1. The structure of an online transaction database has the insertion, update and deletion functions for single point deals (Kimball, 2013). The structure of this database is, thus, optimized for writing and updating data. A data warehouse database has retrieval and aggregation functions focused on large data quantities (Kimball, 2013). The structure of a data warehouse database is optimized for gathering information, processing queries, and analyzing data.
Due to normalization, the structure of an online transaction database entails complex tables and joins to prevent data replication, which ensures efficient storage and processing and faster response times (Kimball, 2013). The structure of a data warehouse database, nevertheless, is denormalized and has a simple structure with few tables to ensure efficient retrieval and aggregation of data, which enhances the response time of analytical queries (Kimball, 2013).
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An online transaction database deals with small data volumes, which consumes fewer system resources. A data warehouse, however, deals with large volumes of data, which requires a large number of system resources.
2. In operation data, the database requires many tables to store data, and the stored data contains information for a single transaction (Coronel & Morris, 2018). In Decision support data, the database requires fewer tables, and the stored data is the integrated, analyzed and summarized information about transactions (Coronel & Morris, 2018).
Operational data requires a normalized database with numerous tables and minimum attributes because of the potential for data errors (Coronel & Morris, 2018). Decision support data requires non-normalized databases with fewer tables and numerous attributes because of the need to query data (Coronel & Morris, 2018).
Operational data requires databases with low query activity to enable extra processing cycles for important transactions (Coronel & Morris, 2018). Decision support data requires databases with a high query activity to enable aggregation and analysis (Coronel & Morris, 2018).
3. An online multinational organization can use a database to track basic transactions to determine sales volume or sales within a specified period. An organization can also use a database to seek information about its financial performance by examining how it balances its expenditure, sales, revenues and liabilities in order to enhance efficient operations. Organizations can also link their databases to web browsers and seek feedback from clients or users to improve their products or services (Chen, Chiang & Storey, 2012).
4. An organization can use a data warehouse to aggregate and analyze sales data for a specific product to determine the number sold within a specified period and make the necessary changes to enhance sales. Organizations can also use data mining to find different relationships and patterns and deduce ways to forecast future associations based on the analyzed data. Lastly, organizations can use the sales trend analysis to estimate how clients will purchase their products (Chen, Chiang & Storey, 2012).
References
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: from big data to big impact. MIS quarterly , 1165-1188.
Coronel, C., & Morris, S. (2018). Database systems: Design, implementation, and management . Boston, MA, USA: Cengage Learning.
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Kimball, R. (2013). The data warehouse toolkit: The definitive guide to dimensional modeling . J. Wiley & Sons.
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