Data Analytics Quiz

What is Data Analytics?

• The process of storing data in a database.

• The process of analyzing raw data to uncover trends and patterns.

• The visualization of data using graphs and charts.

• The collection of random data from various sources.

What does "Dirty Data" mean?

• Data stored in the cloud.

• Data that is inaccurate, inconsistent.

• Encrypted data for security.

• Large datasets from social media.

Is Data Analytics and Business Analytics the Same?

• Yes, they are completely identical.

• No, data analytics focuses on data insights while business analytics focuses on business decisions.

• Yes, but only in terms of big data.

• No, data analytics is only for IT, while business analytics is for management.

Which of the Following is NOT a Tool of Data Analytics?

• Tableau

• Excel

• Hadoop

• Photoshop

Is Data Analytics Required for All Companies?

• No, only technology companies need it.

• Yes, all companies benefit from data analytics

• No, small businesses do not benefit from data analytics.

• Yes, but only in the retail industry.

What is the Difference Between Structured and Unstructured Data?

• Structured data is organized; unstructured data is not.

• Unstructured data is only found in small businesses.

• Structured data cannot be analyzed.

• Unstructured data is stored in Excel files.

How Does Data Analytics Help MIS?

• It automates reports and provides actionable insights.

• It replaces MIS completely.

• It stores customer data securely.

• It is only useful for financial reports.

What is Big Data Analytics?

• Analyzing small datasets to identify trends.

• Using advanced tools to analyze large and complex datasets.

• A type of dashboard for visualizing data.

• Data that is stored in traditional databases.

What is Preprocessing in Data Analytics?

• A process for storing data in the cloud.

• A step to clean and prepare data for analysis.

• A method for building predictive models.

• A tool for creating business strategies.

What is the Purpose of Data Mining?

• To ensure data security and privacy.

• To extract useful information from large datasets.

• To store data in a cloud environment.

• To create reports for management.