How to Effectively Realize Data Visualization

Transcription

1 How to Effectively Realize Data Visualization Gaining Insights from Your Data Faster than Ever and Sharing the Insights with Others CONCLUSIONS PAPER Insights from a Webinar in the Applying Business Analytics Webinar Series Featuring: Justin Choy, Global Product Management, Business Intelligence, SAS Jennifer Marchi, Global Product Marketing, Business Intelligence, SAS

2 SAS Conclusions Paper Table of Contents Quickly Visualize Big Data Analysis on the ipad and the Web... 1 Introducing SAS Visual Analytics The Six Components of SAS Visual Analytics... 3 Fast and Easy Visual Data Exploration Visually Explore the Data Create Your Own Hierarchies Choose the Best Visualization for the Data Refine the View... 6 Understand the Distribution of the Data... 6 Identify Relationships Among Variables Understand with Confidence What It Means Create Your Own Visual Reports and Dashboards... 8 Publish Information to the Web and Mobile Devices Closing Thoughts... 10

3 How to Effectively Realize Data Visualization Quickly Visualize Big Data Analysis on the ipad and the Web Organizations are inundated with data terabytes and petabytes of it. Data pours in from every conceivable direction: from operational and transactional systems, from scanning and facilities management systems, from inbound and outbound customer contact points, from mobile media and the Web. It is structured and unstructured; it is messy and overwhelming; it flows at greater speed than ever. The optimist s vision for this tidal wave of data is that organizations will be able to harvest and harness every relevant byte of it to make supremely informed decisions. However, traditional architectures and infrastructures are not up to the challenge. IT teams are burdened with ever-growing requests for data, ad hoc analyses and oneoff reports. Decision makers become frustrated because it takes hours or days to get answers to questions, if at all. More users are expecting self-service access to information in a form they can easily understand and share with others. Many challenges arise when working with this much data, said Justin Choy, Global Product Manager for Business Intelligence Solutions at SAS. Choy joined Jennifer Marchi of SAS Business Intelligence Product Marketing for a webinar in the SAS Applying Business Analytics Series. One problem is that it takes a long time to aggregate all that data. To get around this problem, IT has to create summaries of the data, or a cube with predefined hierarchies for better performance. Once you have a summary or a cube of the data, you can look at it more quickly, said Marchi. But what happens when you realize you need to look at the data in a different way than the summary or cube provides? You would typically have to turn to a data administrator or someone else in IT, and request another view of the data. In most organizations, accessing this new view will take some time, sometimes even a day, which, in turn, delays your analysis. Another problem is that some business questions are best answered by using all available and relevant data, which might be too much data to process within the decision window. Learn More View the on-demand recording of this webinar: sas.com/reg/web/corp/ Other events in the Applying Business Analytics Webinar Series: sas.com/abaws For more about SAS Visual Analytics: sas.com/visualanalytics To see a video demo of SAS Visual Analytics: youtube.com/ watch?v=1dum4ydnzza Related white papers: Big Data: Harnessing a Game-Changing Asset sas.com/reg/gen/corp/ In-Memory Analysis: Delivering Insights at the Speed of Thought sas.com/reg/wp/corp/41962 High-Performance Analytics Insights: Big Data, Bigger Opportunities sas.com/reg/gen/corp/hpa-insights Here is where high-performance computing and data visualization techniques come in. Data visualization is shaking up the world of analytics, changing the way you work with data, said Marchi. You ll find insights from your data faster than ever and be able to share those insights with others. 1

