A client approaches Accenture for a solution to collate the large amounts of data it has collected over the years from various sources. Which solution would help the client pool their data together?
A: a DevOps solution
B: an Agile solution
C: a machine learning solution
D: a cloud analytics solution
Answer: A client approaches Accenture for a solution to collate the large amounts of data it has collected over the years from various sources.
Option( D) a cloud analytics solution would help the client pool their data together.
A cloud analytics result would help the customer pool their data together.
Cloud analytics describes the application of analytic algorithms in the cloud against data in a private or public cloud to deliver a result of interest then.
Cloud analytics involves deploying scalable cloud computing with powerful analytic software to identify data patterns and extract new insights.
More and more businesses rely on data analysis to gain a competitive advantage, advance scientific discovery, or improve life in all sorts of ways.
Data analytics has therefore become an increasingly valuable tool as the quantity and the value of data continues to climb.
Users can store the pool of resources, or retrieve them, from the buckets in a cloud analytics solution, while a Database may be a repository that helps to pool vast amounts of data together.
Cloud storage, or more accurately, cloud buckets, is the name of the repository.
The guarantee that it undertakes is that the data is collected accurately and timely.
The database may be a repository that helps pool large amounts of data together.
Cloud analytics is often associated with artificial intelligence (AI), machine learning (ML), and deep learning (DL). And it is commonly used in industrial applications such as scientific research in genomics or in oil and gas fields, business intelligence, security, Internet of Things (IoT), and many others.