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The Basics of Data Analytics [Ilham] - Coggle Diagram
The Basics of Data Analytics [Ilham]
Required Skills
Analytical skills
Berpikir kritis untuk mengubah data mentah menjadi wawasan
Analytical thinking
Keterampilan dalam memahami pola dari data bisnis
Life Cycle
Question definition
Identifikasi masalah bisnis
Data wrangling
Data cleaning, integration,and transformation
Exploration data analysis
Analisis distribusi data (histogram, boxplot)
Data visualization
Visualisasi tingkat lanjut (heatmap, network graph)
draw conclusion & communicate
Data storytelling
Types
Descriptive
Ringkasan apa yang sudah terjadi
Diagnostic
Analisis faktor penyebab
predictive
Prediksi hasil masa depan berdasarkan data historis
prescriptive
Menentukan aksi terbaik untuk mencapai tujuan
Roles of Data
Operations
Efisiensi supply chain
Strategy
Analisis pasar & kompetitor
Decision-making
Keputusan berbasis data (data-driven decision making)
Measuring
Key Performance Indicator (KPI)
Monitoring
Real-time monitoring (IoT, sensor, log data)
Insight management
Knowledge management
Reporting
aporan rutin (daily/weekly/monthly report)
Artificial Intelegence
Machine learning untuk prediksi
Problem solving
Identifikasi akar masalah (root cause analysis)
Data reuse
Pemanfaatan ulang data historis
Descriptive Statistic
Measuring central tendency
Mean, median, mode
Measuring variability
Variance, standard deviation
Measuring asymmetry
Skewness & kurtosis
Populations and samples
Generalisasi dari sampel ke populasi
Probability distribution
Distribusi normal, binomial, poisson
Tools
Data processing
Python (pandas, numpy)
Data visualization
Matplotlib, Seaborn
Reference
Provost, F., & Fawcett, T. (2013). Data Science for Business.
Bruce, P., & Bruce, A. (2020). Practical Statistics for Data Scientists
McKinney, W. (2018). Python for Data Analysis
Marr, B. (2016). Big Data in Practice
Shmueli, G., Bruce, P., Gedeck, P., & Patel, N. (2020). Data Mining for Business Analytics.