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Gaston-Portfolio

BI & Data Analytics Portfolio

BI & Data Analitics; Data Analytics Portfolio

👋 Hi, I’m Gaston Lucca

I’m a Business Intelligence and Data Analytics professional with experience in building data pipelines, dashboards, and actionable insights using tools like Tableau, Power BI, and QlikView.

Project 1: DataBase & BI reporting: Project Overview

  1. Definition of reporting tool
  2. Definitions of KPIs
  3. Definition and elavoration of the dashboard, regular reporting, and ad-hoc reporting
  1. Data gathering porcess and normalization
  2. ETL procces
  3. Database estructure: variables – dimensions, define transactional tables, schemas (star)- data types
  4. Data base Wharehouse – site – back up - testing
  5. Data Visualization on Qlick View and PowerPoint

Project 2: Analysis of trends and metrics for La.Radio.live

For this project I have select and define a series of metrics, relevant to analyze the performance of the Facebook site for the company, LaRadio.live

Gathering all this information I was able to summary the performance of the Facebook site, estimate by linear regression the future like level. Through this analysis I have generated actionable conclusions and extraction of actionable insights, in order to calibrate the marketing strategy of the company.

Broadcasting Performance:

Broadcasting Performance

Project 3.1 (Tableau): Support Function Cost Automation: Objetives, Estructure & Dashboards

  1. To improve collection, preparation and display of data to promote a change in financial analysis department.
  2. Automatization of process that it is been build from different sources (SAP ERP, ORACLE, manual settings, local files)

Project 3.2 (PowerBI): Support Function Cost Automation + Sales: Objetives, Estructure & Dashboards

  1. To improve collection, preparation and display of data to promote a change in financial analysis department.
  2. Automatization of process that it is been build from different sources (SAP ERP, ORACLE, manual settings, local files)

Mobile expenses by Business Unit.

Sales by Business Unit

Project 4: Finances BI Report: Project Overview

  1. Provide to the finances department a BI solution in order to improve the collection and display of data
  2. Improve data visualization and analytics through Tableau

Note: WIP

Project 5: Deploying BI solution & Advanced analytics with IDS - AWS + Tableau

  1. Definition of Use case (Agile / kanva methodology)
  2. Business/Data Analysis + prioritization: How to solve the use case and how we prioritize the backlog
  3. Data Architecture: What is the data architecture I need to resolve this problem
  4. Definitions of KPIs, business rules, data quality rules, Critical data elements
  5. Deploy data governance: to guarantee that the technical solution is in compliance with the company data strategy (Dat quality, tools, data security)
  6. Development part: Coding (Scrum master methodology) + UAT + delivering the model
  7. Definition of the dashboard, regular reporting, and ad-hoc reporting
  1. Data gathering process and normalization
  2. ETL process + data ingestion
  3. Database structure: variables – dimensions, define transactional tables, schemas (star)- data types
  4. Database Wharehouse – site – back up - testing

Note: WIP

Project 6: Deploying Data Governance base on DCAM approach

Note: WIP

Project 7: Data Architecture for quotation model

  1. Data research to create a quotation model based on SAP
  2. Data ingestion and analysis
  3. JOIN STATEMENT identification on SQL code
  4. Data architecture to be programming on a ETL software (Power Center/ Informatica Cloud /SnapLogic)
  5. Designing the data schema nad architecture

Target Tables - Source tables - SQL JOIN STATEMENT

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Project 8: Machine Learning model- recommendation system for the sales team

  1. Scoping and flameworking the problem statement: use case elaboration
  2. Data Reserach and exploration: exploring the data available on the database level and data sources
  3. IT architecture for scalable machine learning models: what is the right IT architecture to scale models?

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Note: WIP

Project 9: DDH Hackathon

Goal: Working on a managerial reporting solution that will improve the company’s strategic plan follow-up and the KPIs tracking, through the improvement of the KPI definitions, process automation on data gathering, and data visualization.

Software used:

1) Business data analyst & technical approach- Top down

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2) Business data analyst & technical approach- From data to KPI (bottom up) image

3) Example of KPI mesurement: reduce the technical debt by 30 % image

Note: Due data security privacy i can not show the final dashboards Note: WIP

Project 10: Artificial Intelligence Hackathon (Winner)

Problem statement: ​Digital Customer Support has identified duplications in Articles and Documents, which hinder customers from easily finding specific solutions to their issues or searches.

Goal: Our objective is to develop a sustainable solution aligned with Schneider data standards that compares Articles, Documents, and Links, providing accurate similarity scores based on title and responses comparisons.Additionally, use case-oriented visualizations will highlight potential duplicates, assisting agents in the analysis and optimization of the content.

SaasS Plataform: Dataiku

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Librari: Faiss library

Data source analysis: Analysis of the Data Source reveal that Data source is unstructured and risks of Word-to-Word comparisons because of the dependency of the Content and Technical Specific.

Solution: Steps of the solution includes the following actions: Data Preparation, Data Validation, LMM, Reporting and Visualisation. (Dummy Data)

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Visualization: Developed on Tableau (Dummy Data)

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Benefits the model model : Gives detailed matrix after one iteration of SS calculation

Using LLM we save the Context impact.

Flexible Threshold defined by user

Give the pool of similar FAQs biased SS and on FAQ related.

Extract the FAQ if they are connected and allow fast access to online check

Risk Avoided: Word-to-Word comparison lose the Context.

All Experts to use it as interface to make a final validation.

Scale up & Next steps image

Note: WIP

Project 11: Digital Data Analitics Sales Products

Product 1: Greenberry

What is ? Greenberry+ is a Business Intelligence Tableau Dashboard that showcases Sales-related Data collected from bFO into advanced analytics. It empowers the Sales population to effortlessly convert Sales data into valuable insights focusing on the Opportunity Pipeline analysis: a powerful support to adjust their commercial strategy, ensuring flexible responses to market dynamics.

Key Features​​​​​​​

Taget audience: Sales manager, sales globals VP, and sales Operation team Active Users: 1500 Patform: AWS + tableau

Product 2: Platforming and Coverage

What is Platforming & Coverage BI? : Platforming and Coverage are vital components supporting the new E2E Growth Path strategy to improve our Digital Customer Journey.​

Platforming & Coverage BI is the new tool of reference to positively influence your Platforming & Coverage. It will enable Sales Excellence, Sales Leaders, and Sales Managers to:​​

Understand their gaps in platforming ​& coverage Identify potential ways for improvement Optimize their commercial resource allocation

Key Features

PLATFORMING​: View total accounts for my team/country in the 9-box view​ Customize the data view based on the info YOU wish to know.​ View performance by bFO Sales, Net orders, Digital Engagement etc…

COVERAGE​: Am I covering my accounts as per their attractiveness​ …as per my plan?​ …as per their revenue or potential revenue?​ Are there customers engaging with Schneider that I’m unaware of?​

BENCHMARK​:

How am I performing on the official KPIs?​ What is my country’s ranking?

Target audience: Sale manger by region /country Active Users: 500 Patform: AWS + tableau

Note: WIP