DATA ANALYTICS (Intermediate Level)

Durasi : 09.00 – 16.00 WIB

Description Training

Di era digital dan AI-driven business, perusahaan membutuhkan kemampuan analisis data yang lebih cepat, akurat, dan actionable. Level intermediate pada data analytics tidak lagi hanya fokus pada pembuatan laporan, tetapi juga pada kemampuan melakukan data preparation, exploratory analysis, dashboard interaktif, predictive insight, hingga data storytelling untuk pengambilan keputusan bisnis. 

Training ini dirancang berdasarkan tren kompetensi Data Analytics 2026 yang menitikberatkan pada:

• SQL & data querying
• Data cleaning & transformation
• Python analytics workflow
• Interactive dashboard (Power BI/Tableau)
• Statistical analysis
• Business insight generation
• Automation & AI-assisted analytics

Training Objective

Setelah mengikuti pelatihan ini, peserta akan mampu:

1. Memahami workflow Data Analytics modern

2. Mengolah dan membersihkan data dari berbagai sumber

3. Melakukan analisis menggunakan SQL & Python

4. Membuat dashboard interaktif dan visualisasi profesional

5. Menghasilkan insight bisnis berbasis data

6. Melakukan exploratory & statistical analysis

7. Menyusun data storytelling untuk manajemen

8. Mengintegrasikan automation dan AI tools dalam analytics workflow

Siapa yang disarankan untuk mengikuti Pelatihan ini ?

• Data Analyst Junior – Intermediate
• Staff Reporting & Business Intelligence
• Finance, Marketing, HR, Operation Analyst
• Supervisor & Professional yang sudah memahami dasar Excel/SQL/Data Visualization

Prerequisite

Peserta telah memahami dasar:

• Microsoft Excel
• Konsep database sederhana
• Basic reporting/dashboard
• Statistik dasar

Training Outline

HARI PERTAMA : DATA PREPARATION, SQL & ANALYTICS WORKFLOW 

1. Modern Data Analytics Framework

• Peran Data Analyst di era AI & automation
• Data analytics lifecycle
• Business-driven analytics approach
• KPI & business metrics fundamentals
• Data governance & data quality awareness

2. Data Collection & Data Sources

• Structured vs unstructured data
• Database fundamentals
• CSV, Excel, API, Cloud Data
• Introduction to data warehouse & ETL

3. SQL for Intermediate Analytics

• Review SQL fundamentals
• Advanced filtering & aggregation
• JOIN optimization
• Subquery & Common Table Expression (CTE)
• Window Functions
• Ranking & analytical query
• Time-series query
• Cohort & segmentation analysis

4. Hands-on SQL Analytics Lab

• Sales analysis
• Customer segmentation
• Revenue trend analysis
• Product performance analysis

5. Data Cleaning & Data Wrangling

• Handling missing values
• Duplicate detection
• Data normalization
• Data validation
• Outlier handling
• Data transformation workflow

HARI KEDUA : PYTHON FOR DATA ANALYTICS & EXPLORATORY ANALYSIS 

1. Python Analytics Ecosystem

• Python for analysts
• Jupyter Notebook workflow
• Introduction to: Pandas / NumPy / Matplotlib / Seaborn

2. Data Manipulation with Pandas

• Import multiple data sources
• DataFrame operations
• Filtering & sorting
• Merge & concatenate
• Grouping & aggregation
• Pivot table analysis

3. Exploratory Data Analysis (EDA)

• Exploratory workflow
• Pattern identification
• Trend analysis
• Correlation analysis
• Descriptive statistics
• Distribution analysis

4. Statistical Analysis for Analysts

• Mean, median, standard deviation
• Correlation & covariance
• Hypothesis testing basics
• Confidence interval
• Regression overview

5. Data Visualization Principles

• Effective chart selection
• Business visualization standards
• Interactive chart concepts
• Avoiding misleading visualization

6. Hands-on Python Analytics Project

• Sales forecasting basics
• Customer behavior analysis
• Marketing analytics case study

HARI KETIGA: BUSINESS INTELLIGENCE, DASHBOARD & DATA STORYTELLING

1. Power BI / Tableau Intermediate

• Data connection & modeling
• Data transformation with Power Query
• DAX fundamentals
• Calculated columns & measures
• KPI dashboard development

2. Interactive Dashboard Design

• Executive dashboard principles
• Operational dashboard
• Drill-through & filtering
• Dynamic visualization
• Dashboard performance optimization

3. Business Analytics & Insight Generation

• Turning data into decisions
• Root cause analysis
• Trend & anomaly interpretation
• Predictive insight basics
• Business recommendation framework

4. Data Storytelling for Management

• Storytelling framework
• Executive presentation techniques
• Communicating insight effectively
• Building actionable recommendations

5. AI & Automation in Data Analytics

• AI-assisted analytics
• Prompt engineering for analysts
• Analytics automation workflow
• Introduction to AutoML & Copilot analytics
• Future trends in analytics

6. Final Integrated Project

Peserta akan:

• Membersihkan data
• Melakukan analisis
• Membuat dashboard
• Menyusun insight bisnis
• Presentasi hasil analytics

7. Workshop: End-to-End Data Analytics Business Case

TOOLS & SOFTWARE YANG DIGUNAKAN

Peserta akan menggunakan kombinasi tools industri terbaru seperti:

• Microsoft Excel Advanced
• Google Sheets
• SQL (PostgreSQL/MySQL)
• Python (Pandas, NumPy, Matplotlib)
• Jupyter Notebook
• Power BI
• Tableau
• GitHub basic portfolio workflow

Tools tersebut menjadi standar kompetensi analytics modern 2026. 

OUTPUT PELATIHAN

Setelah pelatihan peserta mampu:

• Membuat analytical report profesional
• Mengolah data skala menengah-besar
• Membuat dashboard interaktif
• Menghasilkan insight bisnis
• Mengotomasi sebagian proses reporting
• Menyusun presentasi data-driven decision

Metode Pelatihan

Kegiatan pelatihan dirancang agar peserta dapat memahami secara komprehensif materi yang disampaikan, sehingga dapat dimplementasikan secara aplikatif dalam dunia kerja. Adapun metode yang digunakan adalah:

• Pre and Post Test
• Instructor Led Training
• Interactive Discussion
• Hands-on Practice
• Case Study Industry
• Dashboard Workshop
• Group Exercise
• Final Presentation
• Evaluasi Training

Trainer : Spectracentre Trainer Team