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Storytelling With Data Using Oracle Data Visualization


This article explains capabilities of Oracle Data Visualization (DV), a business analytics service for connecting, preparing, visualizing and sharing insights or stories from data.

The objective of this document is to help you understand what Oracle DV offers and how it can support your organization’s business intelligence (BI) strategy. The intended audience of this document are IT professionals, who manage organization’s BI platforms, solutions, and tools as well as BI analysts, who specialize in data modelling, analytics, and presentation.

Oracle Analytics & Data Visualisation – An Overview

Fig.1: Landscape of Oracle Analytics

Oracle Analytics is the only true analytics platform which provides capabilities such as Governed, Self-Service & Augmented Analytics to serve business needs whereas other vendors fall into either one or two of the capabilities i.e., Tableau in Self-Service Analytics, MicroStrategy in Governed Analytics.

On one hand, Oracle Analytics provides traditional BI reporting capabilities such as ad-hoc reporting, pixel perfect reporting & dashboards, where business team has a lot of dependency on IT teams for data preparation, building data warehouse and configuring semantic model for querying.

On the other hand, Oracle Analytics provides Self-Service Analytics through Oracle Data Visualization which enables business users to easily connect any of their data, explore data through interactive visualizations that reveal trends in an organisation’s data, discover important insights about your business and share them with team or organization members at any time on any device.

Oracle further embedded its AI, Machine Learning capabilities to provide next generation analytics called Augmented Analytics. Using Augmented Analytics, one can easily train their data by using in-built Machine Learning algorithms to predict anomalies or future trends.

Fig.2: Oracle Data Visualization Components

Oracle Data Visualization is available as stand-alone named Oracle Data Visualization Desktop (DVD) and Oracle Data Visualization Cloud Service (DVCS) as a part of Oracle Analytics Cloud (OAC). The individual components and their capabilities of Oracle Data Visualization are further described below.

Building Blocks of Storytelling in Oracle DV:

1. Connect to any data source:

Oracle Data Visualization, a part of Oracle Analytics provides Self-Service & Augmented Analytical capabilities for an enterprise with the ability to connect any data, irrespective of data availability (on-premises, cloud or third-party applications) & type of data (structured or unstructured).

  • 50 + built in Connectors to all types of data
  • Relational, NoSQL & Big Data
  • Non-Oracle SaaS Applications
  • Oracle Cloud, Third Party Clouds & On-Premises
  • Blend any data together regardless of source or type
  • Data Preparation/Enrichment capabilities
  • Smart connectors to Oracle Fusion Applications (ERP, SCM, HCM & CX etc.)
  • In-built AI & Machine Learning capabilities
Fig.3: Typical data sources that are supported by Oracle Data Visualization

One can easily connect to data sources of their choice using available in-built connectors and provide necessary details in order to establish connection. Once connection established, one can create data set out of that for further analysis.

Fig.4: Creating connection to data source

2. Create and prepare data sets & enrich your data:

Fig.5: Creating Dataset using existing Connections/SA

Data Set is a basic storage unit in Oracle Data Visualisation which will store data from various data sources, such as file, subject area (part of enterprise data modelling) or connection. Based on the source of data set, data access property can be enabled to either Live (data always returned from live source) or Automatic Caching (data from live source may be cached for faster performance). Data Sets based on file source cannot be refreshed automatically.

Data Flow

Fig.6: Transformations available in Data Flow

Data Flow is used to organize and integrate data to produce a curated set of data (Data Set) to build analytic content. Data Flows are powerful, not only allowing users to join disparate data but also perform some useful data preparation/transformation activities, ranging from basic filtering, aggregation and data manipulation actions to more complex sentiment analysis, forecasting and even some machine learning modelling features.

Importantly, Data Flows can be set to output their results to disk, either written to a Data Set or even to a database table and they can be scheduled for repetitive refresh.

Data Replication

Fig.7: Data Replications from Source to Target

It is a unique feature of Oracle Data Visualization which allows to source data from various Oracle SaaS offerings and then replicate data into target Database/DWH. With data replication, one can import and transform their data without using additional ETL/ELT tools.


