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Oracle Data Visualization (DVD/DVCS) Implementation for Advanced Analytics and Machine Learning

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Oracle Data Visualization Desktop(DVD) or Cloud Server(DVCS) is a very intuitive tool, which helps every business user in the organization to create quick and effective analytics very easily. People at all level can leverage the benefit of blending and analysing data in just a few clicks and help the organization to take informed decision using actionable insights. Oracle DVD is a Tableau like interactive tool which helps to create analysis on-the-fly using any type data from any platform, be it on premise or Cloud. Main benefits of Oracle DVDs are below:

·         A personal single user desktop tool, or a SAAS cloud service, which can be leveraged by any business user in the Organization.

·         Enable the desktop user to work even offline

·         Completely private analysis of heterogeneous data

·         Business user can have entire control over the dataset/connections

·         Direct access to on premise or cloud data sources

·         Administration task has been removed completely

·         No concept of remote server infrastructure

Oracle DVD/DVCS enables the business user to perform analysis using traditional methodologies as well as provides capability to perform Advance Analytics using R and creating Predictive model using Machine Learning algorithm using Python.

This simple and intuitive tool provides a very unique way to enable you to perform Advance analytics by just installing all the required packages. DVML (Data Visualization Machine Learning library) is the tool to help you install all the required packages for implementing machine learning algorithm for predictive analysis in one go.

Install Advance Analytics(R) utility will help you to install all the required R packages to perform Advanced Analytics functions like Regression, Clustering, Trend line etc. However, to run both the utility in your personal system/server, you need administrative access as well as access to internet and permission to automatically download all the required packages.


In the below slides we are going to discuss, how to leverage Advance analytics and machine learning functions to provide predictive analytics for the organization.

In order to create a Trend line graph, we need to enable Advanced Analytics and then pull required column into the Analysis.

Trend line Function: This function takes 3 parameters to visualize the data in a trending format.

Syntax: TRENDLINE(numeric_expr, ([series]) BY ([partitionBy]), model_type, result_type)

Example : TRENDLINE(revenue, (calendar_year, calendar_quarter, calendar_month) BY (product), 'LINEAR', 'VALUE')

We need to create various canvases and put them into one story line by providing corresponding description over the canvas. While creating Trend line visualization, we need to provide the Confidence level of data. By default, it will take 95% confidence level, which means the analysis will be performed over the 95% of data.



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