Freelance Data Analysts in Gauteng
Freelance Data Analysts in Gauteng
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Joshua Bell
Johannesburg, South Africa
Research-Driven Copy for Thought Leaders & Changemakers
5.0
Rating
4
Followers
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Research-Driven Copy for Thought Leaders & Changemakers
0
1000 Young Voices Report
0
4
0
Business Issues Report: Insights for Education Development
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6
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Book Chapter Synopsis: Motivation To Teach
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4
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Book Chapter Synopsis: Teacher Beliefs About Teaching
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2
Data Analyst
(5)
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Benjamin van der Merwe
Sandton, South Africa
Driving Revenue Generation Using Data Science || Go + Python
9
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Driving Revenue Generation Using Data Science || Go + Python
1
Forex Dashboard Web Application
1
10
1
Tradingview Custom Indicator Development
1
21
1
Customer Segmentation for Targeted Marketing
1
5
1
Sentiment Analysis of Tweets for Customer Experience Analysis
1
14
Data Analyst
(4)
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Thabo Mailula
Pretoria, South Africa
Data Analyst: SQL, Python & Power BI for actionable insights
New to Contra
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Data Analyst: SQL, Python & Power BI for actionable insights
0
Customer & Marketing Insights Dashboard | Power BI Project This Power BI project analyzes customer behavior, sales performance, promotions, and product cross-sell opportunities using sample data. The dashboard provides interactive insights in four areas: KPI Scorecards – New customers, repeat purchase rate, average basket size, and customer lifetime value (CLV). Promotion Effectiveness – Revenue trends and comparison charts showing how discounts impact sales and profit. Product Affinity / Cross-Sell – Heatmaps reveal commonly purchased product combinations. Customer Retention & Cohorts – Tracks returning customers and retention patterns.
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12
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Maji Ndogo Water Project – Part 2 | Data Analysis & Insights In Part 2 of the Maji Ndogo Water Project, I focused on cleaning and analyzing employee and water source data to understand access, detect patterns, and prioritize interventions. Key Activities: Employee Data Cleaning – Standardized emails, converted to lowercase, and updated phone numbers. Employee Performance – Counted visits per employee and identified top surveyors. Water Source Distribution – Analyzed records by town and province, calculated rural percentages, and total people served. Water Source Usage – Calculated average and total users per source type. Prioritizing Repairs – Ranked water sources by people served to guide repair priorities. This workflow highlights water access, employee activity, and priority areas for intervention.
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10
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Workflow Explanation – Part 1 Here’s what I did in this first part of the Maji Ndogo Water Project: 1.Understand the Data First, I looked at the types of water sources in the dataset: rivers, wells, shared taps, home taps, and broken taps. I noted which sources are generally safe versus which are high risk. This step helped me know what “normal” data should look like. 2.Identify Anomalies in Queue Times I checked for visits where people waited more than 8 hours (500 minutes). This flagged water sources that may have access problems or data errors. 3.Check Water Quality Records for Invalid Revisits I focused on records with perfect water quality scores (10) but multiple visits. According to the survey rules, only shared taps should have multiple visits. This step identified invalid or duplicated records in the database.
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9
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Maji_ndos_powerbi_dashboard_part1 This dashboard looks at how communities in the Maji Ndos project access water. The focus is on population size, water source availability, and how people actually use those sources during the week. What’s in the report Cards for total population and number of water sources Slicers for province, town, and location type Bar charts showing average queue time by weekday and people served by water source type Line chart for queue-time trends across the week Stacked chart showing women, men, and children in daily queues How it was built Cleaned and shaped the data in Power Query Linked population, water source, and usage tables Created measures for totals, counts, and average queue times Designed visuals that highlight patterns without overwhelming the reader
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20
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Xolani Mazibuko
Johannesburg, South Africa
Software Engineer | Python | Django | React | AWS
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Software Engineer | Python | Django | React | AWS
0
Sales Register
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8
0
System Upgrade
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29
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mazi76erX2/Auto-Report-Generator
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2
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Tumisang Kalagobe
Johannesburg, South Africa
Expert in Sales, Business Development, and Growth Strategies
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Expert in Sales, Business Development, and Growth Strategies
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Sales process optimisation
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12
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Sales training for a home insurance firm
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15
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EUR300k grant funding for South African energy pilot program
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7
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Usamah W Maphumulo
Johannesburg, South Africa
Data Analyst & Wordpress Developer
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Data Analyst & Wordpress Developer
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Should you always double down on your #1 market? 🌍 While building this Executive Revenue dashboard, the data told a different story. Instead of pouring more into the US market, we identified a massive opportunity to make countries 2-4 (India, UK, and Brazil) more competitive. The Tech Stack: ETL: Pandas (Python) Database: MySQL Viz: Power BI Moving from 5 scattered CSVs to a centralized SQL-backed dashboard allowed us to see a $9.32M revenue stream clearly for the first time.
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26
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Behind every great dashboard is a clean query. I’m currently using SQL to transform raw event logs into actionable intelligence for an e-commerce build. Key Metrics Extracted: Traffic Quality: Identifying high-intent sources via avg_session_duration. Campaign ROI: Using expected_uplift to pinpoint winning customer segments. Behavioral Trends: Mapping friction points in the checkout funnel. Moving from "gut feelings" to real-time data in Power BI, Tableau, and Looker Studio.
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81
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In the hyper-competitive "Streaming Wars," content is the product, but data is the compass. The goal of this project was to move beyond static spreadsheets and engineer a live, automated pipeline. I set out to uncover the "Survival Rate" of global content and identify the production trends that drive billion-dollar programming decisions across 197 countries.
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75
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This project was designed to empower the marketing team of a retail store with actionable insights into customer behavior. By cleaning and transforming a complex dataset using Python and Pandas, I created a streamlined CSV source that feeds into a Power BI dashboard. This tool allows stakeholders to analyze spending habits, demographic trends, and channel performance to make more informed marketing decisions.
2
135
Data Analyst
(4)
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Buhlebethu Biyela
Johannesburg, South Africa
Data Analyst | Excel & SQL | Data Cleaning and Insights.
New to Contra
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Data Analyst | Excel & SQL | Data Cleaning and Insights.
0
Analyzed monthly product sales data to identify trends and performance across multiple product categories. Created clear visualisations to highlight sales patterns, peak periods and product comparisons, enabling better understanding of business performance. This project demonstrates my ability to transform raw data into meaningful insights using Excel.
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14
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Analysed monthly product sales data to identify trends and performance across multiple product categories. Created clear visualizations to highlight sales patterns, peak periods and product comparisons, enabling better understanding of business performance. This project demonstrates my ability to transform raw data into meaningful insights using Excel.
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16
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Created a Tableau dashboard to analyze geographic and temporal patterns in sightings data across Kentucky. The analysis highlights monthly trends and the distribution of sightings by county, providing insights into location-based patterns and frequency over time. This project demonstrates my ability to work with geospatial data and visualize trends effectively using Tableau
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7
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Developed an interactive Tableau dashboard to analyse Airbnb listing data, focusing on pricing trends, geographic distribution and property characteristics. The dashboard highlights key insights such as average price by bedrooms, price variations by location and weekly pricing trends, enabling better understanding of the short-term rental market. This project demonstrates my ability to visualise complex data and communicate insights effectively using Tableau.
0
12
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Romeo Gama
Pretoria, South Africa
Data Scientist building data assets
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Data Scientist building data assets
0
Dashboard Creation: Visualizing Data Trends
0
0
0
Data Analysis: Predicting Customer Behavior
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7
0
Web Development
0
9
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