Fundamentals of Data Analytics Flashcards

What is the primary purpose of data analytics?

Answer: To extract insights and support decision-making.

Data analytics is the systematic process of examining raw data to discover meaningful patterns, correlations, and insights. Its primary purpose is to transform data into actionable information, enabling businesses and organizations to make more informed, data-driven decisions and improve various aspects of their operations and strategies.

Which of the following best describes structured data?

Answer: Data organized in rows and columns.

Structured data refers to information that is highly organized and follows a predefined format, making it easily searchable and analyzable. It typically resides in relational databases or spreadsheets, where data elements are arranged in tables with rows and columns, each having a specific type and meaning, ensuring consistency and clarity.

What is the first step in the data analytics process?

Answer: Defining the problem or objective.

Before diving into data collection or analysis, the crucial first step in any data analytics project is clearly defining the business problem or objective that needs to be addressed. This ensures that all subsequent efforts—from data gathering to visualization—are focused, relevant, and aligned with achieving a specific, measurable goal.

Which type of analytics predicts future trends based on historical data?

Answer: Predictive analytics.

Predictive analytics is a type of data analytics that uses historical data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes or trends. It aims to forecast what might happen next, enabling proactive decision-making, risk assessment, and strategic planning based on anticipated events.

What is a key characteristic of big data?

Answer: High volume, velocity, and variety.

Big data is characterized by the 'Three Vs': Volume, Velocity, and Variety. Volume refers to the immense amount of data generated, Velocity to the speed at which data is generated and processed, and Variety to the diverse types and formats of data. These characteristics present unique challenges and opportunities for storage, processing, and analysis.

Which programming language is widely used for data analysis?

Answer: Python

Python is widely recognized as a leading programming language for data analysis due to its extensive ecosystem of libraries. Libraries like Pandas, NumPy, SciPy, and Scikit-learn provide powerful tools for data manipulation, statistical analysis, machine learning, and visualization. Its readability and versatility make it a preferred choice for data professionals.