statistical analysis Algorythms
- what? optimize & predict - Present/Future data
- data science to analyze
- descriptive & prescriptive
- Modeling, forecasting
- for: analysts/strategists
- why? Increase efficiency, revenue, & reduce costs
- Anticipate customer needs and market shifts
- e.g. use-cases
- Retail: Forecast demand and optimize inventory
- Finance: Detect fraud and assess credit risk
- Healthcare: Predict patient readmissions
- Marketing: Segment customers and personalize campaigns
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skills
- Components
- Modeling: scikit-learn, TensorFlow, SAS
- Data management: Snowflake, BigQuery, Redshift
- Data analysis: Python, R, SQL
- Visualization: Tableau, Power BI, Superset
SQL, Excel Basic stats, trend analysis KPI-driven
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ba
- SQL, Python, R
- Predictive modeling, regression, clustering
- Data modeling - Star/snowflake schemas
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Star/snowflake schemas
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ETL tools
- Apache Airflow, Talend, Fivetran, AWS Glue, dbt, Informatica
| Skill Area | Business Intelligence (BI) | Business Analytics (BA) | Data Analytics (DA) |
|---|---|---|---|
| Data querying | SQL, Excel | SQL, Python, R | SQL, Python, R |
| Visualization | Power BI, Tableau, Qlik | Tableau, Superset, Looker | Grafana, Matplotlib, Seaborn |
| Statistical analysis | Basic stats, trend analysis | Predictive modeling, regression, clustering | Full range: descriptive to prescriptive |
| Data modeling | Star/snowflake schemas, KPIs | Forecasting, optimization models | Machine learning, deep learning |
| ETL & data prep | ETL tools, data warehouses | Data wrangling, transformation | Data pipelines, APIs, scripting |
| Business acumen | High (KPI-driven) | High (strategy-driven) | Medium to high (depends on domain) |
| Communication | Dashboards, reports, storytelling | Insight presentation, stakeholder alignment | Data storytelling, technical reporting |
| Tools | Power BI, Tableau, Excel, SQL Server | Python, R, SAS, Superset, Looker | Jupyter, Pandas, Spark, BigQuery |