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You may be wondering if you need something special to gain access to the Schedule Chart object. Don’t worry, you don’t, you just need to unhide this visualization if it isn’t already. You can do this from the Objects’ drop down menu. There are several other objects available to you if you’d like to show those as well. Simply check the ones you want to include in the list and then click ok.
The VA 7.3 Schedule Chart is similar to the traditional Gantt chart in that it serves to illustrate the start and finish duration of a category data item. You must provide a category data item and two date or datetime data items representing the start and end dates. You can also add a group by category, lattice by columns and/or rows. Here is a simple example that visualizes my local school district’s 2016-2017 Traditional School Calendar.
Schedule charts can be used to visualize a variety of data such as:
- Calendar Events
- Project Tracking
- Campaign/Promotional Runs
- Floor Service Coverage
Essentially, any category which can be associated with a start and end date can use this visualization.
Here are some examples of using the Schedule Chart to look at project tracking data. Our team uses a similar visualization; however, I have modified real names and gave it a Star Wars theme for a bit of fun.
In this example, the Project name is assigned as the main category. Here are a few takeaways:
- The schedule chart gives a great bird’s eye view of a lot of data. This particular data has over 350 projects spanning a team of 19 individual members.
- The schedule chart automatically includes the least and greatest date value. You can override the X Axis in the Properties tab by assigning a fixed minimum and maximum.
In this next screenshot, I have selected the manager Obi-Wan Kenobi to filter the Schedule Chart. Therefore, by adding section filters to this report, you can see how spotting coverage of Projects and Project Types are easy. And, with some Mock Combat planned later in the year, the Jedis might want to up their training.
This example uses the same Schedule Chart role assignments as before, but different section prompt filters. Here, this report shows how an individual team member can use the Schedule Chart to visualize several things:
- A list of his/her assigned projects.
- The planned duration of each project.
- How the projects are spread throughout the year.
If you chose to look at a particular Project Type, then this visualization would help list the Project names and how they span across the year.
The next example moves away from the traditional use of putting the Project as the main category data item and instead places the Team Lead on the Y Axis. This now allows us to see how busy each Team member is and with which Project Type. By the way, did you notice the neat way the Team names are sorted? I used a custom sort!
Here are just a few more things you can do to enhance this visualization: you can adjust the transparency so you can see overlapping projects and you can easily add reference lines to the X Axis. In this example, I’ve added the reference lines for Q1 through Q4. I’ve also selected a manager from the report section filters and added an additional data item for the Label.
In this example, I wanted to demonstrate the use of the Lattice rows and I also applied a Display Rule for the Project Type. This is a good way if you want to view overlapping information and the transparency property isn’t distinct enough.
Schedule Chart Limitations
If you want a bar representation on the Schedule Chart to appear then the data must have a start and end date for every row of data. If either is missing, then the category name will appear on the Y Axis but no bar will be displayed on the visualization. Also, you cannot create an interaction from or to the Schedule Chart object. That means you cannot create a filter or brush with another object in the report area. The Schedule Chart will be filtered by either report or section prompts. I hope you can include the Schedule Chart into your reports, it is one of my favorite visuals.
You can expand on the functionality of SAS Visual Data Builder in SAS Visual Analytics by editing the query code, adding code for pre- and post-processing, or even writing your own query. You can process single tables or join multiple tables, writing the output to a LASR library, a SAS library, or a DBMS library. But you can also easily schedule your queries, right from the Visual Data Builder interface.
When a query is open in the workspace of Visual Data Builder, you can schedule the query from the application by clicking the Schedule (clock) icon.
The scheduling server used is determined by the SAS Visual Data Builder Scheduling preferences setting, shown below.
By default, the Visual Analytics deployment includes the Operating System Services scheduling server, so it appears automatically as the default.
The Server Manager plug-in to SAS Management Console identifies the scheduling servers that are included in your deployment. You can specify a different scheduling server, such as Platform Suite for SAS server, if your deployment includes it.