4 SAS Conclusions Paper Introducing SAS Visual Analytics SAS Visual Analytics is a high-performance, in-memory solution for exploring massive amounts of data very quickly, using SAS industry-leading analytics, said Marchi. It enables users to spot patterns, identify opportunities for further analysis and convey visual results via Web reports or an ipad. With SAS Visual Analytics, business users can explore data visually on their own, but it goes well beyond traditional query and reporting. Running on low-cost, industrystandard blade servers using Hadoop distributed processing, it delivers answers in seconds or minutes instead of hours or days. This kind of processing speed with massive data sets makes it possible to find important insights quickly insights that were not evident before. For example, marketing campaign optimizations that previously took eight to 10 hours or more can now run in less than three minutes. Bank risk calculations that once took 18 hours can now be completed in 15 minutes. Do you simply want to collect large amounts of data, or do you want to understand and take advantage of its full business value? What if you could easily access more than a billion rows of data, and then very quickly explore all of that data using visualization techniques combined with powerful analytics? You can. High-performance computing completely redefines what s possible. Analysts can use complete data sets instead of sample subsets. They can apply sophisticated analytic techniques, not just simple calculations, to generate descriptive and predictive insights from all that data. And they can put this power into the hands of a broad range of users through a dynamic, visual interface. Consider some possibilities. Retail marketing analysts are always looking for ways to optimize the offers and promotions they make to customers. When they can include more data from online sales and hundreds of stores plus demographic information, purchased market data, social media data and any other relevant data source they can determine next best offer recommendations with greater accuracy and certainty. They are not limited to a subset of customers; they can get on-target recommendations for entire populations, quickly and easily. Consider fraud detection models for banking and finance. With SAS Visual Analytics embedded in the analytics life cycle, analysts can look at more data more often and more quickly for new insights that lead to better models that can be quickly adapted to address new and emerging patterns of fraud. Retail, telecommunications and financial services are showing the greatest early interest in SAS Visual Analytics because of its ability to analyze large customer and prospect pools at an individual level while easily managing a collaborative analytics environment. In time, data visualization capabilities will be extended across the SAS software portfolio. SAS Visual Analytics combines an easy-to-use dynamic interface and in-memory processing to enable all types of users to visually explore big data, execute analytic correlations on billions of rows of data in minutes or seconds, understand what the data really means, and deliver the results quickly wherever needed via Web reports and mobile devices. 2

5 How to Effectively Realize Data Visualization The Six Components of SAS Visual Analytics SAS Visual Analytics includes the following components. The SAS LASR Analytic Server quickly reads data into memory for fast processing and data visualization, with direct communication to clients. SAS Visual Analytics Explorer is a discovery and visualization tool for ad hoc data exploration and analysis. SAS Visual Analytics Designer provides a graphical, drag-and-drop environment to create standard and custom reports and dashboards. SAS Visual Analytics Mobile is a tool for viewing reports by connecting to servers and downloading information on the go. SAS Visual Analytics Hub provides a central location to launch the various elements of SAS Visual Analytics. SAS Visual Analytics Environment Administration allows administrators to manage users, security and data. SAS Visual Analytics is tremendously powerful for its in-memory and massive parallel processing capabilities, but it is still cost-effective, said Choy. One of the ways we ve made it cost-effective is to use commodity hardware, taking advantage of Hadoop for data persistence on blade servers from HP and Dell, as well as dedicated data appliances from our partners Teradata and EMC Greenplum. The speed of in-memory architecture offers tremendous benefit. Organizations can explore huge data volumes and get answers to critical questions in near-real time. SAS Visual Analytics offers a double bonus: the speed of in-memory analytics plus self-service eliminates the traditional wait for IT-generated reports. Dan Vesset Program Vice President of Business Analytics Research, IDC SAS LASR Analytic Server has been tested on billions of rows of data and is extremely scalable, bypassing the known column limitations of many relational database management systems (RDBMS). This processing power is coupled with SAS Analytics, which differs from other solutions that simply move data from a SQL database into memory. Other solutions cannot support regressions or logistics models because such capabilities are not built into databases. 3

