adplus-dvertising
frame-decoration

Question

How do data analytic algorithms help in optimizing Big Data solutions?

a.

By reducing data storage requirements.

b.

By speeding up data processing.

c.

By uncovering patterns and correlations for better decision-making.

d.

By compressing data to reduce its size.

Posted under Big Data Computing

Answer: (c).By uncovering patterns and correlations for better decision-making. Explanation:Data analytic algorithms help in optimizing Big Data solutions by uncovering patterns and correlations in the data, which can lead to better decision-making.

Engage with the Community - Add Your Comment

Confused About the Answer? Ask for Details Here.

Know the Explanation? Add it Here.

Q. How do data analytic algorithms help in optimizing Big Data solutions?

Similar Questions

Discover Related MCQs

Q. What is the trade-off that often exists between data ingestion speed, query response time, and data quality in Big Data solutions?

Q. What is the difference between OLTP and OLAP in the context of storage systems?

Q. How can distributed crawlers enhance the data mining process?

Q. What are faceted queries, and where are they especially useful?

Q. Why is the ability to process data in real-time important in Big Data solutions?

Q. What is the primary benefit of processing data in real-time in business scenarios?

Q. What are the two most important enabling technologies related to data access for computing in Big Data solutions?

Q. How does the type of indexing used in a Big Data system affect data retrieval operations?

Q. What is the purpose of an incremental indexing system like the one offered by Couchbase?

Q. In the context of Big Data, why is the modeling and management of data relationships important?

Q. How can high-speed cache stores be used in Big Data solutions?

Q. What is the purpose of using well-defined cache systems or temporary files in Big Data solutions?

Q. What is the role of metadata in Big Data access for data analysis?

Q. How can structured metadata benefit the process of data analysis in the financial sector?

Q. What are some examples of attributes that can be applied to data as metadata in Big Data solutions?

Q. How can data descriptors and metadata be used to save time in data analysis operations?

Q. What is the main purpose of ArrayDBMS in the context of Big Data solutions?

Q. What does Rasdaman offer in terms of query language and execution in the ArrayDBMS context?

Q. How is the conceptual model of Rasdaman ArrayDBMS structured?

Q. What is the role of metadata in describing data arrays in Rasdaman ArrayDBMS?