Comprehensive Solutions
What is data analytics?
- The process of analyzing data to extract insights
- The process of encrypting data to keep it secure
- The process of storing data in a secure location for future use
- The process of collecting data from various sources Correct Answer - The
process of analyzing data to extract insights
What is data science?
- The practice of using statistical methods to extract insights from data
- A field that involves creating data visualizations to provide insights
- The process of creating computer programs to automate tasks
- The study of how computers interact with human language Correct
Answer - The practice of using statistical methods to extract insights from
data
How is data science different from data analytics?
- Data science focuses more on tracking experimental data, and data analytics
is based on statistical methods and hypotheses.
,- Data science focuses on developing new algorithms and models, while data
analytics focuses on using existing models to analyze data.
- Data science focuses more on data visualization, while data analytics focuses
on data cleaning and preprocessing.
- Data science involves creating new algorithms, while data analytics uses
existing statistical methods. Correct Answer - Data science focuses on
developing new algorithms and models, while data analytics focuses on using
existing models to analyze data.
Which comparison describes the difference between data analytics and data
science?
- Data analytics focuses on descriptive analysis, while data science focuses on
prescriptive analysis.
- Data analytics is the process of analyzing data to extract insights, while data
science involves building and testing models to make predictions.
- Data analytics focuses on statistics, and data science mainly focuses on
qualitative reasoning.
- Data science involves analyzing data from structured sources, while data
analytics involves analyzing data from unstructured sources. Correct
Answer - Data analytics is the process of analyzing data to extract insights,
while data science involves building and testing models to make predictions.
Which type of data analytics project aims to determine why something
happened in the past?
- Diagnostic
,- Descriptive
- Predictive
- Prescriptive Correct Answer - Diagnostic
What are the different types of data analytics projects?
- Data warehousing, data mining, data visualization, and business intelligence
- Regression analysis, time series analysis, text analytics, and network analysis
- Data collection, data cleaning, data transformation, and data visualization
- Descriptive, diagnostic, predictive, and prescriptive analytics Correct
Answer - Descriptive, diagnostic, predictive, and prescriptive analytics
What is the difference between exploratory and confirmatory data analytics
projects?
- Exploratory projects involve testing hypotheses and finding patterns in data,
while confirmatory projects involve verifying existing hypotheses.
- Exploratory projects involve analyzing data that is already structured, while
confirmatory projects involve analyzing unstructured data.
- Exploratory projects involve analyzing large datasets, while confirmatory
projects involve analyzing smaller datasets.
- Exploratory projects involve analyzing data from a single source, while
confirmatory projects involve integrating data from multiple sources.
Correct Answer - Exploratory projects involve testing hypotheses and finding
patterns in data, while confirmatory projects involve verifying existing
hypotheses.
, NOT CORRECT
Which project is considered a data analytics project?
- Developing a recommendation system to suggest new products to customers
based on their past purchases
- Creating a dashboard to visualize sales data and monitor inventory levels for
a grocery store chain
- Building a predictive model to forecast stock prices for a financial services
company
- Designing a database schema to store customer information for a retail store
Correct Answer - Creating a dashboard to visualize sales data and monitor
inventory levels for a grocery store chain
Why is quality control/assurance crucial for data engineers in a data analytics
project?
- It ensures that the data is analyzed in a timely manner.
- It ensures that the data is stored in a secure location.
- It ensures that the data is accurate and reliable.
- It ensures that the data is accessible to all stakeholders. Correct Answer -
It ensures that the data is accurate and reliable.
What does a data analyst do in a data analytics project?