Question 1

Why is Veracity crucial in Big Data analytics?

Accepted Answer

Veracity in Big Data refers to the accuracy and reliability of the data being analysed. Ensuring veracity is crucial because the value of insights derived from Big Data hinges on the truthfulness of the underlying data. Without reliable data, decision-makers may draw incorrect conclusions, potentially leading to flawed strategies and outcomes.

Question 2

How does Big Data contribute to urban planning in Smart Cities?

Accepted Answer

Big Data plays a pivotal role in smart cities by harnessing data from sensors, traffic cameras, and citizen interactions. This data is analysed to optimise transportation systems, improve energy efficiency, and enhance public services. The insights derived from Big Data contribute to efficient urban planning, creating smarter and more sustainable cities.

Question 3

What is the role of an agile approach in Big Data analytics?

Accepted Answer

An agile approach in Big Data analytics involves adopting flexible methodologies that allow for rapid experimentation and iteration. This approach is essential in the dynamic landscape of Big Data, enabling organisations to adapt quickly to changing business requirements. Agile analytics fosters collaboration between different functions, promoting a holistic understanding of data needs.

Question 4

How do organisations address the ethical considerations of using Big Data?

Accepted Answer

Organisations address ethical considerations in Big Data by establishing clear guidelines and practices for the responsible use of data. This includes obtaining informed consent for data collection, ensuring data privacy, and transparently communicating how data will be used. Ethical considerations in Big Data underscore the importance of balancing innovation with ethical responsibility.

Question 5

What are the key factors influencing the salaries of Big Data engineers?

Accepted Answer

The salaries of Big Data engineers are influenced by factors such as expertise in designing and maintaining infrastructure for processing large datasets, experience in distributed computing architectures like Apache Hadoop, and the ability to ensure scalability and security. The complexity of managing vast amounts of data and implementing effective solutions contributes to the demand for skilled Big Data engineers, influencing their salaries.

Big data in data science examples

Everything You Need to Know About Big Data in Data Science