Note: The Distributed In-process scheduling server is not supported.
Any scheduling preferences that you change are used the next time you create and schedule a query. If you need to change the settings for a query that is already scheduled, you can use SAS Management Console Schedule Manager to redeploy the deployed job for the query.
When you schedule a query, the SAS statements are saved in a file in the default deployment directory path: SAS-config-dir/Lev1/SASApp/SASEnvironment/SASCode/Jobs.
In the examples in this blog, the SAS-config-dir is /opt/sasinside/vaconfig.
The metadata name of the directory is Batch Jobs.
The default SAS Application Server name associated with the directory is SASApp.
If you are working in a VA environment where multiple application servers are defined, you should be aware of the following SAS Notes at the links below, relating to the application’s choice of application servers for scheduling.
SAS Note 58186: SAS® Visual Data Builder might use the wrong application server for scheduling
SAS Note 52977: SAS® Visual Data Builder requires the default SAS® Application Server and the default scheduling servers to be located on the same physical machine
To schedule a query, open the query and select the Schedule (clock) icon. (The clock is grayed out if you have not saved the query.)
You can schedule the query to run immediately (Run now) or at a specified time event. To define a time event, select the Select one or more triggers for this query button and click New Time Event. Grouping events are not supported for the default server, but may be supported for other scheduling servers, such as Platform Suite.
You can schedule for One time only, or More than once, running Hourly, Daily, Weekly, Monthly, or Yearly. The appearance of the interface and scheduling parameters change with your specification.
In this example, a One time only event is specified.
The time event specification gets recorded in the Trigger list on the Schedule page, and is selected in the Used column.
After you click OK in the Schedule window, you will get the confirmation below.
After the time event has passed, you can verify that the table has been loaded on the LASR Tables tab of the Visual Analytics Administrator.
When you schedule, the Visual Data Builder:
- creates a job that executes the query.
- creates a deployed job from the job.
- places the job into a new deployed flow.
- schedules the flow on a scheduling server.
The files are named according to vdb_query_id_timestamp.
In this example the files are named vdb_CustomerInfoData_1490112883364_timestamp.
When the query executes at the scheduled time, the SAS code that is written to the /opt/sasinside/vaconfig/Lev1/SASApp/SASEnvironment/SASCode/Jobs directory. The query is run with the user ID that scheduled it.
If you right-click on Server Manager in SAS Management Console and view Deployment Directories, you will see that this is the Deployment directory (Batch Jobs) for SASApp.
In the /opt/sasinside/vaconfig/Lev1/SASApp/BatchServer/Logs directory, you can view the SAS Log.
The scheduling server script and log are in /opt/sasinside/vaconfig/Lev1/SchedulingServer/Ahmed/vdb_CustomerInfoData_14900112883364
Observe that the script was written to this location at the time the job was scheduled, rather than at execution time.
If you edit a data query that is already scheduled, you must click the schedule icon again so that the SAS statements for the data query are regenerated and saved.
If you edit the query again and specify additional time events, each event appears in the trigger list, and you can check which time event is to be used for scheduling.
If scheduling a query according to time events, you should also be aware of this Usage note:
And to add to the fun, also keep in mind that if your deployment includes SAS Data Integration Studio, you can also export a query as a Job and then perform the deployment steps using DI Studio.
Just right-click on the query in the SAS folder panel in Visual Data Builder and Select Export as a Job!
Easy Scheduling in Visual Data Builder - SAS Visual Analytics 7.3 was published on SAS Users.
Earth is an explosive world! Data from the Smithsonian Institution's Global Volcanism Program (GVP) documents Earth's volcanoes and their eruptive history over the past 10,000 years. The GVP database includes the names, locations, types, and features of more than 1,500 volcanoes. Let's look closer into volcanic eruptions across the globe [...]
When senior leaders at the University of Louisville (UofL) approached Vice Provost Bob Goldstein in early April 2016 with a request for a fully functioning data visualization platform by start of the 2016 fall semester—just four months away—he did not panic. Instead, Goldstein, along with Becky Patterson, Executive Director of [...]
