTABLE PROJECTS

Tourism Recommendation System

• Led the development of an advanced web-based recommender system utilizing Django, PostgreSQL, Visual Studio, and Python. Enabled tourists to input preferences and receive tailored place recommendations with a user feedback mechanism.

• Implemented an intuitive user interface for seamless data entry, employing sophisticated algorithms to generate personalized travel suggestions based on user-specified location types and countries.

• Integrated a robust feedback mechanism for user reviews on recommended places, driving continuous improvement of the recommendation engine which led to 30% increase in user engagement Video Games Sales Prediction R Studio

• This project aims to utilize gaming data to enhance sales predictions for video games.

• Implemented diverse machine learning methodologies, including linear regression, support vector regression, random forest, and decision trees, to scrutinize sales patterns across genres, publishers, and platforms in distinct geographical regions.

• Identified superior machine learning algorithms yielding precise predictions and minimal error rates for video game sales forecasting.

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