6 SAS Conclusions Paper Fast and Easy Visual Data Exploration One of the first things a data analyst wants to do when presented with a new set of data is to get some idea what it s about, said Jim Goodnight, CEO of SAS. What are the outliers? What variables are related to each other? Up until now, analysts would have to spend hours and hours doing samples so they could actually get jobs to run. With SAS Visual Analytics, you can cruise a billion records to create graphs and plots one after the other. It really allows you to understand your data better before you go into the high-performance analytics. Marchi and Choy demonstrated how SAS Visual Analytics Explorer can conceptualize, visualize and investigate the data in different ways to find the best answer a particular business question. To see SAS Visual Analytics in action, check out the four-minute demo at youtube.com/watch?v=1dum4ydnzza. Visually Explore the Data Users can explore all data, execute analytic correlations on billions of rows of data in seconds, and visually present results to the Web and mobile devices. This kind of processing speed with massive data sets makes it possible to quickly identify patterns, trends and relationships in data that were not evident before. By dragging and dropping hierarchies or categories onto the visualization pane, I can quickly and easily see how my revenue expenses are doing by region, said Choy, demonstrating the system. I can hover over the bubbles and see that my West region is doing better than other regions. I can double-click on the bubble and go into that region for more detail. It s as simple as that, and all of the data being presented to me is based on a billion rows of geographic, product and financial information for this manufacturing company. Figure 1: The interface uses intuitive, drag-and-drop actions and visualizations. 4

7 How to Effectively Realize Data Visualization Create Your Own Hierarchies If you need the data organized a certain way for the business problem at hand, you don t have to go to your company s data specialists to request a new view of the data. With SAS Visual Analytics, you have access to all of the data, and based on all of the data, you can create and modify your own hierarchies to explore the data, however and whenever you want, without having to rely on someone else, said Choy. It is so easy to do. I can create a new visualization and then go into the Create a New Hierarchy area, and then just double-click or drag and drop [from a menu selection box] the items on which I want to build a hierarchy. Once I m satisfied with that, I can give it a name or just hit OK. It s that easy. Choy demonstrated how the new hierarchy appears in the visualization. Double-click on a bar in a bar chart or on a slice of a pie chart, for instance, and you can drill down to a different level or go back up a level. All of these views are changing within seconds, yet drawing on a billion rows of data behind the scenes. Build-it-yourself hierarchies eliminate the need for data analysts to constantly seek help from IT. It is easy to drill up and down through the hierarchies to slice and dice data on any level. Choose the Best Visualization for the Data When you re working with a billion rows of data, it is really difficult to quickly understand what s happening in the data simply by looking at rows and columns, said Marchi. Even guessing what type of chart to use can be challenging. SAS Visual Analytics simplifies all that by using intelligent autocharting to recommend an appropriate type of visual for the information you re trying to view. It could be a line or bar chart, a scatter plot or box plot, heat maps or bubble charts anything from the portfolio of available visualizations. In the example shown in the demo, SAS Visual Analytics recognized that the data had geographic elements revenue and expenses by geographic regions and offered the data as a bubble plot superimposed on a map of the regions. In another example, Choy showed how SAS Visual Analytics chose a line chart as the best visual for a selection of two variables, then changed to a clustered bar chart when a third variable was added. Of course, users can always select the desired of visual anything acceptable to the measures and categories chosen. Autocharting capabilities help users create the best possible visualizations, including those specifically designed to display big data. And remember, this speed-of-sight display is being calculated with 1.1 billion rows and 47 columns of data. 5

