Freelance Data Analysts in Gauteng

Freelance Data Analysts in GautengFreelance Data Analysts in Gauteng

Benjamin van der Merwe

Sandton, South Africa

Driving Revenue Generation Using Data Science || Go + Python

8: Followers

Driving Revenue Generation Using Data Science || Go + Python

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Forex Dashboard Web Application

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6

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Tradingview Custom Indicator Development

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12

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Customer Segmentation for Targeted Marketing

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3

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Sentiment Analysis of Tweets for Customer Experience Analysis

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Data Analyst(4)

Johannesburg, South Africa

Research-Driven Copy for Thought Leaders & Changemakers

5.0: Rating

2: Followers

Research-Driven Copy for Thought Leaders & Changemakers

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1000 Young Voices Report

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2

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Business Issues Report: Insights for Education Development

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4

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Book Chapter Synopsis: Motivation To Teach

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Book Chapter Synopsis: Teacher Beliefs About Teaching

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1

Data Analyst(5)

Pretoria, South Africa

Data Analyst: SQL, Python & Power BI for actionable insights

New to Contra

Data Analyst: SQL, Python & Power BI for actionable insights

Cover image for Customer & Marketing Insights Dashboard | Power BI Project T...

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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3

Cover image for Maji Ndogo Water Project – Part 2 | Data Analysis & Insights...

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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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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2

Cover image for Maji_ndos_powerbi_dashboard_part1 This dashboard looks at ho...

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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Data Analyst(4)

Xolani Mazibuko

Johannesburg, South Africa

Software Engineer | Python | Django | React | AWS

Software Engineer | Python | Django | React | AWS

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7

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25

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mazi76erX2/Auto-Report-Generator

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1

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Data Analyst(1)

Tumisang Kalagobe

Johannesburg, South Africa

Expert in Sales, Business Development, and Growth Strategies

Expert in Sales, Business Development, and Growth Strategies

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Sales process optimisation

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11

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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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6

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Data Analyst(1)

Johannesburg, South Africa

Data Analyst

Data Analyst

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Amazon Prime Dashboard

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24

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National Sales and Customer Ratings

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0

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Daily Sales Calendar

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13

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Co-founder & COO

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8

Data Analyst(3)

Johannesburg, South Africa

Data-Driven SEO & Brand Design Specialist

Data-Driven SEO & Brand Design Specialist

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Sentry Safe Solutions

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1

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Letukile Academy

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2

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Ech3lons Luxury Coffee

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1

Brand Redesign and Social Media for Fashion Boutique

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1

Data Analyst(1)

Christelle kalanda

Johannesburg, South Africa

Agile data engineer & software developer

Agile data engineer & software developer

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Custom Dashboard

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6

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Data Analyst(1)