Exploring Big Data Concepts

What is Big Data Analytics and why is it important?

• Big Data Analytics focuses solely on social media data.

• Big Data Analytics is important because it enables organizations to make data-driven decisions, improve operational efficiency, enhance customer experiences, and gain a competitive advantage by leveraging insights from vast amounts of data.

• Big Data Analytics is a method for storing data without analysis.

• Big Data Analytics is only useful for large corporations.

Name three popular tools used for data visualization.

• Excel

• Tableau, Power BI, Matplotlib

• RStudio

• Google Sheets

How does machine learning enhance big data analysis?

• Machine learning enhances big data analysis by identifying patterns, making predictions, and automating decision-making.

• Machine learning eliminates the need for data analysis.

• Machine learning slows down big data processing.

• Machine learning only focuses on small datasets.

What are the key challenges in ensuring data privacy?

• Increased data storage capacity

• Enhanced user interface design

• Faster internet connectivity

• Key challenges in ensuring data privacy include data breaches, regulatory compliance, user consent management, data security, and technological vulnerabilities.

Explain the concept of data ethics in the context of big data.

• Data ethics in big data ignores user consent and privacy.

• Data ethics in big data refers to the responsible use of data, focusing on privacy, consent, transparency, and accountability.

• Data ethics is solely about data storage practices.

• Data ethics focuses only on data analysis techniques.

What role does Hadoop play in big data processing?

• Hadoop is a programming language for data processing.

• Hadoop plays a crucial role in big data processing by providing a scalable and fault-tolerant framework for storing and processing large volumes of data.

• Hadoop is a database management system for small data sets.

• Hadoop is primarily used for real-time data analytics.

List two advantages of using cloud-based data visualization tools.

• Limited storage capacity.

• Complex installation process.

• High upfront costs.

• 1. Accessibility from any device. 2. Real-time collaboration.

How can bias in machine learning algorithms affect big data outcomes?

• Bias has no impact on machine learning outcomes.

• Bias improves the accuracy of predictions in big data.

• Bias in machine learning algorithms can lead to skewed predictions and unfair outcomes in big data.

• Bias in algorithms ensures equal treatment for all data points.

What are some common techniques for data cleaning in big data analytics?

• Common techniques for data cleaning include removing duplicates, handling missing values, standardizing formats, filtering outliers, and validating data.

• Implementing real-time data streaming

• Using machine learning for data visualization

• Increasing data size for better analysis

Why is it crucial to have a data governance framework in place?

• It eliminates all data-related risks.

• It guarantees unlimited data access for everyone.

• It reduces the need for data analysis.

• It ensures data quality, security, compliance, and informed decision-making.