The Oracle Analytics team have been busy working on the latest version of Oracle Analytics Cloud - 5.9 which is packed with a number of interesting features and enhancements that we'll cover in some detail in this blog post.
There is now a permanent Search field and smaller Data, Visualisations and Analytics icons which have been relocated to the top of the side bar. This results in the reduction of wasted space on the left of the side bar.
The animated progress bars that are displayed when visualisations and data are loaded have been updated.
The thin blue horizontal progress bars that were visible in previous Oracle Analytics versions across the screen when a. visualisation or canvas was refreshed have been changed as you can see in the images above.
There is now one click access to TRIM whitespace from a text column in the Data Preparation stage of Data Visualisation. This removes whitespace from both sides of the selected column
US ZIP Codes
This new feature is available in a column that contains ZIP code data. Oracle Analytics suggests a recommendation step to repair any of the ZIP codes that have missing leading zeros.
You can now move a Visualisation level filter to the Canvas level by simply dragging it from the side bar to the Canvas level filter section. You can also do the opposite; moving a filter from the Canvas level to a specific Visualisation.
There is now the capability in OAC 5.9 to sort by multiple dimensional attributes. In the screenshot below, you can see that the state_name and county_name have sorts defined.
Columns added to the Size and Tooltip of a visualisation can also be included in the visualisation sorting.
You can also sort by a measure but note that this will overwrite any dimensional attribute sorting that has been previously defined for the visualisation.
For those who still export data dumps to Excel ?, row limits have been increased. Formatted exports that include XLSX, PPTX, HTML and PDF files have been increased to 400,000 rows with instances that have 16-52 OCPUs. Instances with 2-12 OCPUs will have their limit increased to 200,000 rows.
The limits of unformatted report exports (XML, Tab Delimited and CSV) have been increased to 2,000,000 rows for instances with 2-12 OCPUs. Instances with 16-52 OCPUs will see their limits rise to 4,000,000 rows.
Area Visualisation Enhancements
There were previously 2 Area Visualisations in versions of Oracle Analytics prior to version 5.9. There are now 3 types; Area, Stacked Area and 100% Area.
I personally think that the new Stacked Area visualisation is more "visual" and users can gain a quicker insight visually.
New Mapping Options
These new map backgrounds give users more flexibility with their map visualisations.
It can be useful to gain some insights into the Machine Learning models that Oracle Analytics uses. There have been some enhancements added to the Oracle Machine Learning (OML) inspect tab which exposes much more metadata about the Machine Learning model.
There has been some renaming and reorganising of the tabs available in the Machine Learning Inspect window. The Details tab contains basic information about the Oracle Machine Learning model including input and output columns.
The Related tab now shows in-depth information of the Oracle Machine Learning model which is stored in database metadata views.
You can even access these views and build out visualisations to gain further insights and understanding of the Machine Learning models that you are using in your Analytics.
The Oracle Analytics team have put together a YouTube video about it which you can view below.
In previous versions of Oracle Analytics, Text Tokenization was indirectly available. OML ADW capabilities could be used. Francesco Tisiot recently blogged about this with a good example demonstrating a typical use case for textual analytics.
In Oracle Analytics Cloud 5.9, Text Tokenization is natively available as a data flow step thereby taking away the need to access the ADW instance in order to create a context index on the text column to be analysed and then to link the tokens to the text field in your data that is being analysed. This is now done for you automatically.
The Text Tokenization functionality only works with Oracle sourced datasets - ATP, ADW and Oracle On-Premise Databases. It makes use of the Oracle Text database functionality and the Database Analytics data flow step is only available for these Oracle sourced datasets.
In order to avoid this error:
Ensure that your user account that you use for the connection to the database has the correct privileges:
As you will have gathered, this 5.9 release of Oracle Analytics Cloud comes packed with a wide range of features and enhancements. The release is typically staggered whilst the upgrade is applied to the Oracle data centres in the various regions so watch this space! If you want to see further details of all of these new features, check out the Oracle's "What's New" document here.
