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    Data Visualization Techniques, Tools and Concepts

    Data Visualization Techniques: In the world of Big Data, data visualization techniques are essential to analyze massive amounts of information

    Data visualization is a graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. This blog on data visualization techniques will help you understand detailed techniques and benefits.

    In the world of Big Data, data visualization in Python tools and technologies are essential to analyze massive amounts of information and make data-driven decisions.

    Contributed by: Dinesh

    Benefits of good data visualization

    Our eyes are drawn to colours and patterns. We can quickly identify red from blue, and square from the circle. Our culture is visual, including everything from art and advertisements to TV and movies.

    Data visualization is another form of visual art that grabs our interest and keeps our eyes on the message. When we see a chart, we quickly see trends and outliers. If we can see something, we internalize it quickly. It’s storytelling with a purpose. If you’ve ever stared at a massive spreadsheet of data and couldn’t see a trend, you know how much more effective a visualization can be. The uses of Data Visualization as follows.

    Powerful way to explore data with presentable results.

    Primary use is the pre-processing portion of the data mining process.

    Supports the data cleaning process by finding incorrect and missing values.

    For variable derivation and selection means to determine which variable to include and discarded in the analysis.

    Also play a role in combining categories as part of the data reduction process.

    Data Visualization Techniques

    Box plots Histograms Heat maps Charts Tree maps

    Word Cloud/Network diagram

    Box Plots

    The image above is a box plotA boxplot is a standardized way of displaying the distribution of data based on a five-number summary (“minimum”, first quartile (Q1), median, third quartile (Q3), and “maximum”). It can tell you about your outliers and what their values are. It can also tell you if your data is symmetrical, how tightly your data is grouped, and if and how your data is skewed.

    A box plot is a graph that gives you a good indication of how the values in the data are spread out. Although box plots may seem primitive in comparison to a histogram or density plot, they have the advantage of taking up less space, which is useful when comparing distributions between many groups or datasets. For some distributions/datasets, you will find that you need more information than the measures of central tendency (median, mean, and mode). You need to have information on the variability or dispersion of the data.

    List of Methods to Visualize Data

    Column Chart: It is also called a vertical bar chart where each category is represented by a rectangle. The height of the rectangle is proportional to the values that are plotted.Bar Graph: It has rectangular bars in which the lengths are proportional to the values which are represented.Stacked Bar Graph: It is a bar style graph that has various components stacked together so that apart from the bar, the components can also be compared to each other.Stacked Column Chart: It is similar to a stacked bar; however, the data is stacked horizontally.Area Chart: It combines the line chart and bar chart to show how the numeric values of one or more groups change over the progress of a viable area.Dual Axis Chart: It combines a column chart and a line chart and then compares the two variables.Line Graph: The data points are connected through a straight line; therefore, creating a representation of the changing trend.Mekko Chart: It can be called a two-dimensional stacked chart with varying column widths.Pie Chart: It is a chart where various components of a data set are presented in the form of a pie which represents their proportion in the entire data set.Waterfall Chart: With the help of this chart, the increasing effect of sequentially introduced positive or negative values can be understood.Bubble Chart: It is a multi-variable graph that is a hybrid of Scatter Plot and a Proportional Area Chart.Scatter Plot Chart: It is also called a scatter chart or scatter graph. Dots are used to denote values for two different numeric variables.Bullet Graph: It is a variation of a bar graph. A bullet graph is used to swap dashboard gauges and meters.Funnel Chart: The chart determines the flow of users with the help of a business or sales process.Heat Map: It is a technique of data visualization that shows the level of instances as color in two dimensions.

    Five Number Summary of Box Plot

    Minimum Q1 -1.5*IQRFirst quartile (Q1/25th Percentile)”: The middle number between the smallest number (not the “minimum”) and the median of the datasetMedian (Q2/50th Percentile)”: the middle value of the datasetThird quartile (Q3/75th Percentile)”: the middle value between the median and the highest value (not the “maximum”) of the dataset.

    स्रोत : www.mygreatlearning.com

    What Is Data Visualization? Definition & Examples

    Data visualization is the graphical representation of information. It uses visual elements like charts to provide an accessible way to see and understand data.

