Each of the following video clips were recorded by me, Mark Daynes, and are designed to show ‘something interesting’ using Oracle Analytics Cloud (OAC) in a very short time period, typically around a minute. Most examples are focused on visualizations elements. Whilst these were created using OAC, a lot will also apply to Oracle Analytics Desktop
Examples 1-16 were created using the January 2022 version and all others were from the latest version applicable at the time.
1. Make mine a skinny donut
The video below shows how we can quickly tweak a donut chart to make it skinny.
2. Make a data point stand out
In the video below we make a data point near Newcastle stand out by changing its colour and also its shape so that it is a bright cross and thus distinctive.
3. Using a Visualization as a Filter
In the video below we create a visualization and then create a table visualization and use the table to filter the results.
4. Quickly view data at a relative time to today (e.g. last 6 months).
In the video below we create a new relative time filter so we can filter the data in the chart relative to todays date.
5. RAG Status Colour Coding
In the video below we apply a RAG status to data in a table.
6. Multi-Select and Change Common Properties of Selected Visualizations
In the video below we select multiple visualizations and then change some common properties simultaneously.
7. Zoomable, auto-focus map, controlled by second visualization
In the video below we create a map visualization and then create a trellised view and filter the map by the trellis and show zooming in action.
8. Trend Lines, Reference Lines and Forecast
In the video below we will add various reference lines such as median, maximum and minimum and then add a polynomial trend line and then add a forecast.
9. Natural Language Generation
The video below shows the creation of a chart which we then duplicate and the visualization is then changed to provide a Natural Language interpretation. We then go a step further and add a second metric to the NLG visualization.
10. Auto Insights
The video below shows the OAC auto insight generation in action. It creates suggested visualizations based on the dataset and allows them to be selected and used in the workbook.
11. Adding a Note and Linking to Data Points.
The video below shows us creating two visualizations in Oracle Analytics Cloud (OAC), adding a new note and then linking the note to datapoints in the visualizations. Thus, when we are presenting this workbook, the viewers can see the comment and the data points to which it applies.
12. Using the Data Quality screen to review data and set location columns.
The 2 min video below shows us creating a new data set in Oracle Analytics Cloud (OAC) from a table in an autonomous database. We then review the data using the data quality screen and see how certain items are distributed. We perform some filtering to examine the data before we toggle the latitude and longitude columns to be attributes and indicate that they are location columns prior to us using them in a new workbook.
13. Data Action ‘in action’
The following video shows the creation of a ‘detail’ canvas, a ‘master’ canvas and a Data Action to navigate from one to the other passing context upon which to filter the detail.
14. Sentiment Analysis and Binning – Adding value with a Data Flow.
The following video shows a simple example of how we can use a dataflow to add additional content and value to a dataset. There’s a lot of options, including invoking machine learning models, but here we just show a couple such as Sentiment Analysis and also put the sales figures into some bins and then we take this augmented data and visualise it.
15. Custom Backgrounds
The following video shows the assignment of a custom background image, (which can be used for presentations, infographics, etc), making the canvas freeform and adding a new example visualisation.
16. Use “Search Everything” to Explore Indexed Datasets.
The following video shows an example of using the ‘Search Everything’ bar to visualize indexed dataset data.
17. New Dashboard Filter Bar in Action
The following video shows some of the basic new features of the Dashboard Filter Bar in action (and we are using the March 2022 version of the Oracle Analytics Desktop here). This component acts as a way of grouping dashboard filters together so they can been seen as a logical unit. Here we see the ordering of the filters set, the background of the bar being customised, ‘Apply’ and ‘Reset’ buttons applied and the orientation of the bar changed. Auto dependency is used between each filter.
18. Persistent right-click calculations
Added 30th May 2022
The May 2022 version of Oracle Analytics Cloud introduced the ability to ‘Persist right-click analytics calculations’ so when creating Outliers or Clusters by using the right click and create statistics, these ‘persist’ in the visualization and are able to be made into custom calculations and re-used.
