Rismawati
about me
DATA ANALYST
Hello!
I am a data analyst enthusiastic about translating powerful stories from data and creating engaging, insightful content.
I'm Rismawati, a passionate data analyst with a Bachelor's degree in Information Technology. With over a year of experience, I'm an expert in collecting, extracting, and organizing data from diverse sources, utilizing advanced statistical analysis and data modeling techniques to uncover trends, correlations, and anomalies. Proficient in Python, SQL, and data visualization tools, I specialize in developing predictive models and machine learning algorithms to extract actionable insights.
DATA ANALYST
Previous Work
Rismawati
portfolio
Data analytic for project Complication in pregnant
I using RapidMiner for comprehensive statistical analysis, utilizing data mining techniques including clustering, classification, and association to identify patterns and relationships within complex datasets. Additionally, I utilized Excel as a supplementary tool to refine data analysis, organizing and presenting data effectively with features like pivot tables, VLookUp, and filters.
Platform : RapidMiner, Excell
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Based on daily trend, convertion rate on Saturday is lower than other days. Gustavo can give a voucher or another promo on Saturday, so customer will be interest in shopping. On Monday, logistic team must prepare for many deliveries to increase customer satisfaction because we have a lot of shipment on monday.
Rismawati
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DATA ANALYST
PYTHON PROJECT
recommendations:
Data Source: Gustavo E-Commerce data on Google Collab
python query:
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- Active Users of Streaming Platforms: Targets users who actively use streaming platforms
- Identifies users who have watched movies and provides movie recommendations
- Partner with streaming platforms to serve recommendations directly to users through their recommendation features
Rismawati
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DATA ANALYST
recommendation for customer
recommendations:
Data Source: rating movie ON Github
python query:
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DATA ANALYST
SQL SKILL SET
Basic SQL : basic syntax, basic function and operators, ordering and alias.
Intermediate SQL : data manipulation, SQL joins, formatting and cleaning in SQL Advanced SQL : SQL date type, SQL date format, subqueries, CTE, window function, cohort analysis
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- The total number of users who created a new title in June 2014 decreased. Its shown in the table hypothesis.
- Next two month after release was decreased by 16%-39%, so hacker news need to improve in first month (e.g special gift for the author)
- Hacker news needs to keep its performance since this cohort table become a stationer (horizontal trend)
Rismawati
about me
DATA ANALYST
Monthly Retention Cohort in 2014 using SQL
Data Source: Google BigQuery Hacker News with "stories" table
SQL query:
recommendations:
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DATA ANALYST
TABLEAU DASHBOARD
DASHBOARD INSIGHT:
- November 2017 had the highest order from December 2016 to August 2018.
- 2018 had a significant increase in sales. Olist can give a double-date campaign to increase sales.
- Sao Paolo (SP) state has the most significant number of orders because many customers in Sao Paolo have a high income, so Olist can plan another promo in a low number of orders such as the Central-West region of Brazil.
- Home Appliances have the highest sales products category, so Olist can add more products in Home Appliances category.
Data Source: Olist E-Commerce data on Google Collab
TABLEAU RESULT
Rismawati
DATA ANALYST
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Achievment
Mahasiswa Berprestasi Tingkat Wilayah Tahun 2023
Pusat Prestasi Nasional
Regional Kalimantan (LLDIKTI XI)
Data Analytic Professional Certificate
Google - Coursera
AI Mastery Program
Orbit Future Academy
Microsoft Academy
Power BI Data Analyst
Microsoft -
Initiative