Several months ago, I posted a blog about calculating moving averages for a measure in the Visual Analytics Designer. Soon after that, I was asked about calculating not only the average, but also the standard deviation over a period of months, when the data might consist of one or more repeated values of a measure for each month of a series of N months. For the example of N=20 months, we might want to view the average and standard deviation over the last n months, where n is any number between 3 and 20.
The example report shown below allows the user to type in a number, n, between 3 and 20, to display a report consisting of the amount values for past n months, the amount values for Current Month Amt-Previous, the Avg over the last n months, the Standard Deviation over the last n months, and the absolute value of the (Current Month Amt – Previous Month Amt), divided by the Standard Deviation over the last n months. A Display rule is applied to the final Abs column, showing Green for a value less than 1 and red for a value greater than or equal to 1.
The data used in this example had multiple Amount values for each month, so we first used the Visual Data Builder to create a SUM aggregation for Amount for each unique Date value. This step gives more flexibility in using the amount value for aggregations in the designer.
When the modified data source is initially added to the report, it contains only the Category data item Month, with a format of MMYYYY, and the measure Amount Sum for Month.
The data will be displayed in a list table. The first columns added to the table will be Month, displayed with a MMYYYY format, and Amount Sum for Month.
Specify the properties for the list table as below:
Since we want to display the last n months, we create a new calculated data item, Numeric Date, calculated as below, using the TREATAS operator on the Month data item:
Then we create the Current Month Amt-Previous aggregated measure using the RelativePeriod date operator:
Next, create the Avg over all displayed months aggregated measure as below:
Then, create the Std.Dev. over all displayed months aggregated measure as shown below:
Create the Abs (Current-Previous/StdDev) as shown below:
Create a numeric parameter, Number of Months, as shown, with minimum value of 3 (smallest value that a standard deviation will make sense) and maximum value of 20 (the number of months in our data). You can let the default (Current value) value be any value that you choose:
For the List Table, create a Rank, as shown below. Note that we are creating the rank on the Numeric Date (not the Month data item), and rather than a specific value for count, we are going to use the value of the parameter, Number of Months.
Create a text input object that enables the user to type in a ‘number of months’ between 3 and 20.
Associate the Parameter with the Text input object:
If you wish, you can add display rules to sound an alarm whenever there is an alarming month-to-month difference in comparison to the standard deviation for the n months.
So the final result of all of the above is this report, which points out month-to-month differences, which might deserve further concern or investigation. Note that the Numeric Date value is included below just to enable you to see what those values look like—you likely would not want to include that calculated data item in your report.
As a practitioner of visual analytics, I read the featured blog of ‘Visualizations: Comparing Tableau, SPSS, R, Excel, Matlab, JS, Python, SAS’ last year with great interest. In the post, the blogger Tim Matteson asked the readers to guess which software was used to create his 18 graphs. My buddy, Emily Gao, suggested that I should see how SAS VA does recreating these visualizations. I agreed.
SAS Visual Analytics (VA) is better known for its interactive visual analysis, and it’s also able to create nice visualizations. Users can easily create professional charts and visualizations without SAS coding. So what I am trying to do in this post, is to load the corresponding data to SAS VA environment, and use VA Explorer and Designer to mimic Matteson’s visualizations.
I want to specially thank Robert Allison for his valuable advices during the process of writing this post. Robert Allison is a SAS graph expert, and I learned a lot from his posts. I read his blog on creating 18 amazing graphs using purely SAS code, and I copied most data from his blog when doing these visualization, which saved me a lot time preparing data.
So, here’s my attempt at recreating Matteson’s 18 visualization using SAS Visual Analytics.
This visualization is created by using two customized bar charts in VA, and putting them together using precision layout so it looks like one chart. The customization of bar charts can be done by using the ‘Custom Graph Builder’ in SAS VA, which includes: set the reverse order for X axis, set the axes direction to horizontal, and don’t show axis label for X axis and Y axis, uncheck the ‘show tick marks’, etc. Comparing with Matteson’s visualization, my version has the tick values on X axis displayed as non-negative numbers, as people generally would expect positive value for the frequency.
