An organization has created a medical fitness app and wants to store a very large amount of data about exercise times, activity, and calories burned for later analysis.
Which data management solution should the organization use?
I strongly think that B is the correct answer
Reasoning:
I read an article from Qlik.com that compares DataLake and DataWarehouse.
In that i noticed 2 factors that bring out the difference.
1. DataLake better at handling unstructured Data whereas Datawarehouse is better at structured data
2. DataLake shines are real-time analytics and nothing is said about real-time analytics for Datawarehouse.
in the given question the data is primarily structured and explicitly mentions that data is required for analysis "Later". hence B should be the correct match/answer.
B. Data warehouse is correct. Because the data about exercise times, activity, and calories burned etc. falls under either structured data or semi-structured data which data warhouse (like BigQuery) can handle really well. And it is mentioned in question that data is needed for later analysis. Data warehouse (like BigQuery) can help in this analysis.
B. Data warehouse is correct. Because the data about exercise times, activity, and calories burned etc. falls under either structured data or semi-structured data which data warhouse (like BigQuery) can handle really well. And it is mentioned in question that data is needed for later analysis. Data warehouse (like BigQuery) can help in this analysis.
A. Data lake
A data lake is a centralized repository that stores all types of data, including structured, semi-structured, and unstructured data. Data lakes are often used to store large amounts of data for later analysis.
The data that the fitness company wants to store is structured and/or semi-structured and there's no mention of BLOBs or anything like that. The answer is B.
An organization that has created a medical fitness app and wants to store a very large amount of data about exercise times, activity, and calories burned for later analysis should use a data lake (A). A data lake is a centralized repository that allows organizations to store all their structured and unstructured data at any scale. Data can be stored in its raw form and can be analyzed later using big data processing tools.
Agree on B. Since there is no requirement for semi-structured and unstructured data in raw form, and the data mentioned in the question large amounts of structured data, I would go with Data Warehouse.
I would choose Data Warehouse as it is a solution to store Big Data and serve it for analytics services. For example, BigQuery has an ML solution embedded on it.
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