A picture is worth a thousand words \u2013 especially when you are trying to understand and gain insights from data. It is particularly relevant when you are trying to find relationships among thousands or even millions of variables and determine their relative importance. Organizations of all types and sizes generate data each minute, hour and day. Everyone \u2013 including executives, departmental decision makers, call center workers and employees on production lines \u2013 hopes to learn things from collected data that can help them make better decisions, take smarter actions and operate more efficiently.<\/p>\n
Line Graphs<\/strong><\/p>\n A line graph, or line chart, shows the relationship of one variable to another. They are most often used to track changes or trends over time (see Figure 1). Line charts are also useful when comparing multiple items over the same time period (see Figure 2). The stacking lines are used to compare the trend or individual values for several variables. You may want to use line graphs when the change in a variable or variables clearly needs to be displayed and\/or when trending or rate-of-change information is of value. It is also important to note that you shouldn\u2019t pick a line chart merely because you have data points. Rather, the number of data points that you are working with may dictate the best visual to use. For example, if you only have 10 data points to display, the easiest way to understand those 10 points might be to simply list them in a particular order using a table. When deciding to use a line chart, you should consider whether the relationship between data points needs to be conveyed. If it does, and the values on the X axis are continuous, a simple line chart may be what you need.<\/p>\n <\/p>\n Bar Charts<\/strong><\/p>\n Bar charts are most commonly used for comparing the quantities of different categories or groups (see Figure 3). Values of a category are represented using the bars, and they can be configured with either vertical or horizontal bars with the length or height of each bar representing the value. When values are distinct enough that differences in the bars can be detected by the human eye, you can use a simple bar chart. However, when the values (bars) are very close together or there are large numbers of values (bars) that need to be displayed, it becomes more difficult to compare the bars to each other. To help provide visual variance, bars can have different colors. The colors can be used to indicate such things as a particular status or range. Coloring the bars works best when most bars are in a different range or status. When all bars are in the same range or status, the color becomes irrelevant, and it is most visually helpful to keep the color consistent or have no coloring at all. Another form of a bar chart is called the progressive bar chart, or waterfall chart. A waterfall chart shows how the initial value of a measure increases or decreases during a series of operations or transactions. The first bar begins at the initial value, and each subsequent bar begins where the previous bar ends. The length and direction of a bar indicates the magnitude and type (positive or negative, for example) of the operation or transaction. The resulting chart is a stepped cascade that shows how the transactions or operations lead to the final value of the measure.<\/p>\n Scatter Plots<\/strong><\/p>\n A scatter plot (or X-Y plot) is a two-dimensional plot that shows the joint variation of two data items. In a scatter plot, each marker (symbols such as dots, squares and plus signs) represents an observation. The marker position indicates the value for each observation. Scatter plots also support grouping. When you assign more than two measures, a scatter plot matrix is produced. A scatter plot matrix is a series of scatter plots that displays every possible pairing of the measures that are assigned to the visualization. Scatter plots are useful for examining the relationship, or correlations, between X and Y variables. Variables are said to be correlated if they have a dependency on, or are somehow influenced by, each other. For example, \u201cprofit\u201d is often related to \u201crevenue\u201d \u2013 and the relationship that exists might be that as revenue increases profit also increases (a positive correlation). A scatter plot is a good way to visualize these relationships in data. In a scatter plot, you can also apply statistical analysis with correlation and regression. Correlation identifies the degree of statistical correlation between the variables in the plot. Regression plots a model of the relationship between the variables in the plot. Once you have plotted all of the data points using a scatter plot, you are able to visually determine whether data points are related. Scatter plots can help you gain a sense of how spread out the data might be or how closely related the data points are, as well as quickly identify patterns present in the distribution of the data (see Figure 4). Scatter plots are helpful when you have many data points. If you are working with a small set of data points, a bar chart or table may be a more effective way to display the information.<\/p>\n Pie Charts<\/strong><\/p>\n There is much debate around the value of pie charts, which are used to compare the parts of a whole. However, they can be difficult to interpret because the human eye has a hard time estimating areas and comparing visual angles. Another challenge with using a pie chart for analysis is that it is difficult to compare slices of the pie that are similar in size but not located next to each other. If you do use pie charts, they are most effective when there are limited components and when text and percentages are included to describe the content. By providing additional information, information consumers do not have to guess the meaning and value of each slice. If you choose to use a pie chart, the slices should be a percentage of the whole (see Figure 5). When designing reports or dashboards, another consideration for the efficacy of a pie chart is the amount of space the pie chart requires in the sizing of the report. Because of the round shape, pie charts require extra real estate, so they may be less than ideal when developing dashboards for small screens or mobile devices. Other charts may provide a better way to represent the same information in less space.