In the example video below, we take a years worth of sales figures, shown by month, for four sales people. To help us analyze these figures, we use clustering to see how the sales data for each sales person is distributed. We then create a new cluster calculation and duplicate it and make some tweaks to change the K-Means clustering value from 5 to 6 clusters and then show how we can quickly and easily use this in a new visualization. All under 2 minutes.
19. Overlay Charts
Added 17th July 2022
Overlay Charts were introduced into the July 2022 versions of OAC and Analytics Desktop. We can use overlays to build multi-layered visuals whilst also being able to control the transparency of each layer. When layers are added, they default to the Y-axis, but where there is a need to do so, we can also use a secondary Y-axis. In this example, we create two line charts and then a third, a bar chart that needs to use a secondary Y-axis where we also tweak the transparency to de-emphasize the focus on the bar chart.
20. Composite Cards
Added 18th Sep 2022
Introduced in the September 2022 release was the concept of composite cards. Now we can add a tile to a visualisation and include up to three measures whilst having some control over both the layout and sizing properties of each measure. In my example I take what is already what I consider to be a ‘composite visualzation’ of the Overlay Chart and further enhance it with summary metrics at the top. So, in one visualization we can see the interplay between the Forecast and Actual sales as line charts, the number of customers we have on a monthly basis that underpin the sales, and now we have totals for the year for the Number of Customers, with the Forecast and Actuals clearly displayed on the top as primary and secondary measures.
21. Custom ‘No Data Found’ Message
Added 9th Oct 2022
The default message when a visualization returns no data is simply ‘No Data Found’. In the September 2022 release we can now change this to a custom message by toggling a new workbook setting. In the example below we show how to set this, sarting with a visualisation that does actually return data and then giving it an expression filter that is so restrictive as to return no data. Note the granuality; this is not sensitive at a visualisation or a canvas basis, this is a workbook property.
22. New Filter Bar
Added 9th Oct 2022
The new Filter Bar provides a lot of new context sensitive filtering to the components that are simply dropped into it. This facility gives us some really easy access to a range of filtering options that are item type specific. In the short example below we create an analytic from scratch and also add in some new tiling so we can see a few metrics as well. We then apply a numeric filter and then show how this can also be individually disabled too, then we add a date filter before clearing all filter values.
23. Export to Excel with Formatting (Preview).
Added 4th Dec 2022
In this video we show the new (preview) feature from November 2022 of exporting to Excel with formatting. In just a minute and 40 seconds we create a new visualization, we add a grand total and format that. We then order from high-low sales and then add some RAG status colouring to highlight the clusters of highest achievers, mid range and low achievers. We then use a new feature to rename a column in the output to something different than the default from the subject area. We then take all this and export to Excel and see how we retain that formatting.
24. Sliders
Added 4th Dec 2022
Intoduced in the November 2022 release, sliders provide us with some interesting interactivity. Here we create a new visualization and apply a time based slider to see the change in income over time. We take a date field and tweak it to act as a slider to show the change in income on a week by week basis and play that back at a high speed setting.
25. Re-purpose an Auto-Insight Generated Calculation
Added 6th Dec 2022
Auto-Insights are super useful for providing some really interesting insights into the data. Quite often they also provide some innovative calculations to support the visualisation they suggest, and so I recommend having a look at these as they often provide some useful inspiration for other ideas. In this short video below, we see a ‘Top 10’ analytic being created based on one metric which performs a ranking by that metric and then creates an ‘others’ section. We take this calculation, duplicate it and then change the measure from the count of flights to the sales value and then rank the sites into the top 5. We then duplicate the visualisation and replace the original calculation with our new one. We still have some visual tidying up to do with titles and axis, but in under 2 mins we get a lot of additional value from the calculation provided by Auto-Insights.