    In our increasingly data-driven world, it’s more important than ever to have accessible ways to view and understand data. After all, the demand for data skills in employees is steadily increasing each year. Employees and business owners at every level need to have an understanding of data and of its impact.

    That’s where data visualization comes in handy. With the goal of making data more accessible and understandable, data visualization in the form of dashboards is the go-to tool for many businesses to analyze and share information.

    In this article, we'll cover:

    The definition of data visualization

    Advantages and disadvantages of data visualization

    Why data visualization is important

    Data visualization and big data

    Data visualization examples

    Tools and software of data visualization

    More about data visualization

    What is data visualization?

    Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends, outliers, and patterns in data. Additionally, it provides an excellent way for employees or business owners to present data to non-technical audiences without confusion.

    In the world of Big Data, data visualization tools and technologies are essential to analyze massive amounts of information and make data-driven decisions.

    What are the advantages and disadvantages of data visualization?

    ​​​​Something as simple as presenting data in graphic format may seem to have no downsides. But sometimes data can be misrepresented or misinterpreted when placed in the wrong style of data visualization. When choosing to create a data visualization, it’s best to keep both the advantages and disadvantages in mind.

    Advantages

    Our eyes are drawn to colors and patterns. We can quickly identify red from blue, and squares from circles. Our culture is visual, including everything from art and advertisements to TV and movies. Data visualization is another form of visual art that grabs our interest and keeps our eyes on the message. When we see a chart, we quickly see trends and outliers. If we can see something, we internalize it quickly. It’s storytelling with a purpose. If you’ve ever stared at a massive spreadsheet of data and couldn’t see a trend, you know how much more effective a visualization can be.

    Some other advantages of data visualization include:

    Easily sharing information.

    Interactively explore opportunities.

    Visualize patterns and relationships.

    Disadvantages

    While there are many advantages, some of the disadvantages may seem less obvious. For example, when viewing a visualization with many different datapoints, it’s easy to make an inaccurate assumption. Or sometimes the visualization is just designed wrong so that it’s biased or confusing.

    Some other disadvantages include:

    Biased or inaccurate information.

    Correlation doesn’t always mean causation.

    Core messages can get lost in translation.

    Why data visualization is important

    The importance of data visualization is simple: it helps people see, interact with, and better understand data. Whether simple or complex, the right visualization can bring everyone on the same page, regardless of their level of expertise.

    It’s hard to think of a professional industry that doesn’t benefit from making data more understandable. Every STEM field benefits from understanding data—and so do fields in government, finance, marketing, history, consumer goods, service industries, education, sports, and so on.

    While we’ll always wax poetically about data visualization (you’re on the Tableau website, after all) there are practical, real-life applications that are undeniable. And, since visualization is so prolific, it’s also one of the most useful professional skills to develop. The better you can convey your points visually, whether in a dashboard or a slide deck, the better you can leverage that information. The concept of the citizen data scientist is on the rise. Skill sets are changing to accommodate a data-driven world. It is increasingly valuable for professionals to be able to use data to make decisions and use visuals to tell stories of when data informs the who, what, when, where, and how.

    While traditional education typically draws a distinct line between creative storytelling and technical analysis, the modern professional world also values those who can cross between the two: data visualization sits right in the middle of analysis and visual storytelling.

    Data visualization and big data

    As the “age of Big Data” kicks into high gear, visualization is an increasingly key tool to make sense of the trillions of rows of data generated every day. Data visualization helps to tell stories by curating data into a form easier to understand, highlighting the trends and outliers. A good visualization tells a story, removing the noise from data and highlighting useful information.

    However, it’s not simply as easy as just dressing up a graph to make it look better or slapping on the “info” part of an infographic. Effective data visualization is a delicate balancing act between form and function. The plainest graph could be too boring to catch any notice or it make tell a powerful point; the most stunning visualization could utterly fail at conveying the right message or it could speak volumes. The data and the visuals need to work together, and there’s an art to combining great analysis with great storytelling.

