Abolfazl Madani

Led data warehouse design project to achieve data infrastructure and support business growth, reduced query response time by 40%. Leveraged data science and business intelligence skills to drive data-driven decision making across the organization, utilizing technologies such as Superset, PowerBI, MariaDB, and Google Analytics. Developed and implemented data analysis solutions resulting in a 30% in

Managed ETL & ELT from 3rd party APIs (more than 10 pipeline). Designed an ETL and dynamic for fetching data with python that optimized 19% of daily scheduling. Designed data modeling for NoSQL database (MongoDb) for 2 Datawarehouse. Worked with SSIS (SQL Server Integration Service) for automating ETLs.

Appointed as a Project Manager with sufficient technical knowledge. Designed a recommendation system for an online bookstore that utilized collaborative and semantic analysis based on customer activity in semi-social media on the website and book-following patterns to suggest better books aligned with their interests, thereby improving customer engagement and audiobook sales. Conducted research on

Managed transactions and customer activity for over 10M customers. Designed successful parts of data warehousing, B2B reports, and coding some of the pipelines with 6 technologies. Developed B2B reports based on third-party data models and updated or upsert daily. Created near to 20 reports for C-levels and managers in the start-up.

Part of the team that successfully launched new Business Intelligence with ODI, OBI. Redesigned reports and managed 4 years of data in less than 6 months. Created a new RFM (recency, Frequency, Monetary) with a machine learning method that improved the achievement of business and marketing scenarios. Prepared OKR (Object Key Results) reports weekly. Created a CDC (Change Data Capture) with debeziu

Performed sentiment analysis on app comments, improved analysis 30% more than ever. Created a pipeline to fetch comments from apps. Designed a sentiment analysis customized with 4 classifications based on application category, it improved 35% of marketing brand.