The project focused on the use of public data to assess the economic situation in the country based on the state of the stock market and national means of payment, in particular - of the national currency. As sources are used: Open data Ministry of Finance of the Russian Federation These Moscow Exchange Google Finance Data Technologies used: Backend: Databases (relational) - Microsoft SQL Server 2014 Databases (multivariate) models DataMining, OLAP-cube - Microsoft Analysis Services 12.0 Веб-сервер - Windows Server 2012 / Internet Information Services Самописный ASP.NET HTTP Restful интерфейс для взаимодействия с Frontend ETL (загрузка и пре-процессинг данных, управление обновлением данных) SQL Server Integration Services 2014 (разработка в Visual Studio 2013, SSDT) Frontend: AngularJS ChartJS Twitter Bootstrap These were chosen so that the detail (granularity) in the set is not less than 1 day. The result has been created and filled with data analytic repository (Kimball model, topology - star), which was used to build a multi-dimensional databases and OLAP-based cubes on it, as well as models of analysis of data on two main algorithms: Microsoft Time Series, Microsoft Neural Network . To ensure interoperability frontend and backend server for backend-server was set up HTTP-Restful interface JSON-issuing documents in the form of finished sets. The project includes two main areas: Intelligent visualization of open data Analysis of open data and the construction of forecasts based on them Intelligent visualization involves the use of MDX-queries to the OLAP-cube, followed by depression (drilldown) in the data, the system allows the user to quickly find the "weak points" of the economy, as part of the data collected. To predict the time a standard mix of algorithms ARTXP / ARIMA, without the use of queries involving cross-prediction (but it is possible to enroll in the system correct data). These algorithms have been tested primarily on foreign exchange rates (US dollar) and the assets of banks included in the special list of Ministry of Finance. In addition, for assets shows the different customization options algorithms - a long-term, short-term and medium-term (balanced) plan. Assessing the impact of oil prices and foreign currency exchange rate for the total market capitalization was conducted on a sample of the data collected: companies with a total market capitalization of 100 to 500 million rubles, present in the market during 2013-2015 Analytical server builds the neural network receiving the input exchange rates, companies, the weighted average share price, total capitalization of the company and the price of oil to requests received models give the opportunity to evaluate the growth rate of \ fall (if at all) the company's capitalization at historical exchange rates and / or the cost of oil. Built a system can expand to include new indicators, which will significantly increase the accuracy of forecasting.

Optimisation de l'Entrepôt de Données pour un Acteur Majeur de l'E-Commerce

An end-to-end Data Warehousing solution for HR Analytics. Includes ETL (SSIS), OLAP Cubes (SSAS), MDX queries, Power BI dashboards, and predictive modeling (XGBoost/Random Forest) to analyze workforce turnover.

Designed Data Warehouses with Snowflake Schema in SQL & Tableau Dashboards from multiple data sources. Modeled OLAP Cubes & ETL processes using SSAS, designed Validation Tables with 3NF on Azure Cloud. Reduced processing load by optimizing the buffer time & cache from 15 to 5 mins for 10 million rows in T-SQL

Using Global Superstore dataset with 5-year data from operational systems, the project is to design a data model using Dimensional Modelling and Bus Matrix Architecture. Then, conducting five ETL workflow on SSMS to transfer data to data warehouse. From data warehouse, SSAS and Power BI have been deployed to build different cubes and answer OLAP queries for business purposes

Integrated Data Warehouse Solution for Airbnb Analytics: ETL Automation, SQL SERVER: Data Warehouse Modelling, OLAP Cube, and PowerBI Reporting

Sales Data Warehouse in PostgreSQL with ETL pipelines for data transformation, cleansing, and dimension modeling, supporting OLAP cubes and multi-dimensional sales analysis

A comprehensive data warehouse project analyzing movie data from IMDb and TMDb, featuring ETL with SSIS, OLAP cubes with SSAS, and predictive modeling.

End-to-End BI & Data Warehouse project using SQL Server, SSIS, SSAS, and SSRS with ETL pipelines, Star Schema modeling, OLAP cube, and analytical reports.

End-to-end DW/BI and ML pipeline: SSIS ETL, SQL Server star schema, SSAS OLAP cubes, and fraud-risk modeling using Logistic Regression, Random Forest, and XGBoost.

End-to-end Data Warehousing & Business Intelligence project using the Instacart dataset. Covers ETL with SSIS, Snowflake schema design, OLAP cube in SSAS, and interactive Power BI dashboards. Demonstrates data modeling, KPIs, and OLAP operations for decision support.

End-to-end Data Warehousing and Business Intelligence solution for banking operations. Features comprehensive ETL pipelines using SSIS, Star Schema modeling in SQL Server, and OLAP Cube creation with SSAS.

End-to-end BI project for a fictitious retail store using Microsoft SQL Server tools — covering OLTP modeling, ETL with SSIS, OLAP cube creation with SSAS, and report generation with SSRS

This project demonstrates a modern approach to workforce analytics by combining robust ETL processes, multidimensional OLAP analysis, interactive visualizations, and predictive modeling to support strategic workforce planning. It revitalizes NASA's Workforce Information Cubes (WICN) using advanced data-driven methodologies.

A Microsoft Business Intelligence (MSBI) solution for evaluating and benchmarking Large Language Models (LLMs) using real-world benchmark data. This project implements a complete BI pipeline with SSIS (ETL), SSAS (OLAP Cube), and Power BI visualizations to centralize, structure, and analyze the performance of open-source LLMs.

This project, created for IT3021 – Data Warehousing and Business Intelligence, showcases a complete DWBI solution using real-world data. It covers OLTP data modeling, ETL with SSIS, dimensional warehouse design, SSAS cube with hierarchies, OLAP analysis in Excel, and Power BI reporting with drill-down, drill-through, and interactive visualizations

This is a project created for DWBI model which includes preparation of transactional dataset and preparation of a data wharehouse with the utilization of ETL tools such as SSMS and SSIS. Alongside OLAP cube also was also deployed for data visualization using Excel, Power BI and SSRS reporting using reporting tool

Development of a Business Intelligence solution for stock management for the port of La Goulette. Designing a data warehouse / Implementing ETL processes and creating OLAP cube / Developing reports and dashboards / Applying data mining models. Social Media, Text mining , marketing channels efficiency and user behaviour analysis. Tools: PostgreSQL, MSSQL, Talend, Pentaho, Tableau Software, QlikView, R, hadoop Cloudera