26. Custom Sizing of Location Points
Added 12th Feb 2023
The January 2023 release of OAC provides the ability to change the size of the location points. The video shows how to simply do this so that they can be set to a size appropriate to their density. In this release, the Property panel is now adjacent to the Grammar panel and is easier to navigate.
27. New Tile Visualisation
Added 12th Feb 2023
Oracle OAC January 2023 introduced a new tile visualisation which has more flexibile features than the original, which is now shown as deprecated. In this short video we show the creation of a new tile for a main measure of “Sales Values”, for which we create a custom title and tweak the font size and also the size of the measure value. We then choose a “centre-centre” layout and then add in two more secondary measures and set their values to a custom size. Finally we apply a pre-existing conditional format to the tile.
28. Make It Snappy
Added 26th Feb 2023
The Jan 2023 version of Oracle Analytics introduced the “Snap to Grid” functionality to provide further visualization layout and alignment capability. Once the canvas is toggled into Freeform mode then we can set up the grid size to our needs, make the grid visible and then align visualization objects to the grid.
29. Can You Explain That To Me?
Added 26th Feb 2023
Explain functionality in Oracle Analytics Cloud provides machine learning generated insights on specific attributes and measures that can be used as visualizations and filters in our projects. Explain’s output is subdivided into four different sections : Basic Facts, Key Drivers, Segments and Anomalies. In the following video we select a column (Sales Item) and run Explain on it to examine some of the generated insights. We then select some of the generated visualizations to use in a project. Starting with the basic facts, we let explain give us the basic information about the Sales Items so we can quickly see the various Sales Items we have and how they compare to each other in relation to the metrics available. Next we pick the Key Drivers and see how the Sales Items corrolate to outcomes. We then look at Segments, which runs a classification algorithm for the attribute being examined and allows us to set a variable number of segments to be generated across selected attributes/measures in the dataset to determine key intersections. When segments are added to a project they create a new custom calculation, which can be examined and then added as a filter to include or exclude data related to that segment.
30. Combining Multiple Techniques
Added 5th March 2023
The prior videos have tended to focus on single things “of interest”. In this short video we show a number of techniques combined together to create a data story using sample data of balloon pilots flights over time. Firstly we create a detailed data canvas showing sales per pilot in a graphical format and then copy that visualization to display it in a data table colour coded by pilot with a grand total. We then select both visualizations, where Oracle Analytics shows us the shared properties of the selected objects we can change which will affect all selected objects. Using this feature we hide the legend to maximise the visualization real-estate. We then create a second canvas to show sales by pilot and then duplicate that visualization to show by a another measure, the number of flights. We then create a dashboard filter and use the facility provided by Oracle Analytics with date fields to change the granularity and choose a weekly view. Tweaking the layout, we create a slider of all of the weeks and then hide the grammar panel to maximise the layout and set the slider to display the details of sales and number of flights for all pilots on a week by week basis. Then we create a data action to connect the visualizations to the details canvas we first created, passing all values. This allows us to focus on the pilot and sales during the week in question we are viewing. We then show this drilling to detail action for both visualizations we have. In just a very short 3 minutes we show how easy it can be to create really responsive visualizations without any coding to analyze data.
31. Shadow Outline to make visualisations “pop”.
Added March 26th 2023.
The March 2023 release of Oracle Analytics gives us further enhancements to the layout, including the ability to specify shadow properties.
In this example we create 4 tiles and tweak the font sizing and add some background colour and then select a shadow style to give the tiles some extra visual “pop”. In the video the method used to quickly duplicate the visualisation once we have it in the format we desire is ctrl-c to copy it and then ctrl-v to paste it. We can then simply change the metric to rapidly build a suite of tiles in the same format.
32. Annotations and Formatting Together
Added Jun 10th 2023
The May 2023 release introduced the concept of annotations within conditional formatting. In this very short sub 2 minute video we create a new visualization and add both conditional formatting to highlight underperforming sales figures and then add an annotation to provide additional contextual information, which is really useful when creating a data story for presentation.
