Data Lake — Learn free

Self-check

Questions 1–10 of 10

1. What is a data lake?
Question 1A. A centralised repository that stores structured, semi-structured and unstructured data in its raw formB. A normalised relational database for transactionsC. A department-level analytical martD. A virtual layer over source systemsE. A pre-aggregated multidimensional cube
2. What challenge led to the emergence of the data lake?
Question 2A. Data warehouses were too expensive to licenseB. Warehouses handled structured data well but were not designed to ingest, store or process semi-structured and unstructured data at scaleC. OLTP systems could not process transactions fast enoughD. Regulators demanded raw data retentionE. Relational databases stopped supporting SQL
3. What does the schema-on-read philosophy of a data lake mean?
Question 3A. Data must be modelled and cleansed before it is loadedB. Data is ingested quickly without upfront modelling, and structure is applied later when it is analysedC. Only data with a predefined schema can be readD. Schemas are read from the source system's catalogueE. Data is encrypted before reading
4. On which storage technologies does a data lake architecture typically rest?
Question 4A. Tape libraries and optical discsB. HDFS in its early days and, more recently, cloud object storage such as Amazon S3, Azure Data Lake Storage or Google Cloud StorageC. Relational databases such as Oracle and SQL ServerD. In-memory caches such as RedisE. Spreadsheets shared on a network drive
5. Why did data lake storage make it feasible to retain information that was once discarded?
Question 5A. Because it compresses data to zeroB. Because it holds massive volumes of diverse data at low cost, even data that does not fit a relational schemaC. Because it deletes duplicates automaticallyD. Because regulators pay for the storageE. Because it only stores summaries
6. In the healthcare example, which data type is described as semi-structured?
Question 6A. Patient recordsB. Billing dataC. XML-based lab resultsD. X-ray and MRI imagesE. Physician notes
7. In the healthcare data lake example, which technique is applied to doctors' notes?
Question 7A. Computer visionB. Statistical analysisC. Natural language processingD. Schema-on-write modellingE. Referential integrity checks
8. What is a data swamp?
Question 8A. A data lake stored on-premises rather than in the cloudB. A data lake that has degraded into a repository where data is plentiful but poorly catalogued, inconsistent and hard to useC. A data lake that contains only structured dataD. A backup copy of a data lakeE. A data lake with too little data
9. Which of the following is NOT one of the practices modern data lake implementations emphasise to preserve usability?
Question 9A. Metadata managementB. Data cataloguesC. Access controlsD. Lifecycle governanceE. Mandatory upfront 3NF modelling
10. How does a data lake relate to a data warehouse?
Question 10A. It replaces the warehouse entirelyB. It complements the warehouse by addressing new forms of information and supporting advanced analytics, machine learning and real-time decision-makingC. It is a smaller subset of the warehouseD. It is the same thing under a new nameE. It is a warehouse without any governance