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Free DP-900 Exam Braindumps (page: 16)

Page 15 of 72
PDF with 306 Questions

HOTSPOT (Drag and Drop is not supported)
Select the answer that correctly completes the sentence.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




A data analyst's primary skill set revolves around data acquisition, handling, and processing.
Incorrect:
* A data engineer requires an intermediate level understanding of programming to build thorough algorithms along with a mastery of statistics and math.
* A data scientist needs to be a master of both worlds. Data, stats, and math along with in-depth programming knowledge for Machine Learning and Deep
Learning.


Reference:

https://www.edureka.co/blog/data-analyst-vs-data-engineer-vs-data-scientist/



HOTSPOT (Drag and Drop is not supported)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

  1. See Explanation section for answer.

Answer(s): A

Explanation:



Box 1: No
OLTP workloads: Heavy writes, moderate reads

Box 2: No
OLAP databases are optimized for heavy read, low write workloads.

Box 3: Yes
Data warehouses are optimized for read access.


Reference:

https://learn.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-transaction-processing
https://learn.microsoft.com/en-us/azure/architecture/data-guide/relational-data/data-warehousing



A retail point of sale (POS) system is an example of which type of solution?

  1. a data warehouse
  2. online analytical processing (OLAP)
  3. extract, transform, and load (ETL)
  4. online transaction processing (OLTP)

Answer(s): D



HOTSPOT (Drag and Drop is not supported)
Select the answer that correctly completes the sentence.

  1. See Explanation section for answer.

Answer(s): A

Explanation:





Box: vertexes
Graph databases: Stores data as nodes (vertices/vertexes) and relationships (edges). Vertices typically store object information while edges represent the relationships between nodes. We can have a SQL-like query language in our graph databases.


Reference:

https://towardsdatascience.com/introduction-to-nosql-graph-databases-fb2feac7a36






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