33. Binding Parameters
Added August 20th 2023
We can now bind parameters to filter results, so that when a filter is set the parameters are also set and can be used in multiple places. In the following short video we show a “Region” filter being created and then a new parameter is created and bound to the filter. As an example we set the title of one of the analytics to dynamically show the Region filter values by embedding the bound parameter in the title.
34. Enhance Tiles with Spark Charts
Added August 23rd 2023
Spark charts are a super visual enhancement to add to tiles as we can see the movement of the measure over time and be alerted to any peaks and troughs. In this short video we start with a blank canvas and create tiles and format them before adding on a Spark chart and then cycle through some of the options that are available to us. We then show how easy it is once we have a tile created to duplicate and tweak for other measures to have the same look and feel.
35. Line Style Manipulation
Added December 1st 2023
On occasion we want to be able to show multiple lines on a chart and provide emphasis on some and put some into the background for context and reference. A new facility appears in the November 2023 release allows us to do just that. Using a combination of new properties we can change the transparency, width and style (sold, dotted, dashed, etc) of the lines. These new tools allow us to tweak the emphasis so our visualizations fit with the gestalt philosophy of “figure/ground”. In this short video we create an analytic showing material costs and labour costs for factory maintenance and we wish to have the maintenance costs blend into the background and have the item costs in the foreground. Watch what happens to the labour line when we change the new parameters.
36. Custom Point Sizes Everywhere
Added 2nd December
In video 26 we looked at the ability to change point sizes for location specific data. The grammar panels have now been enhanced to allow us to the change point sizes across multiple visualisations. In this short video we show how to make the points in a scatter sensitive to a measure value, and then provide some control over the size of those points. We also add an outline to the points. We then duplicate the visualisation and tweak to create line charts and show the points being resized here too.
37. Create a Card Deck in minutes
Added 3rd Dec 2023
Combining a number of techniques we can :
- Get Auto insights to suggest a range of different visualizations by interrogating the dataset and using AI to create a suite of visualizations for consideration.
- Select a few of these and allow the layout editor to auto-size the visualizations.
- Multi-select a number of these visualizations and change the border, shadow, etc to give them an appearance of “cards”
- Add in a couple of new Tiles for the Labour and Material Costs and show the costs for each over a period of time and make them also appear as cards and give them a distinctive background. Also change their default titles to be something quite specific.
- Revisit the other “cards” in the “deck” and give them a more subtle background to distinguish between the tiles and the other visualizations.
The aim of this example is to show that in a few clicks, and without any coding, we can combine a number of techniques to create deck of analytic cards against a data set in a very short time.
38. Banding
Added 13th Jan 2024
We can now create visual “banding” on analytics to draw attention to specific areas of a chart. This is a development of the reference line statistical functionality, whereby we can create a reference line and select a range of date values to highlight. We can then set the transparency, colours, to suit our requirements to finesse the look and feel.
39. Annotate Tables with Icons
Added 15th Jan 2024
A new extension of conditional formatting allows us to specify icons and emojis that can be displayed in the tabular reports. In the following video we show how to do this from scratch in a minute and then also apply some shading. We have a table of monthly sales data and can use icons and some subtle colouring to highlight the months where the sales dipped according to the prior month. These visual cues focus our attention to the data elements that are important to us. The “down arrow” adds meaning indicating the trend of the sales more so that just the shading which acts to draw our attention to the items we need to look at. We do not need anything to indicate that sales went up, as we can assume that they are fine from the fact that they are not brought to our attention. Thus we reduce any visual noise and see the data we are interested in with minimal cognative load.
40. Emojis on Tiles
Added 10th March 2024
In the March 2024 release, we build on the formatting shown in Video 39 with icons and emojis being assigned to Tiles. Previously, whilst “RAG” (Red, Amber, Green) colour coding can be applied through conditional formatting, we can now assign other visual cues such as Icons and Emojis to tiles. Deuteranomaly is the term for Red/Green colour-blindness, so having other visual cues in addition to colour coding can be significantly useful. In the following short video we show the above tile being developed from scratch.