If you’re intrigued with the features that Oracle plan to incorporate into the Oracle Analytics platform here is some information on an Oracle Analytics resource worth mentioning; the public roadmap which contains information on Oracle Analytics features that may be included in the platform with an idea of when these may become generally available.
The Oracle Analytics Product Management team descended on London ahead of the Oracle OpenWorld Europe event for the Oracle Analytics Summit London event held at The Soho Hotel in London on the 11th of February earlier this week.
The day kicked off with a Partner Advisory Council session from the Product Management team which included a look ahead at the roadmap for Oracle Analytics as well as a Q&A session which was very informative.
There were several other sessions throughout the day providing participants with a wealth of knowledge on all things Oracle Analytics.
The biggest announcement of the day was undoubtedly Oracle being named a visionary in Gartner's Magic Quadrant for Analytics and BI Platforms. The news was hot off the press and received mixed reactions.
Oracle has had a torrid time in the eyes of the Market Researchers in recent times with the likes of Gartner completely excluding Oracle from the Analytics Magic Quadrant not too long ago. Gartner's justification was regarding the fact that Oracle's Analytics offerings provided little or no self service features which is an opportunity that Oracle missed with the likes of Qlik, Tableau & Power Bi to name but a few that filled the gap in the Self Service Analytics space.
The Oracle Analytics team has filled the Self Service void with a variety of features and products including products and features like Oracle Analytics Desktop, Data Visualisation, Natural Language Processing and all the Augmented capabilities that enable end users to get to their insights with little or no IT intervention. This focus and attention led to Gartner bringing Oracle back into the Magic Quadrant as a niche player.
Oracle has made huge strides in the self service analytics space at the expense of the governed analytics capabilities that hasn't seen much development and enhancements in recent times.
The governed analytics part of the Oracle Analytics product is very mature and is its unique selling point. You hear of many stories where end users have acquired a self service analytics tool and plug it into OBIEE's semantic model. Most of the "new age" analytics tools are geared around self service and there still appears to be a huge demand for governed analytics which Oracle Analytics provides alongside its self service capabilities.
Some have said that Oracle may have taken their eye off the ball in order to focus all attention on getting back into Gartner's good books. As mentioned previously, a lot of attention has been focused on self service capabilities possibly to the detriment of governed analytics capabilities.
There was a mix of the Oracle Analytics Product Management team, Partners and Customers in attendance at the Oracle Analytics Summit and it was great to see and hear first hand from the Product Management team.
The purpose of this blog post is to highlight the results of a number of Research Analysts reports that have been recently published on Analytics platforms and how Oracle Analytics Cloud measured up with other vendors.
In the findings of 451 Research, it is claimed that “the sleeping giant has awakened “.451 Research notes that Oracle Analytics Cloud is the second largest part of Oracle’s PaaS business which is a bold statement if true.
Machine Learning and Artificial Inteligence features that have been incorporated into the Data Preparation functionality of the Data Visualisation tool got a mention.
Oracle Analytics Cloud platform was categorised in the Leaders quadrant according to G2 Crowd’s research. G2 Crowd collates its results from reviews from hands on users of these tools.
In Gartner’s 2019 Magic Quadrant for Analytics and Business Intelligence platforms, Oracle has made a re-entry after a brief absence in 2016 for being too IT centric and being late to the bimodal Analytics party.
Oracle made it back in as a Niche player by addressing this issue by expanding the functionality of the Data Visualisation tool giving end users the ability to mashup data from the IT managed semantic model with spreadsheets for instance. Gartner has recently mentioned a term, “Augmented Analytics” several times and it appears that Oracle has made huge strides in this direction by implementing such things as Data Preparation, Machine Learning and Natural Language generation which are all in line with Gartner’s Augmented Analytics.
You may have noticed the varied opinions of these Research results and I must admit that a lot of great work goes in to creating these reports but there is also a huge amount of subjectivity that is involved in the process.
These reports are useful but shouldn't be used in isolation when you may be on the market for Analytics tools. It should form part of the process.