Another thing is, I used the custom sort for the category to define the order of the items in the bar chart. This can be done by right click on the category and select ‘Edit Custom Sort…’ to get the desired order. You may also have noticed that the legend is a bit strange for the Neutral response, since it is split into Neutral_1stHalf and Neutral_2ndHalf, which I need to gracefully show the data symmetrically in the visualization in VA.
VA can create a grouped bar chart with desired sort order for the countries and the questions easily. However, we can only put the questions texts horizontally atop of each group bar in VA. VA uses vertical section bar instead, with its tooltip to show the whole question text when the mouse is hovered onto it. And we can see the value of each section in bar interactively in VA when hovering the mouse over.
Matteson’s chart looks a bit scattered to me, while Robert’s chart is great at label text and markers for the scatterplot matrix. Here I use VA Explorer to create the scatterplot matrix for the data, which omitted the diagonal cells and its diagonal symmetrical part for easier data analysis purpose. It can then be exported to report, and change the color of data points.
I used the ‘Numeric Series Plot’ to draw this chart of job losses in recession. It was straightforward. I just adjust some setting like checking the ‘Show markers’ in the Properties tab, unchecking the ‘Show label’ in X Axis and unchecking the ‘Use filled markers’, etc. To make refinement of X axis label of different fonts, I need to use the ‘Precision’ layout instead of the default ‘Tile’ layout. Then drag the ‘Text’ object to contain the wanted X axis label.
VA can easily draw the grouped bar charts automatically. Disable the X axis label, and set the grey color for the ‘Header background.’ What we need to do here, is to add some display rules for the mapping of color-value. For the formatted text at the bottom, use the ‘Text’ object. (Note: VA puts the Age_range values at the bottom of the chart.)
SAS VA does not support drawn 3D charts, so I could not make similar chart as Robert did with SAS codes. What I do for this visualization, is to create a network diagram using the Karate club dataset. The grouped detected communities (0, 1, 2, 3) are showing with different colors. The diagram can be exported as image in VAE.
***I use the following codes to generate the necessary data for the visualization:
/* Dataset of Zachary’s Karate Club data is from: http://support.sas.com/documentation/cdl/en/procgralg/68145/HTML/default/viewer.htm#procgralg_optgraph_examples07.htm This dataset describes social network friendships in karate club at a U.S. university. */ data LinkSetIn; input from to weight @@; datalines; 0 9 1 0 10 1 0 14 1 0 15 1 0 16 1 0 19 1 0 20 1 0 21 1 0 23 1 0 24 1 0 27 1 0 28 1 0 29 1 0 30 1 0 31 1 0 32 1 0 33 1 2 1 1 3 1 1 3 2 1 4 1 1 4 2 1 4 3 1 5 1 1 6 1 1 7 1 1 7 5 1 7 6 1 8 1 1 8 2 1 8 3 1 8 4 1 9 1 1 9 3 1 10 3 1 11 1 1 11 5 1 11 6 1 12 1 1 13 1 1 13 4 1 14 1 1 14 2 1 14 3 1 14 4 1 17 6 1 17 7 1 18 1 1 18 2 1 20 1 1 20 2 1 22 1 1 22 2 1 26 24 1 26 25 1 28 3 1 28 24 1 28 25 1 29 3 1 30 24 1 30 27 1 31 2 1 31 9 1 32 1 1 32 25 1 32 26 1 32 29 1 33 3 1 33 9 1 33 15 1 33 16 1 33 19 1 33 21 1 33 23 1 33 24 1 33 30 1 33 31 1 33 32 1 ; run; /* Perform the community detection using resolution levels (1, 0.5) on the Karate Club data. */ proc optgraph data_links = LinkSetIn out_nodes = NodeSetOut graph_internal_format = thin; community resolution_list = 1.0 0.5 out_level = CommLevelOut out_community = CommOut out_overlap = CommOverlapOut out_comm_links = CommLinksOut; run; /* Create the dataset of detected community (0, 1, 2, 3) for resolution level equals 1.0 */ proc sql; create table mylib.newlink as select a.from, a.to, b.community_1, c.nodes from LinkSetIn a, NodeSetOut b, CommOut c where a.from=b.node and b.community_1=c.community and c.resolution=1 ; quit;
I created this map using the ‘Geo Coordinate Map’ in VA. I need to create a geography variable by right clicking on the ‘World-cities’ and selecting Geography->Custom…->, and set the Latitude to the ‘Unprojected degrees latitude,’ and Longitude to the ‘Unprojected degrees longitude.’ To get the black continents in the map, go to VA preferences, check the ‘Invert application colors’ under the Theme. Remember to set the ‘Marker size’ to 1, and change the first color of markers to black so that it will show in white when application color is inverted.
