Zeeshan Akram

Zeeshan Akram

Rawalpindi, Pakistan

Zeeshan Akram

Data Analytics & BI Dashboards
Do you have data but struggle to extract clear business insights?

I am a Data Analyst who turns messy spreadsheets and databases into executive-level Business Intelligence tools. I don't just build charts; I engineer automated, interactive Power BI dashboards that help you track KPIs, understand business health, and make profitable decisions.

What I Can Build For You:

Executive Power BI Dashboards:
Stop staring at static Excel sheets. I build live, boardroom-ready dashboards with clean, modern UI/UX. Click, filter, and instantly see your Revenue, Profit Margins, and Year-over-Year (YoY) growth.

Deep Data Analysis & SQL Extraction:
I dig into your raw data to find hidden patterns—like which products drain your margins, which regions drive growth, and where your operational bottlenecks are.

Data Cleaning & Automated Pipelines:
I take your messy, unformatted data and use Power Query, Excel and Python to clean, structure, and automate it so your reports update flawlessly.

My Technical Toolkit:

Business Intelligence: Power BI, DAX, Power Query.

Databases & Queries: SQL (PostgreSQL, MySQL).

Data Wrangling: Python, Pandas, Advanced Excel.

Why Me?
I focus on the "Data-to-Ink" ratio—meaning no cluttered visuals, just pure, actionable business insights. I have a proven track record of designing corporate-grade BI solutions with advanced Time-Intelligence tracking.

Let's turn your data into your biggest asset. Contact me to discuss your project!
Delivered comprehensive Data Analytics projects, ranging from Exploratory Data Analysis (EDA) to Executive Business Intelligence reporting.

Business Intelligence & Dashboards: Engineered a Fortune 500-level Superstore Sales BI Dashboard in Power BI. Implemented advanced DAX (Time-Intelligence, YoY tracking) and custom corporate UI/UX to replace static Excel reports.

Data Engineering & Wrangling: Handled complex data cleaning and transformation using Power Query, SQL, and Python (Pandas) to ensure 100% data accuracy for reporting.

Actionable Analytics: Applied segmentation and forecasting techniques to translate raw e-commerce and energy consumption data into clear business strategies.

Technical Stack: Power BI, SQL, DAX, Power Query, Python, Pandas, and Advanced Excel.

Quality Standards: Maintained a professional repository with comprehensive documentation, clean data models, and strict UI/UX design principles.
Building a strong foundation in Computer Science with a specialized focus on Data Analytics and Business Intelligence.

Core Competencies: Relational Databases (SQL), Data Modeling, Advanced Data Visualization, and Object-Oriented Programming.

Practical Application: Leveraging analytical principles to build scalable, production-grade Power BI reporting systems, bridging the gap between raw, messy data and executive decision-making.
  • Data Visualization with Python 02/07/2025
    Advanced training in communicating insights through data storytelling and visualization.

    Core Libraries: Mastered Matplotlib, Seaborn, and Folium for static and interactive plotting.

    Dashboarding: Created interactive dashboards and geospatial maps to visualize complex datasets.

    Application: Transformed raw data into clear, visual narratives to support business decision-making.
  • Natural Language Processing with Classification and Vector Spaces 29/06/2025
    Specialization in NLP, focusing on how machines understand and process human language.

    Core Skills: Sentiment Analysis, Naive Bayes, Vector Space Models, and Word Embeddings (Word2Vec).

    Projects: Built a sentiment analysis model to classify tweets and used vector spaces to find relationships between words.
  • Databases and SQL for Data Science with Python 29/06/2025
    Comprehensive training in SQL and Relational Database Management Systems (RDBMS).

    Core Skills: Writing complex SQL queries (SELECT, JOIN, COUNT), database design, and accessing databases from Python using Jupyter Notebooks.

    Tools: SQL Magic, Cloud Databases, and Python integration.
  • Data Analysis with Python 27/06/2025
    Deep dive into the Data Science data wrangling pipeline.

    Core Skills: Data cleaning, manipulation, and analysis using Pandas and NumPy.

    Techniques: Handling missing values, data formatting, and exploratory data analysis (EDA) to derive insights from raw datasets.
  • Machine Learning with Python 23/06/2025
    Practical application of Machine Learning algorithms using Python libraries.

    Core Skills: Supervised (Classification, Regression) and Unsupervised Learning (Clustering/K-Means).

    Stack: SciPy, Scikit-Learn, and Hierarchical Clustering for customer segmentation.
  • Supervised Machine Learning: Regression and Classification 22/06/2025
    Mastered the fundamentals of Machine Learning with Andrew Ng. Built and trained supervised learning models for prediction and binary classification tasks.

    Core Skills: Linear & Logistic Regression, Gradient Descent, Regularization to prevent overfitting, and Scikit-Learn implementation.

    Application: Applied algorithms to real-world datasets for price prediction and medical diagnosis classification.
  • 🇬🇧 English
  • 🇮🇳 Hindi
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