Unveil­ing the July 2023 OAC Release: Key Enhance­ments and Insights

The July 2023 Update for Oracle Ana­lyt­ics Cloud came out just a few days ago, and in this blog post we are going to look at its most import­ant new fea­tures. Here is a com­pre­hens­ive list of all the fea­tures and bug fixes.

1. Enhan­cing Data Visu­al­isa­tion: Spark Charts in Per­form­ance Tiles

Per­form­ance tiles are a valu­able fea­ture com­monly used in dash­boards and home pages to provide users with a quick over­view of key inform­a­tion. Oracle‘s latest release intro­duces an excit­ing addi­tion to per­form­ance tiles: spark charts. Today we’re going to see what spark charts are and how they enhance data visu­al­isa­tion within per­form­ance tiles.

What are Spark Charts?

Spark charts are com­pact visu­al­isa­tions that effect­ively present data trends or pat­terns in a con­densed format. These small graph­ics are designed to offer sim­pli­city and com­pact­ness, mak­ing them ideal for situ­ations that require the rep­res­ent­a­tion of mul­tiple met­rics or KPIs in a lim­ited space.

Now let’s take a look at how to con­fig­ure spark charts in a tile visu­al­isa­tion. As we already know, tiles in OAC can take mul­tiple meas­ures, the first being the primary meas­ure and the rest sec­ond­ary meas­ures. In the image below we can see that Oracle has added a new ‘Cat­egory (Chart)’ to the tile viz Gram­mar panel:

We can add an attrib­ute to this new cat­egory edge in the Gram­mar panel, and once we’ve done so, we will imme­di­ately see that a spark chart is gen­er­ated for the primary meas­ure. By default, the selec­ted chart type is ‘Line with Area’:

We can also cus­tom­ise these charts by mak­ing use of the prop­er­ties defined in the Gram­mar panel. In the image below, you can see the prop­er­ties avail­able for the spark visu­al­isa­tion, and users can also choose from sev­eral types of charts, includ­ing line with area, bar chart, and area chart:

We can cus­tom­ise other fea­tures of the chart as well, such as col­our, pos­i­tion (above or below), width, height, etc. Here is an image of a tile visu­al­isa­tion with a cus­tom­ised spark chart:

2. Para­meter Binding

This is a new func­tion­al­ity released in the July update that allows authors to bind a para­meter to a list fil­ter to spe­cify the filter’s value. Bind­ing para­met­ers to list fil­ters enables con­tent authors to dynam­ic­ally accept, store, and manip­u­late the parameter’s stored val­ues, and they can con­trol how the fil­ters behave and how they are used in the dashboards.

Let’s explore this inter­est­ing fea­ture with an example involving the cre­ation of a list fil­ter. When we open the list fil­ter, we can see a new icon in ‘Selec­tions’ that allows us to bind the para­met­ers to this fil­ter. The para­met­ers can be cre­ated in two ways: either by cre­at­ing a para­meter from the Para­meter panel or by using ‘Cre­ate Para­meter’ on the list fil­ter, as shown in the image below:

When you bind the para­meter to the fil­ter, the para­meter takes on the fil­ter value selec­ted by the user, depend­ing on the parameter’s defin­i­tion. Once the user selects a value in the fil­ter, it is passed to the para­meter. To view the val­ues stored in the para­meter, you can drag and drop the para­meter to the fil­ter tab at the top of the dash­board (see below):

How­ever, if you choose to define the para­meter by adding spe­cific ‘Pos­sible Val­ues’ in the Edit Para­meter sec­tion, the para­meter will only accept those spe­cific val­ues when the user selects the fil­ter; it will pass the remain­ing val­ues. The value in the para­meter can be used to fil­ter other visu­al­isa­tions on the canvas.

In the example below, we are cre­at­ing a new visu­al­isa­tion with a bar graph. We will then cre­ate an expres­sion fil­ter and add an expres­sion where the Product Band is in the <Para­meter Value>. This will auto­mat­ic­ally fil­ter the new visu­al­isa­tion with the val­ues that are bound to the list fil­ter we cre­ated in the example above. In the fol­low­ing image, you can observe that the para­meter has passed the value to the bar graph, which is fur­ther broken down by Com­pany. You may also notice that the legend dis­plays the value of the parameter:

The para­meter bind­ing func­tion­al­ity can also be used to pass the val­ues of a fil­ter con­trol on a dash­board fil­ter across dif­fer­ent canvases, whereas before a fil­ter con­trol could only be used to fil­ter val­ues on the same can­vas. In the image below, we have cre­ated a new can­vas from the above work­book and bound the fil­ter con­trol to the para­meter we cre­ated in the pre­vi­ous steps. When we select fil­ter val­ues in Can­vas 1, the fil­ter con­trol in Can­vas 2 changes accord­ingly, and the fil­ter is applied to the visu­al­isa­tions on that canvas:

3. Show/Hide Visu­al­isa­tion Toolbar

Every graph on a dash­board offers a set of visu­al­isa­tion actions that users can take when work­ing with it. Wouldn’t it be great to be able to con­trol which options are avail­able for each graph? Well, that is exactly what Oracle has done in this update! Let’s cre­ate a simple visu­al­isa­tion and click on the Present mode on top of the workbook:

In the Present mode, by click­ing on the Act­ive Can­vas panel we can see a new prop­er­ties sec­tion called ‘Visu­al­iz­a­tion Tool­bar’. With this enhance­ment, we can choose to show or hide the dif­fer­ent visu­al­isa­tion action but­tons. Here in our example, we’ve selec­ted a couple of prop­er­ties to show in the Present mode, and when we pre­view this, the action but­tons appear on the dash­board (see the image below) which the users can see:

4. Data Flows and Sequence Sharing

Data Flow, com­monly abbre­vi­ated to DF, is a valu­able tool for gen­er­at­ing data sets dir­ectly in OAC from mul­tiple sources, includ­ing exist­ing OAS Reports, whilst also allow­ing for modi­fic­a­tions. It is an excel­lent way to gen­er­ate work­books. How­ever, a sig­ni­fic­ant issue exis­ted until now – the inab­il­ity to share the data trans­form­a­tion object or Data Flow with colleagues.

Only the cre­ator could access it, and there was no func­tion­al­ity avail­able in other OAC objects to grant per­mis­sions to users or roles for Data Flows, which in turn meant chal­lenges in main­tain­ing and updat­ing pro­cesses because some­times the object that gen­er­ated the data set you were work­ing with couldn’t be seen. Fur­ther­more, this issue also affected Sequences, another type of OAC object. (Just in case you don’t know, Sequences are used when you want to run a pre­defined list of Data Flows in a spe­cific order).

Let’s dive into this fea­ture by cre­at­ing a simple Data Flow. First go to the Access tab in the Data Flow prop­er­ties, open the Data Flow in Oracle Ana­lyt­ics Cloud, and nav­ig­ate to the Inspect tab:

Within the Inspect tab, vari­ous tabs for dif­fer­ent aspects of the Data Flow prop­er­ties can be found. Click­ing on the Gen­eral tab enables us to view gen­eral inform­a­tion about the Data Flow: the Owner field, which indic­ates the owner of the work­flow (in this case, oracleuser), and addi­tion­ally we may find an Object ID field, which is mapped to oracleuser too.

Now, we click on the Access tab to view and man­age access per­mis­sions for the Data Flow. In the Access tab, we can define and modify per­mis­sions for users and roles to con­trol who can view and work with the Data Flow, allow­ing us to share it with other users and to grant them the neces­sary access rights.

In the Access tab we can see which users and applic­a­tion roles have access to this work­flow. We have added a test user to this Data Flow (giv­ing full con­trol access to the new user enables them to modify the access to the Data Flow). After click­ing on Save a pop-up appears, allow­ing us to grant appro­pri­ate per­mis­sions to the users:

5. Oracle Ana­lyt­ics Data Connectivity

In this new release, Oracle has also added new con­nec­tions to Snow­flake and Ver­tica data sources when cre­at­ing pixel-per­fect reports. These con­nec­tions to Snow­flake and Ver­tica are not new, but prior to this release they were not avail­able as sources when using Oracle Ana­lyt­ics Pub­lisher (formerly known as BI Publisher).

Along with this, Oracle has also intro­duced a new self-ser­vice con­nector to Oracle Ana­lyt­ics Views. With this fea­ture, the user can find and retrieve exist­ing ana­lyt­ics views to cre­ate datasets:

Con­clu­sion

And that was it for this month’s release! We have covered the main top­ics and to sum­mar­ise, Oracle is expand­ing exist­ing tools: tile graphs and para­met­ers are clear examples. We wel­come all changes that give more options for users to per­son­al­ise their reports, espe­cially if they lever­age exist­ing func­tion­al­it­ies instead of build­ing new ones, which helps flat­ten the learn­ing curve and allows for a more tailored cus­tomer experience.

Our Oracle con­sult­ants are espe­cially glad that Data Flows are finally treated as objects and can be shared to users and roles, and now have an easy way to know a Data Flow’s Source and Tar­get. This was a long-desired fea­ture, and we’re sure every­one who uses Data Flows will appre­ci­ate it.

In con­clu­sion, this month’s update brings an array of excit­ing enhance­ments and new fea­tures that empower users to new heights. These key enhance­ments and insights help users to cre­ate bet­ter dash­boards, ana­lyse data trends effect­ively, and col­lab­or­ate seam­lessly. Oracle con­tin­ues to invest in provid­ing a power­ful and user-friendly plat­form for busi­nesses to gain action­able insights from their data, thus enhan­cing decision-mak­ing and driv­ing busi­ness success.

Stay tuned as we’ll be bring­ing you more insight­ful con­tent soon, and in the mean­time don’t hes­it­ate to con­tact our team of Oracle experts if you want to lever­age this tech­no­logy to boost your busi­ness results!