This is a very simple scatter chart in VA. I only set transparency in order to show the overlapping value. The blue text in left-upper corner is using a text object.
To get this black background graph, set the ‘Wall background’ color to black. Then change the ‘Line/Marker’ color in data colors section accordingly. I’ve also checked the ‘Show markers’ option and changed the marker size to bigger 6.
There is nothing special for creating this scatter plot in VA. I simply create several reference lines, and uncheck the ‘Use filled markers’ with smaller marker size. The transparency of the markers is set to 30%.
In VA’s current release, if we use a category variable for color, the marker will automatically change to different markers for different colors. So I create a customized scatterplot using VA Custom Graph Builder, to define the marker as always round. Nothing else, just set the transparency to clearly show the overlapping values. As always, we can add an image object in VA with precision layout.
I used the GEO Bubble Map to create this visualization. I needed to create a custom Geography variable from the trap variable using ‘lat_deg’ and ‘lon_deg’ as latitude and longitude respectively. Then rename the NumMosquitos measure to ‘Total Mosquitos’ and use it for bubble size. To show the presence of west nile virus, I use the display rule in VA. I also create an image to show the meaning of the colored icons for display rule. The precision layout is enabled in order to have text and images added for this visualization.
This visualization is also created with GEO bubble map in VA. First I did some data manipulation to make the magnitude squared just for the sake of the bubble size resolution, so it shows contrast in size. Then I create some display rules to show the significance of the earth quakes with different colors, and set the transparency of the bubble to 30% for clarity. I also created an image to show the meaning of the colored icons.
Be aware that some data manipulation is needed for original longitude data. Since the geographic coordinates will use the meridian as reference, if we want to show the data of American in the right part, we need to add 360 to the longitude, whose value is negative.
My understanding that one of the key points of this visualization Matteson made, is to show the control/interaction feature. Great thing is, VA has various control objects for interactive analysis. For the upper part in this visualization, I simply put a list table object. The trick here is how to use display rule to mimic the style. Before assigning any data to the list table in VA, I create a display rule with Expression, and at this moment we can specify the column with any measure value in an expression. (Otherwise, you need to define the display rule for each column with some expressions.) Just define ‘Any measure value’ is missing or greater than a value with proper filled color for cell. (VA doesn’t support filling the cell with certain pattern like Robert did for missing value. Therefore, I use grey for missing value to differentiate from 0 with a light color.)
For the lower part, I create a new dataset for interventions to hold the intervention items, and put it in the list control and a list table. The right horizontal bar chart is a target bar chart with the expected duration as the targeted value. The label on each bar shows the actual duration.
VA does not have solid-modeling animation like Matteson made in his original chart, yet VA has animation support for bubble plots in an interactive mode. So I made this visualization using Robert’s animation dataset, trying to make an imitation of the famous animation by the late Hans Rosling as a memorial. I set the dates for animation by creating the dates variable with the first day in each year (just for simplicity). One customization here is: I use the custom graph builder to add a new role so that it can display the data label in the bubble plot, and set the country name as the bubble label in VA Designer. Certainly, we can always filter the interested countries in VA for further analysis.
