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Questions and Answers
What is the main purpose of OLTP?
What is the main purpose of OLTP?
What is the process of creating an OLAP model?
What is the process of creating an OLAP model?
What is the primary focus of a conceptual data model?
What is the primary focus of a conceptual data model?
What is included in a logical data model?
What is included in a logical data model?
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What is physical data modeling concerned with?
What is physical data modeling concerned with?
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What is the purpose of a conceptual data model?
What is the purpose of a conceptual data model?
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What is included in a conceptual data model?
What is included in a conceptual data model?
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What is the purpose of logical data modeling?
What is the purpose of logical data modeling?
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What is the main purpose of Business Intelligence?
What is the main purpose of Business Intelligence?
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What type of data is OLAP used for?
What type of data is OLAP used for?
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What is the main feature of Multidimensional OLAP?
What is the main feature of Multidimensional OLAP?
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What is the purpose of ROLAP?
What is the purpose of ROLAP?
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What is the primary function of a database?
What is the primary function of a database?
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What is the difference between OLAP and OLTP?
What is the difference between OLAP and OLTP?
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What is the main feature of Hybrid OLAP?
What is the main feature of Hybrid OLAP?
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What is Big Data?
What is Big Data?
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What is a characteristic of a data warehouse?
What is a characteristic of a data warehouse?
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What is OLAP tools?
What is OLAP tools?
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What is the purpose of ETL in a data warehouse environment?
What is the purpose of ETL in a data warehouse environment?
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What is a data warehouse?
What is a data warehouse?
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What is the meaning of nonvolatile in a data warehouse?
What is the meaning of nonvolatile in a data warehouse?
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What is data mining?
What is data mining?
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Study Notes
Data and Database Fundamentals
- Data is essential for an enterprise's operation and decision-making.
- A database is a container that stores data.
- A warehouse is a commercial building for storing goods, but in the context of data, a data warehouse is a relational database designed for query and analysis rather than transaction processing.
Big Data and Data Warehousing
- Big Data refers to data that is too large to be processed on a computer.
- Characteristics of Big Data include:
- Volume
- Velocity
- Variety
- A data warehouse (DWH) is a relational database designed for query and analysis, not transaction processing.
- Data warehouse environment includes:
- ETL (extraction, transformation, and loading)
- Statistical analysis
- Reporting
- Data mining capabilities
Data Warehouse Characteristics
- Characteristics of a data warehouse include:
- Subject-oriented
- Integrated
- Non-volatile
- Time-variant
- Subject-oriented means it can answer questions like "Who was our best customer for this item last year?" or "Who is likely to be our best customer next year?"
- Integrated means it is constructed by combining multiple, heterogeneous data sources.
- Non-volatile means that once entered into the DWH, data should not change.
- Time-variant means that the data in the DWH is time-dependent.
Data Mining and Business Intelligence
- Data mining is the process of extracting usable data from a larger set of data.
- Data warehouse implementation is the process of implementing a data warehouse using tools like Microsoft SQL Server.
- Business intelligence (BI) is a technology infrastructure for gaining maximum information from available data.
- BI is used to improve business processes and involves:
- Gathering data about customers, products, and sales
- Analyzing data using OLAP tools
- Sharing insights and data
OLAP and Business Intelligence
- OLAP (Online Analytical Processing) is a software that facilitates multidimensional analysis.
- Characteristics of OLAP include:
- Historical data
- Infrequent updates
- Integrated data
- Analytical queries
- Types of OLAP include:
- MOLAP (Multidimensional OLAP)
- ROLAP (Relational OLAP)
- HOLAP (Hybrid OLAP)
- OLTP (Online Transactional Processing) is the source data for OLAP and is characterized by:
- Operational database
- Frequent updates and queries
- Normalization and ACID
- Accessing individual tuples
Data Modeling
- A data model visually represents data and is used to create a database.
- Types of data models include:
- Conceptual data modeling
- Logical data modeling
- Physical data modeling
- Conceptual data modeling gives an idea to the functional and technical team and is created by gathering business requirements from various sources.
- Logical data modeling is the actual implementation of a conceptual data model and includes:
- Entities and relationships among them
- Attributes for each entity
- Primary key for each entity
- Foreign keys
- Normalization occurs at this level
- Physical data modeling represents how the model will be built in the database and includes:
- Database performance
- Indexing strategy
- Physical storage
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Description
Test your knowledge of data, databases, and data warehouses. Learn about the basics of data, big data, and data storage.
