Data Analyst

SHASHIKANTH DHANEKULA

+1-857-***-**** ** Beach Point Place, Boston, MA-02125 *********.**@************.*** shashikanth shashikanth EDUCATION

Master of Science in Engineering Management Sep. 2018 – Dec. 2020 Northeastern University, Boston, MA

Relevant Coursework: Data Warehouse and Business Intelligence, Computational Visualization, Data Mining, Data Management and Database Design, Engineering Probability and Statistics. Bachelor of Engineering in Aeronautical Engineering Aug. 2013 – May 2017 Visvesvaraya Technological University, Bengaluru KA TECHNICAL SKILLS

● Programming Languages : Python, C, PowerShell, R-Studio, T-SQL.

● Databases : MS SQL Server, Redshift, MySQL, Oracle, Vertica.

● Data Integration Tools : Azure Data Factory, SSIS, SSRS, SSAS, Talend, Alteryx.

● Data Reporting and BI tools : Tableau, Power BI, Looker, Google Analytics, Excel, Flourish.

● Cloud Technologies : Amazon Web services, Microsoft Azure, Snowflake, Discovery Cluster.

● Other Tools : PySpark, Airflow, Hadoop, Visual Studio, Pandas, NumPy, Matplotlib, GitHub, Docker. PROFESSIONAL EXPERIENCE

Data Research Volunteer Skunkworks, Northeastern University Aug. 2020 – Present

● Designed a Google Bot to handle queries using Neural Network, Python and used multithreading to interact with the backend system using REST API.

● Created complex SQL queries to support data modeling and transformations of large-scale data to enable data-driven decisions. Data Engineer CO-OP Wayfair, Boston, USA Jul. 2019 – Dec. 2019

● Worked on all phases of SDLC, from gathering requirements to testing, implementation, and support.

● Worked with cross-functional teams to structure problems, identify appropriate data sources, extract data and develop integrated information delivery business intelligence solutions.

● Automated ETL workflows in the data pipeline leveraging Python and MS SQL scripts to extract statistical data for reporting.

● Designed and implemented end-to-end solutions using advanced analytical and quantitative methods using Agile methodologies.

● Devised dynamic Tableau dashboards to track agent activity and KPI metrics for key technical and non-technical stakeholders.

● Worked on building a near real-time streaming pipeline using Spark. Data Analyst D.K. Enterprises, Hyderabad, India Jun. 2017 – Jul. 2018

● Spearheaded market research team resulted in a 10% increase in sales revenue. Forecasted inventory status using MS Excel.

● Led team of 3 to conceptualize and implement a sentiment analysis tool to extract the lowest price in the market using Python.

● Created a recommendation engine, to suggest an ideal cluster price in the market. It diminished 15% overall expenditure. ACADEMIC PROJECTS

Twitter Spam and Sentiment Real – Time Analytics Application (AWS, Apache Spark, Tableau) May 2020 – Jul. 2020

● Processed over 20 million tweets to identify spam bots and sentiments of trending events using Twitter API, AWS EC2 and S3.

● Constructed an NLP streaming platform to process real time tweets using Apache Spark streaming and Stanford NLP API.

● Formulated real - time streaming dashboard using Tableau to understand sentiments of trending events. Designing Healthcare Data Warehouse (MS Azure Data Factory, SSIS, Talend, MS SQL, Tableau) Jan. 2020 – Apr. 2020

● Designed and integrated a centralized healthcare data warehouse with over 2 million rows by pipelining data from diverse sources.

● Built an ETL pipeline for Data cleaning, Profiling, Archiving and Loading data into SOR’s using SSIS, Talend and MS SQL. Implemented Slowly changing dimensions and automated pipeline utilizing triggers and stored procedures in Azure Data Factory.

● Created OLAP cubes for reporting access and designed interactive dashboards to generate insights using Tableau. Airline Management System (MS SQL, SSIS, Data Modeling, Data Warehouse) Jan. 2019 – Apr. 2019

● Modelled a Multi-dimensional Star scheme database it stores information related to flight bookings, passenger information, etc.

● Developed and maintained ETL mappings for loading fact tables, aggregate fact tables, slowly changing dimensions and staging tables. Scripted CTE’s, Stored Procedures, column data encryption, correlated sub-queries, complex joins to apply business rules.

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