Exploring Data Analytics and Technology

What is data analytics?

• Data analytics refers to the process of creating software applications.

• Data analytics is the process of examining data sets to uncover insights, trends, and patterns that inform business decisions.

• Data analytics is the art of painting with data.

• Data analytics is the study of animal behavior.

Name three types of data analytics.

• Exploratory, Analytical, Operational

• Qualitative, Quantitative, Mixed

• Descriptive, Predictive, Prescriptive

• Static, Dynamic, Interactive

What role does technology play in data analytics?

• Technology plays a crucial role in data analytics by facilitating data collection, processing, analysis, and visualization.

• Technology complicates the data analytics process.

• Technology is irrelevant to data analytics.

• Data analytics only requires human intuition, not technology.

Define big data and its significance.

• Big data refers to small datasets that are easy to analyze.

• Big data is a type of software used for data entry.

• Big data is large and complex datasets that require advanced tools for processing and analysis, significant for deriving insights and driving decision-making.

• Big data is only relevant for social media platforms.

What is the difference between structured and unstructured data?

• Structured data is only found in databases; unstructured data is only found in spreadsheets.

• Structured data is organized and easily searchable; unstructured data is unorganized and complex to analyze.

• Structured data is always in text format; unstructured data is only in numerical format.

• Structured data is difficult to analyze; unstructured data is simple and straightforward.

Explain the concept of data visualization.

• Data visualization is only about creating charts and graphs.

• Data visualization is the process of collecting raw data without analysis.

• Data visualization refers to the use of text to convey information.

• Data visualization is the graphical representation of information and data.

What tools are commonly used for data analysis?

• Python, R, Excel, Tableau, SQL

• Notepad

• Photoshop

• PowerPoint

How does machine learning relate to data analytics?

• Machine learning only deals with unstructured data.

• Machine learning is a subset of data analytics that automates the process of extracting insights and making predictions from data.

• Data analytics is a type of machine learning.

• Machine learning is the same as data analytics.

What is the importance of data quality in analytics?

• Data quality only affects the visual presentation of analytics.

• Data quality is essential for accurate and reliable analytics.

• High data quality guarantees immediate business success.

• Data quality is irrelevant for effective decision-making.

Describe a real-world application of data analytics.

• In healthcare, data analytics is applied to improve patient care and operational efficiency.

• In agriculture, data analytics is primarily used for planting schedules.

• In education, data analytics is only applied to grade students.

• In finance, data analytics is used solely for predicting stock prices.