Data Analyst Flashcards
What is data collection?
Collecting and gathering large datasets, including databases, surveys, and other data sources from various platforms
Example: Collecting customer feedback surveys to analyze customer satisfaction levels
What is data cleaning, preparation, and processing?
Cleaning and preparing datasets for analysis by correcting data errors, removing duplicates, and reviewing accuracy; these processes are also known as data filtering, data integration, data classification, data munging, and data summarization
Example: Removing duplicate entries in a dataset to ensure accurate analysis results
What is data analysis?
Utilizing statistical methods and data visualization tools to analyze large datasets, identify trends, and compile insights to assist organizations when making business decisions
Example: Using regression analysis to identify the correlation between marketing spending and sales revenue
What is data reporting and visualization?
Creating clear, concise reports and visuals that easily communicate findings to team members and key stakeholders
Example: Creating a dashboard with interactive charts to showcase sales performance
What is predictive analysis?
Using algorithms to assist with predicting trends and future outcomes based on historical data
Example: Using machine learning algorithms to predict customer churn rates
What is data-driven decision-making?
Collaborating with various team members and stakeholders to identify opportunities for improvement to make data-driven decisions
Example: Analyzing customer behavior data to make informed decisions on product development
What is continuous improvement?
Involves professional development, continuously monitoring and evaluating the effectiveness of decision-making processes, and recommending improvements to drive better outcomes; data analysts must stay current with the latest trends and tools within the field
Example: Attending data analytics workshops to stay updated on industry best practices
What are the responsibilities of a Data Analyst?
Data collection, data cleaning, preparation and processing, data analysis, data reporting and visualization, predictive analysis, data driven decision making and continuous improvement.
