the path to insights: data models and pipelines coursera weekly challenge 2 answers

Test your knowledge: Database performance

1. Fill in the blank: A data mart is a _____ database that can be a subset of a larger data warehouse. This means it is a convenient way to access the data pertaining to specific areas or departments of a business.

  • Specialized
  • Subject-oriented
  • Departmental
  • Categorical

2. A business intelligence team manager wants to support their team’s ability to perform at a high level. They investigate the overall capability of their company’s database hardware and software tools to enable the team to process stakeholder requests. In this situation, which of the factors of database performance do they consider?

  • Optimization
  • Resources
  • Throughput
  • Workload

3. What term is used to describe data that is broken up into many pieces that are not stored together?

  • Fragmented data
  • Archived data
  • Split data
  • Modified data

Weekly challenge 2

4. Which of the following statements accurately describe data marts and data lakes? Select all that apply.

  • Data marts benefit business intelligence professionals because they provide a convenient way to access data that is relevant to a particular project.
  • Data marts are useful when a business intelligence system is ingesting a lot of different data types because they do not require the data to be transformed before storage.
  • Data lakes benefit business intelligence professionals because they provide a convenient way to access data that is relevant to a particular project.
  • Data lakes are useful when a business intelligence system is ingesting a lot of different data types because they do not require the data to be transformed before storage.

5. What business intelligence tool enables data to be gathered from different sources, then loaded into a unified destination system and transformed into a useful format?

  • Data lake
  • ELT
  • ETL
  • Data mart

6. What does database performance measure? Select all that apply.

  • The ability of the database to be reconfigured
  • The workload that can be processed by the database
  • Any costs associated with the workload being processed by the database
  • Improvements made to data tools and processes

7. A business intelligence professional is considering the transactions, queries, analyses, and system commands being processed by a database system. Which of the five factors of database performance are they evaluating?

  • Workload
  • Throughput
  • Optimization
  • Contention

8. Which of the following statements accurately describe database resources? Select all that apply.

  • Resources include hardware and software tools.
  • Resources can be both internal and external.
  • Resources include disk space and memory.
  • Resources may not be shared with other users.

9. Optimization involves decreasing _____, which is how long it takes for a database to respond to a user request.

  • Data view
  • Response time
  • Scope
  • Contention

10. A business intelligence professional is investigating the steps their database system takes in order to execute a query. They discover that creating a new table will enhance performance. What does this scenario describe?

  • Evaluating contentions
  • Checking a query plan
  • Limiting data
  • Considering run methodology

11. What are the goals of data partitioning? Select all that apply.

  • Segment text strings in a query
  • Ensure data segments add up to a whole
  • Divide a database into distinct, logical parts
  • Improve query processing

12. Fragmented data is broken up into many pieces that are not stored together. What are some common reasons for this fragmentation? Select all that apply.

  • Deleting data files
  • Modifying data files
  • Using the data infrequently
  • Creating new data files

13. When two or more data analysts attempt to use a single data resource in a conflicting way, what is the result?

  • Duplicates
  • Redundancy
  • Argument
  • Contention

14. Which of the following statements accurately describe data marts and data lakes? Select all that apply.

  • Data lakes are subject-oriented, which means they are associated with specific areas or departments of a business.
  • Data lakes are designed to enable information accessibility because their data doesn’t require a lot of processing.
  • Data marts are designed to enable information accessibility because their data doesn’t require a lot of processing.
  • Data marts are subject-oriented, which means they are associated with specific areas or departments of a business.

15. What are some key benefits of ELT data pipelines in business intelligence?

  • ELT enables business intelligence professionals to transform only the data they need.
  • ELT reduces storage costs and enables businesses to scale storage and computation resources independently.
  • ELT enables business intelligence professionals to transform data while it is being transported.
  • ELT can ingest many different kinds of data into a storage system as soon as that data is available.

16. When evaluating a database system’s resources, what does a business intelligence professional consider? Select all that apply.

  • Disk space and memory
  • Users
  • Hardware
  • Software

17. Fill in the blank: The goal of _____ is to enable a database system to process the largest possible workload at the most reasonable cost.

  • application development
  • business intelligence strategy
  • optimization
  • visibility

18. Fill in the blank: In a relational database system that uses SQL, a _____ describes how the database system will execute a query.

  • data limitation
  • HOW statement
  • query plan
  • run method

19. Which of the following statements accurately describe data marts and data lakes? Select all that apply.

  • A data mart is a subject-oriented database that can be a subset of a larger data warehouse.
  • A data lake is a database system that stores large amounts of raw data in its original format until it’s needed.
  • A data mart is a database system that stores large amounts of raw data in its original format until it’s needed.
  • A data lake is a subject-oriented database that can be a subset of a larger data warehouse.

20. Fill in the blank: A business intelligence professional gathers data, loads it into a unified destination system, and then transforms it into a useful format. They do this using an _____ data pipeline.

  • oriented
  • interpreted
  • ETL
  • ELT

21. What is a measure of the workload that can be processed by a database, as well as the associated costs?

  • Scalability
  • Database performance
  • Distribution
  • Maturity

22. Fill in the blank: A query plan describes the _____ involved with executing a query by a relational database.

  • business strategy
  • steps
  • spreadsheets
  • reasoning

23. Which of the following statements accurately describe indexes versus data partitions? Select all that apply.

  • Data partitioning is typically used in cloud-based systems handling big data.
  • Indexes are organizational tags used to locate data.
  • Indexes can only locate one section of a table at a time.
  • Data partitioning is the process of dividing a database into distinct, logical parts.

24. Fill in the blank: Fragmented data occurs when data is broken up into many pieces that are not_____, often as a result of using the data frequently.

  • stored together
  • sorted and filtered
  • structured
  • labeled

25. When evaluating the workload of a database system, what does a business intelligence professional consider? Select all that apply.

  • Context
  • Transactions
  • System commands
  • Queries and analyses

26. A business intelligence team is optimizing the performance of their database. What does this involve? Select all that apply.

  • Comparing workload to cost
  • Identifying better data sources and structures
  • Evaluating the effectiveness of the team’s spreadsheets
  • Examining resource use

27. Fill in the blank: A business intelligence team uses _____ to divide their cloud database system into logical parts. This helps improve query processing and manageability.

  • data partitioning
  • the SPLIT function
  • database migration
  • metadata

28. A business intelligence team can cause _____ when two or more data analysts attempt to use a single data resource in a conflicting way.

  • repetition
  • annotation
  • contention
  • verification

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