VA can’t show only a part of the bubble labels as Robert did using SAS codes. So in order to clearly show the labels of those interested countries, I made a rank of top 20 countries of average populations, and set a filter to show data between year 1950 to 2011. I use a capture screen tool to have the animation saved as a .gif file. Be sure to click the chart to see the animation.
I think Matteson’s original chart is to show the overview axis in the line chart, since I don’t see specialty of the line chart otherwise. So I draw this time series plot with the overview axis enabled in VA using the SASHELP.STOCK dataset. It shows the date on X axis with tick marks splitting to months, which can be zoomed in to day level in VA interactively. The overview axis can do the zooming in and out, as well as movement of the focused period.
For this visualization, I use a customized bubble plot (in Custom Graph Builder, add a Data Label Role for Bubble Plot.) so it will have bubble labels displayed. I use one reference line with label of Gross Avg., and 2 reference lines for X and Y axis accordingly, thus it visually creats four quadrants. As usual, add 4 text objects to hold the labels at each corner in the precision layout.
I think Matteson made an impressive 3D chart, and Robert recreated a very beautiful 3D chart with pure SAS codes. But VA does not have any 3D charts. So for this visualization, I simply load the data in VA, and drag them to have a visualization in VAE. Then choose the best fit from the fit line list, and export the visualization to report. Then, add display rules according to the value of Yield. Since VA shows the display rules at information panel, I create an image for colored markers to show them as legend in the visualization and put it in the precision layout.
There you have it. Matteson’s 18 visualizations recreated in VA.
How did I do?
In this post I wanted to shed some light on a visualization you may not be using enough: the Word Cloud. Word association exercises can often be a fun way to pass the time with friends, or it can trigger immediate action – just think of your email inbox and seeing an email from a particular person: your boss, wife, husband or child. The same can be true for information for your organization. A single word can quickly, efficiently and effectively communicate the performance of a company’s metric, hence the value of using a word cloud visualization in your report.
Let’s look at some examples. Here I am using the Insight Toy data and looking at the performance of Products based on customer orders.
As the word cloud in SAS Visual Analytics 7.3 Designer has a maximum row return of 100, I have used the Rank feature to look at the top 25 Products and the bottom 25 Products. I also created a filtered interaction between the word clouds and their respective list tables below to show a bit more detail around the next level in the hierarchy after Product Make.
Notice how impactful these Product names are compared to when using their corresponding SKUs. Be sure to pick a meaningful category to represent your data in the word cloud.
This type of visualization could lead to a great comparison report, comparing what the top and bottom Products were for the same month in the previous year.
What if your data doesn’t have the appropriate column to display on a word cloud? No problem. In this next example, I took the value of Sales Rep Rating and created a new Calculated Data Item to represent values less than or equal to 25% to be Poor, inclusively between 26% and 50% to be Average and everything else to be Above Average.
Using a word cloud for this new category data item allows you to quickly move through the different states and compare the Sales Rep Performance frequency. You could also use this new category to compare each performance group’s Order Totals.
Here is California’s Sales Rep Performance:
And here is Maryland’s Sales Rep Performance:
These are two ideas for you to think about how you might include the word cloud visualization into your reports to help quickly and effectively represent the status of a company’s metric beyond the standard text analytics usage.
Visualization Spotlight: Visual Analytics Designer 7.3 Word Cloud was published on SAS Users.
SAS® Viya™ 3.1 represents the third generation of high performance computing from SAS. Our journey started a long time ago and, along the way, we have introduced a number of high performance technologies into the SAS software platform:
- In-Database processing where SAS data quality and analytical processing occur within the data source, minimizing data movement and leveraging the native language of the data source.
- Grid computing to distribute processing over a number of computing nodes in a cluster.
- High Performance Analytics where in-memory calculations are processed across the nodes of a cluster including High Performance Risk and High Performance Data Mining.