Fig.8: Creating Sequence for data refresh

Sequence is the container which can execute multiple Data Flows and other Sequences one after another in a specific order.
When Sequence gets executed, it executes all the Data Flows and/or Sequences included, one by one in a specific order. In case Sequence fails during execution then it reverts all the changes done in the process of Sequence execution.

Explore/Visualize your data & gain quick insights:

In Oracle Data Visualization, Project is an object with one or more data sources containing the data and visualizations that can help to explore content in productive and meaningful ways. It mainly consists of three tabs – Prepare, Visualize and Narrate.


Fig.9: Recommendations & Data Mashups in DV

Data preparation involves cleansing, standardizing and enriching data set prior to analysis of the data in a visualization canvas. Oracle DV’s in-built machine learning (ML) algorithms facilitate recommendations based on the nature of data to the user, further to enhance & derive new data.
In case the visualization project involves analysing data from more than one data set (it does not matter, whether those data sets either from same source or from different sources), one can use joins, data mashup/wrangling based on relationship between data in order to find insights based on those datasets.


Fig.10: Creating & Picking Best Visualization

Oracle DV supports 30+ visualizations out of the box ranging from table, pivot, bar graphs, pie charts, donut, performance tile, tree map, heat map, tag cloud to advanced visualizations such as map view, scatter, boxplot, correlation matrix & tree diagram. Oracle DV has capability to pick right visualization based on the selected data elements. Advanced analytics such as reference line, trendline, forecast, clusters and outliers can be applied on top of visualization for more insights.

One can extend Oracle DV visualizations either by installing third party plugins from Oracle DV library or using Oracle DV SDK to create custom plugin based on D3.js


Fig.11: Building story with multiple canvases on Narrate tab

Oracle DV’s Narrate allows to add visualizations or canvas to the dashboard from the canvases which were created. It allows to write note about findings on visualization and share with the people.

4. Share with your organization members & on social media:

Switching to Presentation Mode

Fig.12: Presentation Mode of Oracle DV

Projects One can share the insights about their findings about the data to friends or members of organization, by switching the application to Presentation Mode. Presentation mode of an application will remove all the menus & buttons and focus just on the storytelling.

Share a Project/Folder as an Application

Fig.13: Exporting Oracle DV Project

One can share/export DV project with multiple supported formats such as pptx, pdf, png (only active sheet/visual), csv (includes only active sheet) and DVA.
The exported .DVA file includes the items that you specify such as associated data sets, the connection string & credentials, and ALC’s. One can further email the exported DVA file to enable other users to work with it.

Import an Application/Project

Fig.14: Importing .DVA Project

One can import .DVA file which was created by another user or can import an application from an external source such as Oracle DV library.
The import includes the items which are specified during export such as associated data sets, connection string & connection credentials, ALC’s and stored data.

Integrating DV Projects into BI Dashboards

Fig.15: Integrating DV Project with Dashboard

Option 1: Oracle DV Projects can be embedded into Oracle Analytics dashboards directly using ‘Embedded Content‘ dashboard object. It is possible to embedded DV Project directly in the presentation mode. For this, ‘&reportmode= presentation’ parameter needs to append to the URL of the project.

Option 2: Drag Oracle DV project just like analysis/prompt onto Dashboard and choose which canvas you want to present (in case more than one canvas exists) to the user.

Share via Social Media:

Fig.16: Sharing DV Project on Social Media

The project’s visualizations, canvases and stories can share as a file on social media such as Twitter, LinkedIn & Slack. One must create app with respect to social media, get authorized before publishing app using Client ID, Client Secret which were created as a part of App creation.


Oracle Data Visualization offers powerful analytical features which can be used to convert data into insights and further useful in supporting a culture of data-driven decision making. IT Team can benefit from easy provisioning of new data sources, fast deployment, and easy integration with existing Oracle Business Intelligence Dashboards. Business Analysts can leverage powerful analysis capabilities for easy data discovery, exploration, and visualization. Oracle Data Visualization’s self-service capabilities make business users no longer need to rely on IT Team for preparing whatever they required. By adding Oracle DV to your organization’s portfolio, you can make BI available to the people who need it, when they need it over the web & mobile.

Contact for further details:

Appi Reddy DUNDETI
Team Lead – Analytics Oracle

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