41. Range and Relative Time Filter Parameters
Added April 14th 2024.
Building on the parameters we looked at in Video 33, we can now easily bind parameters to date range and relative time filters. See here in the manual for details on binding parameters to filters. In this example we create a new analytic to show the sales of books of different types across a couple of years. We add in a column filter so that data can be filtered by the book type. Then we can drag the sales date to the filter section of the analytic. Then we can see the various range options, such as Relative Time and Range. Selecting range, we can then create and bind a “start date” parameter and “end date” parameter and bind them to the start and end dates of the ranges. It is then a simple process to drag these new parameters to the filter bar and this will allow us to enter start and dates. Combined with the column filter we can interrogate the book sales by a range of dates for different book types.
42. Inline Filters
Added May 8th 2024
In the May 2024 release, there is the ability to add filters that appear as checkboxes (for multi-select) and radio buttons (for single select). This works best when there is a relatively small number of options as otherwise they can take up too much screen real estate, the users spends longer search for the options and also there are limits to the number that can be shown. For a small number of options and for quick access this is an excellent option. In the following video we load up some data of star rating for delivery drivers. In this example they all have ratings ONE, TWO or THREE.
We will create a visualisation of the data and then add a standard list filter for the ratings and see that in action. What we then do is to change this to the new “InLine” type with checkboxes for multi select, then change to radio buttons for single select. We then toggle from horizontal to vertical layout.
43. New Sankey Chart
Added August 19th 2024
The July 2024 release provides enhances Sankey diagrams. The short video below looks at a small data set that shows sales for products that are categorized. Putting this into a Sankey Chart automatically shows us the sales people, the items they are selling and the categories they belong to. Using new functionality, we can adjust many parameters such as widths and gaps to get the layout the best suits our data. One really useful features is the ability to group by column or value. In the example above we group by “value” so that we can see the sales for the groupings. The new Sankey chart is a much improved representation that the one available previously and is well worth evaluating where you have categorised data.
44. 100% Area Charts
Added September 1st 2024
The 100% Area chart is not a new visualisation, but it is not seen very often. In this video we start by creating a new bar chart visualisation then add a top 20 filter so that we can see the highest spending suppliers. Including the invoice date we can segregate data by colour, we then set it to show the data on a year by year basis. Then we switch up the visualisation to a 100% Area chart so that the year on year relevant contribution is evident. We can then set the line type to a smoother style and add in the data viz points to allow us to easily hover over them to see the actual values that we are interested in. Further, we can take that year field and use the right-click functionality to add it as a filter.
45. Automatic Date Differences
Added October 15th 2024
The September 2024 release of OAC added a really useful new feature for people using data sets, and that is the automatic data difference computation. In this example we take a data set of car sales and use this new facility to help us to calculate the difference between the order date and the delivery date of the cars ordered without any coding at all, which is a great feature for users who just want to see their data. We can then use the auto-insights feature of OAC to create some visualizations of the data in order to quickly see the forecast of differences between order and delivery dates, as well as the customers with the longest waits.
As the AI assistant is being rolled out across OAC instances (starting with those with high cpu shapes) we can index this new dataset and show the AI assistant in action, in addition to the “auto-insights” that we used in the video above. To see more about the AI Assistant, please check out my article here.
Firstly we need to index the dataset so that the AI assistant can be trained on the data and make it ready for use.
We can now ask the AI Assistant questions and get visualizations which we can add to the workbook.
Here we ask for the “top 10” durations – and we can see they are all very similar apart from one outlier. We then ask for that as a pie and add both to the workbook. It’s a simple case, but a different approach to the auto-insights that uses AI to create a bunch of suggested insights controlled by the parameters we set, here we are asking “natural language questions” of the data to get insights.