Question

Why do firms need to create separate data repositories for their reporting and analytics work?

a. Most firms store their data assets offsite to insure themselves against the possibility of data damage through natural disasters.
b. Maintaining huge databases can be a cost-sink for most firms.
c. Most organizations need to differentiate data derived in-house and from data aggregators.
d. Running analytics against transactional data can bog down a TPS.
e. Reporting and analytics are two separate functions, each requiring its own separate database specifically formatted to the needs of the management team.

Answer 1

The correct answer is option d. Firms create separate data repositories for reporting and analytics mainly because running analytics against transactional data can significantly slow down a Transaction Processing System. Separate repositories, such as Data Warehouses, are optimized for analytic processes and are structured to efficiently run complex queries without impacting the performance of daily transactions.

Step-by-step explanation:

Firms often need to create separate data repositories for their reporting and analytics work to maintain efficient and effective operations. One primary reason for this separation is d. Running analytics against transactional data can bog down a Transaction Processing System (TPS). Transactional databases are optimized for operations such as insert, update, and delete, known collectively as Online Transaction Processing (OLTP). These operations are crucial for day-to-day business functions like sales, inventory management, and customer relations. When analytics queries, which are complex and read-intensive, are run on the same system, they can drastically slow down the performance of these critical transactional operations.

Furthermore, analytical processing often requires historical data and aggregation which might not be available or structured properly in the daily use transactional databases. This is why separate analytical databases, or Data Warehouses (DW), are created where data is structured differently, optimized for read-intensive operations. This separation allows companies to perform in-depth analysis without affecting the performance of their TPS.

The structure of the reporting and analytics databases is typically shaped to support the respective tasks. For example, data warehouses for analytics often use multi-dimensional data models such as star schema or snowflake schema that allow for complex queries and fast retrieval of large volumes of data. On the other hand, reporting databases might be more straightforward, tailored to provide the specific outputs needed for various internal and external reports.

In summary, the correct option that explains why firms create separate data repositories for their reporting and analytics is option d. This approach ensures both transactional integrity by not overloading the TPS with heavy analytical queries and allows for deeper, more complex analytics that would be difficult to perform in a transactional database.