    स्रोत : www.tableau.com

    Data Visualization MCQ 2022

    Data Visualization MCQ: Practice the best Data Visualization MCQ Questions, that checks your basic knowledge of Data Visualization Quiz. This Data Visualization Mock Test contains 20+ Multiple Choice Questions. apart from this, you can also download the Data Visualization MCQ PDF, completely free from the link given below.

    Data Visualization MCQ

    Last Updated: Jun 14, 2022,

    Posted in Interview Questions,

    21 Questions

    Take Data Visualization MCQ Test & Online Quiz to Test Your Knowledge

    We have listed below the best Data Visualization MCQ Questions, that check your basic knowledge of Data Visualization. This Data Visualization MCQ Test contains 20 Multiple Choice Questions. You have to select the right answer to check your final preparation for the Data Visualization Exam/Interviews. apart from this, you can also download the Data Visualization MCQ PDF, completely free from the link given below.

    1. What is data visualization?

    It is the graphical representation of information and data

    It is the numerical representation of information and data

    It is the character representation of information and data

    None of the above Powered By

    This is a modal window.

    No compatible source was found for this media.

    View Answer

    2. What is true about data visualization?

    Data Visualization helps users in analyzing a large amount of data in a simpler way

    Data Visualization makes complex data more accessible, understandable, and usable

    Data Visualization is a graphical representation of data

    All of the above View Answer

    3. Data visualization is also an element of the broader ............

    data process architecture

    data presentation architecture

    deliver presentation architecture

    None of the above View Answer

    4. Data visualization tools provide an accessible way to see and understand .................... in data.

    trends outliers patterns All of the above View Answer

    5. Which method shows hierarchical data in a nested format?

    Treemaps Scatter plots Area charts Population pyramids

    Download Free : Data Visualization MCQ PDF

    View Answer

    6. What are the common types of data visualization?

    Charts Tables Infographics All of the above View Answer

    7. What are specific examples of methods to visualize data?

    Area Chart Bubble Cloud

    Dot Distribution Map

    All of the above View Answer

    8. The importance of data visualization are ......................

    Leading the target audience to focus on business insights to discover areas that require attention

    Revealing previously unnoticed key points about the data sources to help decision makers compose data analysis reports

    Helping decision makers understand how the business data is being interpreted to determine business decisions

    All of the above View Answer

    9. What are the benefits of data visualization?

    Better analysis

    Identifying patterns

    Exploring business insights

    All of the above View Answer

    10. Which of the intricate techniques is not used for data visualization?

    Heat Maps Fever Maps Bullet Graphs Bubble Clouds View Answer

    11. ............. is used to query and edit graphical settings.

    par() plot() cum() anova() View Answer

    12. Which of the following lists names of variables in a data.frame?

    par() names() quantile() barchart() View Answer

    13. ................. groups values of a variable into larger bins.

    cut stem col.max(x) which.max(x) View Answer

    14. Deleting the grid lines in the table and the horizontal lines in the chart.

    increases the data-ink ratio

    decreases the data-ink ratio

    increases the Non-data-ink ratio

    does not affect the data-ink ratio

    View Answer

    15. ................. helps in designing effective tables and charts for data visualization.

    PivotTable Data-ink ratio Scatter charts Crosstabulation View Answer

    16. A useful chart for displaying multiple variables is the .............

    scatter chart

    scatter chart matrix

    two-dimensional graph

    stacked column and bar chart

    View Answer

    17. The charts that are helpful in making comparisons between ...............

    Bar charts column charts Pie charts

    Both Bar & Column Charts

    View Answer

    18. A system that merges maps and statistics to present data collected over different geographies ..................

    The heat map A geographical map

    Geographic information system

    None of the above View Answer

    19. A data visualization tool that updates in real time and gives multiple outputs is called .................

    a data dashboard a metrics table a data table None of the above View Answer

    20. The data dashboard for a marketing manager may have KPIs related to ...............

    current sales measures and sales by region

    current financial standing of the company.

    vehicle's current speed, fuel level, and engine temperature.

    None of the above View Answer

    21. A _____ is a line that provides an approximation of the relationship between the variables.

    स्रोत : www.onlineinterviewquestions.com

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