16 Questions
What is the first step in the data analysis process?
Data Collection
Where does internal data typically originate from?
CRM Software
What is the purpose of data cleaning in the data analysis process?
Ensure the quality and reliability of data
Which of the following is NOT a common step in data cleanup?
Increasing whitespace
What does data visualization aim to do?
Present data visually for easier analysis
Which technique is commonly used in data visualization?
Graphical representation like charts and graphs
What is the primary goal of data visualization?
To explore and understand data patterns
Which of the following is a common measure of central tendency in descriptive statistics?
Mean
Which of these is not a typical step in the data cleaning process?
Generating new variables
Which of the following is a measure of variability in descriptive statistics?
Standard deviation
What type of data visualization is typically used to display the distribution of a single variable?
Histogram
What is the primary purpose of data cleaning in the data analysis process?
To remove inconsistencies, errors, and missing values from the data
Which of the following is a common technique used in data visualization?
Bar charts
Where does external data typically originate from in the data collection process?
Publicly available databases and online sources
What is the primary goal of descriptive statistics in data analysis?
To summarize and describe the characteristics of the data
Which of the following is NOT a common step in the data collection process?
Analyzing the data
Study Notes
Basic Data Analytics
Data Collection
Data collection is the first step in the data analysis process. It involves gathering data from various sources, both internal and external to the organization. Internal data comes from within the business, such as CRM software, internal reports, and archives, while external data originates from outside the company, through surveys, questionnaires, and public data. Software plays a significant role in this phase, with analytics or business dashboard tools and reports from internal tools like CRMs providing internal data. External data is obtained using survey apps and other data collection tools.
Data Cleaning
Once the data is collected, it must be cleaned before analysis begins. Data cleaning, also called data cleansing, is essential to ensure the quality and reliability of the data. It involves checking the data for errors and inconsistencies and correcting or removing them. This step is crucial for obtaining accurate and meaningful results from the analysis. Data cleanup looks different based on the type of data; it may include removing unnecessary information, addressing structural errors, deleting duplicates, trimming whitespace, and verifying human input for accuracy.
Data Visualization
Data visualization is the process of presenting data visually, making it easier to understand and analyze. Graphical representation of data, such as charts and graphs, are common visualization techniques. Data visualization helps to make complex data more comprehensible and provides a clear picture of the findings. Tools like Power BI, Tableau, and Excel are popular for data visualization and presentation purposes.
Descriptive Statistics
Descriptive statistics are used to describe and summarize data. Commonly used descriptive statistics include mean, median, mode, standard deviation, and percentiles. These measures provide an overview of the distribution of the data and help to identify central tendencies, dispersion, and skewness. Understanding descriptive statistics is crucial for interpreting and presenting data accurately.
Learn about essential concepts in data analytics, including data collection, cleaning, visualization, and descriptive statistics. Understand the importance of each step in the data analysis process and how it contributes to deriving meaningful insights from data.
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