Skills, tools, and technologies I use for data analytics and application support.

Here's a comprehensive overview of the technical skills, tools, and methodologies I use in my work as a Data Analytics professional. These skills have been developed through my MSc in Data Analytics, professional experience, and hands-on project work.

Data Visualization Tools

  • Power BI

    Advanced proficiency in Power BI with expertise in DAX (Data Analysis Expressions) for creating complex calculations and measures. Skilled in data modelling, creating interactive dashboards, and building reusable reporting templates for business intelligence.

  • Tableau

    Experienced in building interactive dashboards and visual analytics. Proficient in using filters, parameters, and calculated fields to support data-driven decision-making for non-technical users. Applied in projects like the Public Healthcare Dashboard.

  • Excel (Advanced)

    Expert-level proficiency in Excel including PivotTables, VLOOKUP, advanced charting, and data analysis. Used extensively for KPI tracking, data validation, performance reporting, and creating structured analytical reports.

  • Google Sheets

    Proficient in collaborative data analysis and reporting using Google Sheets, particularly useful for team-based projects and real-time data sharing.

Programming & Database Technologies

  • SQL

    Advanced SQL skills including complex joins, window functions, data extraction, and data validation queries. Experienced in optimizing SQL jobs and ETL workflows, improving batch performance by up to 40% in production environments.

  • Python

    Proficient in Python for QA automation, data analysis workflows, data extraction, cleaning, and formatting. Built tools like the PII Encryption system for customer data compliance. Experienced in using Python libraries for statistical analysis and performance monitoring.

  • R Programming

    Skilled in R for regression modelling, trend analysis, and statistical analysis. Applied in projects like Car Price Forecasting, using techniques such as EDA, feature engineering, distribution checks, and model diagnostics (RMSE, residual analysis).

  • MongoDB

    Experienced in MongoDB aggregation frameworks, data modelling, and NoSQL database operations. Built aggregation pipelines for analyzing activity patterns, anomaly detection, and data profiling. Applied advanced database concepts from MSc coursework.

Data Analysis & Quality

  • Data Analysis

    Expertise in KPI tracking, data validation, anomaly detection, trend identification, and exploratory data analysis (EDA). Skilled in data cleaning, performance reporting, data interpretation, and creating structured analytical narratives.

  • Quality & Auditing

    Proficient in accuracy checks, audits & re-audits, Root Cause Analysis (RCA), error-trend analysis, and SLA monitoring. Experienced in policy adherence, QA documentation, corrective action recommendations, process review, and feedback delivery.

  • Statistical Analysis

    Strong foundation in hypothesis testing, regression modelling, statistical analysis, and advanced analytical techniques. Applied statistical methods for model validation, correlation analysis, and identifying performance bottlenecks.

  • ETL & Data Warehousing

    Knowledgeable in ETL concepts, data warehousing fundamentals, relational modelling, and optimization techniques. Experienced in designing and enhancing ETL workflows for improved performance and data accuracy.

Automation & Process Improvement

  • Workflow Automation

    Experienced in automating manual workflows using SQL and Python, reducing recurring operational effort by 30%. Skilled in creating reusable utilities for data extraction and reconciliation, accelerating ad-hoc analysis tasks.

  • Power Automate

    Basic proficiency in Power Automate for workflow automation and process optimization. Identified workflow inefficiencies and recommended automation opportunities.

  • Data Modelling

    Strong understanding of data modelling fundamentals, relational modelling, and database design principles. Applied in projects involving complex data structures and multi-source data integration.

Soft Skills & Collaboration

  • Communication & Stakeholder Management

    Excellent communication skills with experience in stakeholder coordination, translating analytical findings into actionable recommendations, and presenting insights to both technical and non-technical audiences.

  • Problem Solving & Decision Making

    Strong problem-solving abilities with experience in incident resolution, cross-functional collaboration, and making data-driven decisions under time constraints and strict SLAs.

  • Coaching & Mentoring

    Experienced in coaching and mentoring, knowledge transfer, and process documentation. Created SOPs and documentation that improved team knowledge transfer and reduced repeat escalations.

  • Adaptability & Collaboration

    Proven adaptability in working across different environments (Production, UAT, Test), managing deployments, and collaborating with Development, Network, Cloud, and Business teams to resolve complex issues.