<\/p>\n Visualizing Big Data<\/strong> Big data brings new challenges to visualization because of the large volumes, different varieties and varying velocities that must be taken into account. The cardinality of the columns you are trying to visualize should also be considered. One of the most common definitions of big data is data that is of such volume, variety and velocity that an organization must move beyond its comfort zone technologically to derive intelligence for effective decisions.<\/p>\n \u2022 Volume refers to the size of the data.<\/p>\n \u2022 Variety describes whether the data is structured, semistructured or unstructured.<\/p>\n \u2022 Velocity is the speed at which data pours in and how frequently it changes. Building upon basic graphing and visualization techniques, SAS Visual Analytics has taken an innovative approach to addressing the challenges associated with visualizing data. Using innovative, in-memory capabilities combined with SAS Analytics and data discovery, SAS provides new techniques based on core fundamentals of data analysis and the presentation of results.<\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":" A picture is worth a thousand words \u2013 especially when you are trying to understand and gain insights from data. It is particularly relevant when you are trying to find relationships among thousands or even millions of variables and determine their relative importance. Organizations of all types and sizes generate<\/p>\n","protected":false},"author":3,"featured_media":754,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[5],"tags":[],"class_list":["post-753","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-knowledgebase"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/11\/90charts.png.pagespeed.ce_.CVtP6o56PP.png?fit=381%2C345&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p7ISfL-c9","jetpack_likes_enabled":true,"jetpack-related-posts":[{"id":676,"url":"https:\/\/www.virtono.com\/community\/knowledgebase\/data-security-in-cloud-computing\/","url_meta":{"origin":753,"position":0},"title":"Data Security in Cloud Computing","author":"Daniel Draga","date":"October 3, 2016","format":false,"excerpt":"\u0097With the development of cloud computing, Data security becomes more and more important in cloud computing. This paper analyses the basic problem of cloud computing data security. . \u0097Cloud Computing provides the way to share distributed resources and services that belong to different organizations or sites. Since Cloud Computing share\u2026","rel":"","context":"In "Knowledgebase"","block_context":{"text":"Knowledgebase","link":"https:\/\/www.virtono.com\/community\/category\/knowledgebase\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/07\/IMG_2035.jpg?fit=1200%2C900&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/07\/IMG_2035.jpg?fit=1200%2C900&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/07\/IMG_2035.jpg?fit=1200%2C900&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/07\/IMG_2035.jpg?fit=1200%2C900&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/07\/IMG_2035.jpg?fit=1200%2C900&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":1006,"url":"https:\/\/www.virtono.com\/community\/knowledgebase\/what-is-object-storage-and-why-do-you-need-it\/","url_meta":{"origin":753,"position":1},"title":"What is Object Storage and Why do you need it","author":"Daniel Draga","date":"September 20, 2017","format":false,"excerpt":"By this time we are familiar with the tremendous amount of data that is being produced\u00a0at a massive scale every single day by every single \"smart\" device around us. Before going any further let us differentiate between structured and unstructured data and why structured data storage techniques are now obsolete.\u2026","rel":"","context":"In "Knowledgebase"","block_context":{"text":"Knowledgebase","link":"https:\/\/www.virtono.com\/community\/category\/knowledgebase\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2017\/09\/i_ObjectStorage_1.png?fit=400%2C250&ssl=1&resize=350%2C200","width":350,"height":200},"classes":[]},{"id":619,"url":"https:\/\/www.virtono.com\/community\/knowledgebase\/raid-and-its-types\/","url_meta":{"origin":753,"position":2},"title":"RAID and its TYPES","author":"Daniel Draga","date":"September 10, 2016","format":false,"excerpt":"RAID stands for an redundant array of independent drives Intelligently manages drives in unison performing data read\/write algorithms across drives delivering \u2013High levels of protection against downtime and data loss (mirroring) \u2013Larger storage volumes achievable \u2013Improved performance (striping) \u00a0 RAID Level Overview Selecting the proper RAID level for a specific\u2026","rel":"","context":"In "Knowledgebase"","block_context":{"text":"Knowledgebase","link":"https:\/\/www.virtono.com\/community\/category\/knowledgebase\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/09\/raid.jpg?fit=740%2C426&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/09\/raid.jpg?fit=740%2C426&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/09\/raid.jpg?fit=740%2C426&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/09\/raid.jpg?fit=740%2C426&ssl=1&resize=700%2C400 2x"},"classes":[]},{"id":763,"url":"https:\/\/www.virtono.com\/community\/knowledgebase\/fighting-mobile-data-security-hurdles\/","url_meta":{"origin":753,"position":3},"title":"Fighting Mobile Data Security Hurdles","author":"Daniel Draga","date":"November 18, 2016","format":false,"excerpt":"As mobile devices and applications continue to flood the business landscape, the security holes that these consumer devices pose put your entire enterprise network at risk. 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In this\u2026","rel":"","context":"In "Knowledgebase"","block_context":{"text":"Knowledgebase","link":"https:\/\/www.virtono.com\/community\/category\/knowledgebase\/"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/11\/mobile-security.jpg?fit=590%2C391&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/11\/mobile-security.jpg?fit=590%2C391&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/www.virtono.com\/community\/wp-content\/uploads\/2016\/11\/mobile-security.jpg?fit=590%2C391&ssl=1&resize=525%2C300 1.5x"},"classes":[]},{"id":93,"url":"https:\/\/www.virtono.com\/community\/knowledgebase\/business-intelligence-and-data-challenges\/","url_meta":{"origin":753,"position":4},"title":"Business Intelligence And Data Challenges","author":"Virtono","date":"July 18, 2016","format":false,"excerpt":"One growing demand in the business and analytics world is that of something called Business Intelligence (BI). 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