8 SAS Conclusions Paper Refine the View What if you only want to view data for a certain region, product line or some other variable? SAS Visual Analytics has filtering capabilities that make it easy to refine the information you re viewing, said Marchi. Simply add a measure to the filter pane or select one that s already there, and then select or deselect the items on which to filter. What if the filter isn t meaningful, or it skews the data in undesirable ways? A histogram on the right of the screen provides a visual cue about the distribution of the data, showing how the data is affected by filtering a particular measure, said Marchi, who used expenses as an example. The histogram shows that the majority of the data is on the left, so if I filter from the right, it will have a minimal impact on the information I m viewing in the visualization pane. However, if I filter from the left, it will have a more significant effect on what I m viewing, because the majority of the data is distributed in this area. Histograms allow you to save time by giving you an idea what effect the filter will have on the data before you apply it. Rather than relying on trial and error or gut feel, you can use the histogram to help you decide what areas to focus on. Understand the Distribution of the Data Understanding the distribution of the data is now as simple as creating a new visual and dragging the measure or category onto the visualization pane. By default, the system automatically calculates the best distribution for the data, but the user can go under the Properties tab and change that, said Choy. A histogram shows how the data is distributed, but a better visual for this purpose is a box plot [which graphically depicts numerical data through summary calculations such as minimum, maximum, upper and lower quartile, and median]. I can create a new box plot by creating a new visualization, selecting that visual, and then dragging and dropping the visual on here. You can hover over the box plot and not only see the distribution of the data, but also where the important 50 percent of your data is, as well as some basic statistics about the data, such as average, median, standard deviation, minimum and maximum, average standard deviation, whisker and quartiles information, and count. I can even add a new measure onto here, and we can do a comparison over two different measures in the box plot. I can then add another category in here, such as product line, for example, and now instead of doing 10 calculations on the fly, we re actually doing 40 calculations over a billion rows. And we re getting the results extremely fast, especially considering that the median, the middle value of the data, requires scanning all 1.1 billion rows of data. 6

9 How to Effectively Realize Data Visualization Figure 2: Interactive box plots help users quickly understand the distribution of the data. Identify Relationships Among Variables SAS Visual Analytics makes it easy to assess relationships among variables. Just select a group of variables and drop them into the visualization pane; the intelligent autocharting function displays a color-coded correlation matrix that quickly identifies strong and weak relationships between the variables. Darker colored boxes indicate a stronger correlation, lighter boxes a weaker correlation. Hover over a box to see a summary of the relationship. Double-click on a box in the matrix for further detail. Previously, this type of calculation would have taken many hours, but now it can be done in seconds, said Choy. Think about it; we ve generated a 10 by 9 correlation matrix, executing 45 correlation calculations on over a billion rows of data, and the results were displayed in seconds. By using box plots and correlation matrices, SAS Visual Analytics can help speed up your analytics life cycle because analytical modelers can now do variable reduction more quickly and effectively. By using box plots and correlation matrices, SAS Visual Analytics can help speed up your analytics life cycle because analytical modelers can now do variable reduction more quickly and effectively. Justin Choy Global Product Management, Business Intelligence, SAS Understand with Confidence What It Means Do your business users need help understanding what all this data exploration is telling them? No problem. For business users or analysts who are not familiar with terms such as regression or correlation, help is available, said Marchi. We ve added a What Does It Mean feature to explain some of the terminology and help users understand what they re seeing. Click on the information icon, and a pop-up dialog box explains what the analysis has shown: for instance, that there is a correlation of -0.94, which suggests there s a strong linear relationship between two variables. 7

10 SAS Conclusions Paper Create Your Own Visual Reports and Dashboards Once you ve had a chance to visualize and explore your data, you ll likely see something that you want to share with someone else. Or you might want to generate a report based on the data you have been exploring. The SAS Visual Analytics Designer provides the tools to create and distribute Web-based reports. Through a graphical interface, report authors can get wizard-driven help for previewing, filtering or sampling data before creating visualizations and reports. A variety of formats are available: standard and three-dimensional bar charts with multiple lines, standard and three-dimensional pie charts, scatter plots, heat maps, bubble charts, and tile charts all with the option for annotated reference lines. On-demand What Does It Mean balloons give business users clear explanations of complex analytic functions, correlations and linear regressions in a language that they can understand. The reports are dynamic and interactive, as Choy demonstrated. I ve just opened a report with three sections, looking at gross margin for product lines and categories over a range of years. I can click on 2011 to zero in on that year. Click a bar in the yearly gross margin chart to filter product line and product category gross margin the other two segments of the screen display. I can select various product categories to filter on and get different information or select a geography from the global filter. Choy s sample report had multiple tabs, each with unique sets of visualizations, all of them clickable to explore up or down a level in the hierarchy. With drag-and-drop simplicity, report authors can define the interactions among visuals in a report, specify the type and appearance of the report page, and add labels and annotation. Figure 3: Business users can create their own reports and dashboards using a highly visual workspace. 8

