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Business Intelligence (BI)
Applications for data analysis supporting decision-making.
Operational BI
Focuses on immediate actions and results.
Tactical BI
Aids in daily analysis and campaign refinement.
Strategic BI
Supports long-term planning and marketing strategies.
Data Mining
Analyzing data to extract hidden information.
Data Latency
Time to prepare data for analysis.
Analysis Latency
Duration from data availability to analysis completion.
Decision Latency
Time taken to comprehend and act on analysis.
Data Profiling
Collecting statistics about existing data sources.
Data Replication
Sharing information for consistency across sources.
Recommendation Engine
Algorithm suggesting products based on customer behavior.
Affinity Grouping Analysis
Identifies relationships between data points.
Classification Analysis
Assigns items to predefined categories.
Cluster Analysis
Groups similar data points together.
Estimation Analysis
Predicts unknown values based on known data.
Optimization Modeling
Finding the best solution under given constraints.
Forecasting Modeling
Predicting future trends based on historical data.
Regression Modeling
Analyzing relationships between variables.
Agile BI
BI approach using Agile methodologies for efficiency.
Quantifiable Benefits
Direct measurable advantages from BI deployment.
Indirectly Quantifiable Benefits
New business from existing or new customers.
Unpredictable Benefits
Unexpected discoveries by creative users.
Intangible Benefits
Improvements in communication and job satisfaction.
BI Deployment
Implementing BI systems across an organization.
Business Understanding Phase
Initial phase defining business objectives for data.
Data Understanding Phase
Phase for comprehending data characteristics.
Data Preparation Phase
Cleaning and organizing data for analysis.
Data Modeling Phase
Creating models to analyze data effectively.
Evaluation Phase
Assessing the model's effectiveness before deployment.
Deployment Phase
Implementing the final model into production.