Data Silos — Learn free

Self-check

Questions 1–10 of 10

1. What is a Data Silo?
Question 1A. A datastore that is not accessible from the external world because of technology barriersB. A datastore that is only accessible to its relevant stakeholdersC. A datastore that stores data in a unified data modelD. A datastore used exclusively for decision supportE. A datastore that has been migrated to the cloud
2. How does a Data Island differ from a Data Silo?
Question 2A. A Data Island holds confidential data; a Data Silo never doesB. A Data Island is on-premises; a Data Silo is in the cloudC. A Data Island is not accessible from the external world; a Data Silo is accessible only to relevant stakeholdersD. A Data Island is a process; a Data Silo is a technologyE. There is no difference; the two terms are interchangeable
3. Which of the following is NOT given as a reason why data ends up in a silo?
Question 3A. The datastore hosts confidential data such as finance or audit dataB. The data is semi-structured or unstructured and not readableC. Data quality is so low that sharing it could lead to wrong decisionsD. The data has already been loaded into a data warehouseE. Separate database instances are created for different development teams
4. Why are separate database instances sometimes created for different development teams?
Question 4A. To reduce licensing costsB. So that management can compare the teams' outputC. To enforce data privacy regulationsD. So that if one team changes data or table structures, other teams are not impactedE. To increase query performance
5. Why should Data Silos not exist in a data-driven organisation?
Question 5A. Because they make the same kind of data impossible to correlate across systemsB. Because they consume too much storageC. Because they are not permitted by database vendorsD. Because they are always hosted on legacy hardwareE. Because they cannot be encrypted
6. Which problem did the Data Warehouse come into being to solve?
Question 6A. The lack of transaction processing capacityB. Source-system data sitting in silos, making cross-departmental reporting slow and hard to validateC. The absence of network connectivity between citiesD. The need to encrypt confidential finance dataE. The cost of cloud compute resources
7. In Data Warehousing, in what form is data from all the source systems brought together?
Question 7A. As separate copies, one per departmentB. As unstructured files in an object storeC. In a unified data model, forming a single source of truth for decision supportD. In per-team development instancesE. As a read-only Data Island
8. Which examples of siloed source systems does *I Am Datapedia!* say almost all medium to large organisations have?
Question 8A. Mainframe, Hadoop and KafkaB. Data Lake, Data Mart and OLAP CubeC. Tableau, Power BI and QlikD. Landing, Staging and Transformed zonesE. CRM, ERP, Procurement and HR systems
9. Which two difficulties arise when management wants information from several siloed systems?
Question 9A. Extraction is very time-consuming and data quality is hard to validateB. Data encryption and data maskingC. Licensing and hardware procurementD. Duplicate primary keys and missing indexesE. Slow network links and limited RAM
10. Which concepts describe the current era in which data silos are discouraged?
Question 10A. Per-team database instancesB. Data islands and floppy-drive transfersC. Departmental ownership and restricted sharingD. Manual reconciliation and canned reportsE. Data democratisation and data liberalisation as a norm