11 How to Effectively Realize Data Visualization Publish Information to the Web and Mobile Devices Decision makers get the insights they need, when they need them, even when they re on the go. Reports are easily read via the Web or on an ipad using the SAS Mobile BI app, a free ios app available from the itunes App Store SM. Native ipad support uses the most popular gestures and capabilities, such as zoom, swipe, drag and drop, and resizing objects on screen. Other mobile devices will be supported in the future. Executives or any mobile user can easily benefit from the interactive report viewing capabilities, said Marchi, demonstrating on her ipad the reports created earlier in the demo. It is highly visual and very self-service for the user and very simple. Just open the SAS Mobile BI app to see your portfolio of reports. Click on the library and navigate to a shared folder to look at reports and download new ones. Click Subscribe to download a report. The display shows thumbnails of the reports you subscribe to, which can be viewed at any time, even when offline. The reports offer the same interactions between charts as Choy demonstrated in the Designer toolbox. Reports can also be saved to PDF or PNG formats for printing. SAS strongest play with SAS Visual Analytics is to supercharge its predictive analytics capabilities. The time shift from hours to minutes promises to enable customers to do more analysis with more data and greater accuracy than ever before. Doug Henschen InformationWeek (SAS Introduces Big Data Visual Analytics Platform, March 23, 2012) Figure 4: Get a quick, easy visual understanding of customers or operations on your mobile device. 9

12 SAS Conclusions Paper Closing Thoughts Even the most common descriptive statistics calculations can become complicated when you are dealing with big data. You don t want to be restricted by column limits, storage constraints and the limited data type support of traditional data architectures. The answer is an in-memory engine that accelerates the tasks of data exploration and a graphical interface that displays the results in simple visualizations. Dealing with billions of records on a regular basis is just a reality of doing business today, and SAS understands that, said Marchi. SAS Visual Analytics allows you to explore all of your data using visual techniques combined with industry-leading analytics. Visualizations such as box plots and correlation matrices help you quickly understand the composition and relationships in your data. Large numbers of users, including those with limited analytical and technical skills, can quickly view and interact with reports via the Web or mobile devices, while IT maintains control of the underlying data and security. The net effect is the ability to accelerate the analytics life cycle and to perform the process more often, with more data all the data, if that s what best serves the purpose. By using all data that is available, users can look at more options, make more precise decisions and succeed even faster than before. With SAS Visual Analytics, you can explore your data, discover new insights, generate reports and deliver the information to the people who need it, all from a single solution. Whatever your industry retail, insurance, health care and life sciences, or financial services SAS Visual Analytics can help. Justin Choy Global Product Management, Business Intelligence, SAS Stay Informed Follow us on Like us on Facebook: SAS Analytics To get fresh perspectives on customer analytics from marketing practitioners writing on the SAS Customer Analytics blog: blogs.sas.com/content/ customeranalytics 10

13 About SAS SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions, SAS helps customers at more than 60,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world THE POWER TO KNOW. For more information on SAS Business Analytics software and services, visit sas.com. SAS Institute Inc. World Headquarters To contact your local SAS office, please visit: sas.com/offices SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. indicates USA registration. Other brand and product names are trademarks of their respective companies. Copyright 2012, SAS Institute Inc. All rights reserved _S87282_0812