Stefanini
Current Position: Power BI Analyst MAR 2022 - Present- Developing dashboards and indicators with Microsoft Power BI.
- Developing ETLs with Pentaho Data Integration.
- Developing scripts in the R language.
Postgraduate student in the MBA in Data Science and Analytics, addressing the topics data science, analytics, machine learning, modeling, big data, data mining, IoT, web crawling, deep learning and data architecture, relating them to main issues of strategy, business models, technologies and decision making, always focusing on the fundamentals, concepts and practical applications through studies and applications of real cases and market datasets.
Graduated in the Bachelor's Degree in Software Engineering. Monitoring in Object-Oriented Programming in Java and Calculation.
Ability to implement data engineering solutions using the Microsoft Fabric platform. Data ingestion and transformation. Protect and manage an analytics solution. Monitor and improve an analytics solution.
Deliver significant business value through easy-to-understand data visualizations. Empower others to perform self-service analytics. Deploy and configure solutions for consumption. Transform the data. Create data models. Visualize data. Share assets.
Learn to analyze data with R and Python, using Azure and Spark as a framework. Learn how to collect and store data from different sources using Hadoop, Hive, HBase and Spark. Apply data analysis in business areas, defining metrics and collecting insights and presenting the results with visualizations and dashboards.
Relational and Dimensional Models: Postgresql. NoSQL: MongoDB and Redis. Batch processing, with Hadoop, Sqoop, Hive and Pig. Ingestion of Data with Flume. Real-Time Processing with Spark and Streaming Data with Spark Streaming. General Aspects: Projects and Risks. Course Linux basics.
Scrum Foundation Professional Certificate. Basic skills in scrum that endorse the fundamental knowledge in this structure, definitions and main functions. The Learning Objectives for this certification are based on: Scrum Guide, 4 values and 12 principles.
Remote Work and Virtual Collaboration Certification.
Business Intelligence - BI, Pentaho Data Integration - PDI (Kettle), Spoon, ETL, DW, PostgreSQL, SQL Server 2017.
Creation and presentation of graphic panels and indicators with Microsoft Power BI.
Different visualization techniques and tools to tell the story of data analysis. Main Topics: Presentation Techniques; Design Thinking; Visual Organization; Dashboards and Graphs; Visualization Tools
Learning in building Machine Learning models, studying machine learning theory, developing Machine Learning skills in Python and R languages.
Application of analytical techniques in business areas such as Marketing, Finance, HR and Supply Chain, collecting data, defining metrics, creating models and extracting insights that generate value for companies and support decision-making.
How to create and configure a Hadoop cluster, apply mapping/reduction techniques on data, create a Data Hub with Hadoop and HBase and apply ETL to load Hadoop data.
Study of data analysis techniques, in batch and in real time, with two of the main tools used by Data Scientists: Python and Apache Spark.
Study of statistical data analysis techniques and Machine Learning with two of the main tools used by Data Scientists: R Language and Microsoft Azure Machine Learning.
Study of one of the many ways to obtain Big Data: Web Scraping. “Web Scraping” is a programming technique for copying data from web pages, which can then be used in the analysis process and cross-referenced with internal company data
Java OO, UML, JDBC, JavaFX, Spring Boot, JPA, Hibernate, MySQL, MongoDB.