- In-memory Visual Analytics and Visual Statistics powered by the SAS LASR analytic server.
Introducing Cloud Analytic Services (CAS)
SAS Viya introduces Cloud Analytic Services (CAS) and continues this story of high performance computing. CAS is the runtime engine and microservices environment for data management and analytics in SAS Viya and introduces some new and interesting innovations for customers. CAS is an in-memory technology and is designed for scale and speed. Whilst it can be set up on a single machine, it is more commonly deployed across a number of nodes in a cluster of computers for massively parallel processing (MPP). The parallelism is further increased when we consider using all the cores within each node of the cluster for multi-threaded, analytic workload execution. In a MPP environment, just because there are a number of nodes, it doesn’t mean that using all of them is always the most efficient for analytic processing. CAS maintains node-to-node communication in the cluster and uses an internal algorithm to determine the optimal distribution and number of nodes to run a given process.
However, processing in-memory can be expensive, so what happens if your data doesn’t fit into memory? Well CAS, has that covered. CAS will automatically spill data to disk in such a way that only the data that are required for processing are loaded into the memory of the system. The rest of the data are memory-mapped to the filesystem in an efficient way for loading into memory when required. This way of working means that CAS can handle data that are larger than the available memory that has been assigned.
The CAS in-memory engine is made up of a number of components - namely the CAS controller and, in an MPP distributed environment, CAS worker nodes. Depending on your deployment architecture and data sources, data can be read into CAS either in serial or parallel.
What about resilience to data loss if a node in an MPP cluster becomes unavailable? Well CAS has that covered too. CAS maintains a replicate of the data within the environment. The number of replicates can be configured but the default is to maintain one extra copy of the data within the environment. This is done efficiently by having the replicate data blocks cached to disk as opposed to consuming resident memory.
One of the most interesting developments with the introduction of CAS is the way that an end user can interact with SAS Viya. CAS actions are a new programming construct and with CAS, if you are a Python, Java, SAS or Lua developer you can communicate with CAS using an interactive computing environment such as a Jupyter Notebook. One of the benefits of this is that a Python developer, for example, can utilize SAS analytics on a high performance, in-memory distributed architecture, all from their Python programming interface. In addition, we have introduced open REST APIs which means you can call native CAS actions and submit code to the CAS server directly from a Web application or other programs written in any language that supports REST.
Whilst CAS represents the most recent step in our high performance journey, SAS Viya does not replace SAS 9. These two platforms can co-exist, even on the same hardware, and indeed can communicate with one another to leverage the full range of technology and innovations from SAS. To find out more about CAS, take a look at the early preview trial. Or, if you would like to explore the capabilities of SAS Viya with respect to your current environment and business objectives speak to your local SAS representative about arranging a ‘Path to SAS Viya workshop’ with SAS.
If your SAS Visual Analytics report requirements include linking out to separate reports without the need to pass values, you may want to consider using images to enhance the appearance of your base report. Here are three style examples using images that you can use depending on your report design requirements and report user preference:
1. Visually appealing
3. Screenshot of actual report.
There is no better substitute for looking at examples so here are some screenshots for you:
1. Visually appealing
3. Screenshot of actual report
Using an image in your report has never been easier. You can navigate your local machine for the image and, if you want, you can also save the image in metadata. This allows other users with access to that metadata location the ability to use the same image. This is great when you want to impose consistency throughout your reports.
Setting link using image
To define a report link from your image, click on your image then open the Interactions tab. Then use the New drop-down menu and select the type of link you wish to define. For a Report Link or Section Link, use the Browse button to navigate the metadata and select your target. If you are linking to an External URL then enter the fully qualified URL or you can define a link to a stored process.
Here is a breakdown of the report objects used in the main dashboard report. I also included the screenshots of my Daily, Weekly, and Monthly report examples.
Dashboard example breakdown
Daily report example
Weekly report example
Monthly report example
Use images in SAS Visual Analytics to enhance your report link was published on SAS Users.