Final answer:
The foundational elements of big data analytics are hardware, software, data management, and end-users. These components are crucial for storing, processing, and analyzing large datasets, as well as making use of the generated insights.
Step-by-step explanation:
The building blocks of big data analytics are typically seen as a combination of technology and processes that enable an organization to analyze large volumes of data. The correct option that lists these foundational elements is a) Hardware, software, data management, and end-users. These components represent the core on which big data analytics is built.
- Hardware: The physical infrastructure required to store and process large datasets. This includes servers, data centers, and cloud computing resources.
- Software: The applications and tools used to process and analyze data, such as databases, analytics software, and machine learning algorithms.
- Data management: Practices that ensure the data's quality, security, and accessibility, including data integration, warehousing, and governance.
- End-users: The people who make use of the insights generated from big data analytics to make decisions, such as business analysts, data scientists, and decision-makers.
Options b) and c) mention specific technologies (Hadoop, Spark) and techniques (data mining) which are parts of the larger big data ecosystem but not foundational blocks themselves. Option d) incorrectly refers to web-users instead of the broader category of end-users.