Visualization? Wayne D. Van Sluys Lead Consultant & Oracle ACE - PowerPoint PPT Presentation

What is Oracle Data Visualization? Wayne D. Van Sluys Lead Consultant & Oracle ACE info@interrel.com epm.bi/videos

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Disclaimer • These slides represent the work and opinions of the presenter and do not constitute official positions of Oracle or any other organization. • This material has not been peer reviewed and is presented here with the permission of the presenter. • This material should not be reproduced without the written permission of interRel Consulting.

Intro to DV

Think About This • Your eye will focus on about 50 things per second • In an average lifetime, eyes see 24 million different images. • 80% of our memories are determined by what we see

A plane figure with four equal sides and four right angles

90% 65% 40% 60,000x 36,000 .25 6

Why Data Visualization? • We must be more agile • We need a solution to help us find trends, patterns and relationships across a number of data sources • We need a visual graphical interface (no programming please) • We don’t want to have to rely on super technical resources to access information • No more big huge expensive data warehousing projects • Sources of data can change and need to be able to quickly update • Change the standard; change expectations

̶ ̶ What is Data Visualization? • Self service visual representations of data Enables people to see data presented in a visual format Use charts and graphs for more detail

How is Data Visualization Being Used? • Comprehend information quickly • Pinpoint trends • Identify patterns • Communicate a story

Benefits of Data Visualization • Vivid information – not just a spreadsheet for upper management • Review information in a new, constructive way • Enables users to visually see connections between business processes • Ability to detect shifts in customer behaviors across multiple data sets faster • Brings actionable insights to the surface • Tell a story with data

Data Visualization • Self service data exploration and analytics in visual, modern BI interface • Connect to Essbase cubes as well as well as many other data sources for data exploration, analyses, and dashboards • Click and drag UI to create visualizations • Create multiple canvases / insights • Presentation and story telling mode • Use Data Flows to Wrangle and Mashup Data to create new Datasets • Ever expanding library of visualizations • Any user / no tech skills required • Machine Learning • Artificial intelligence • Natural language • Custom visualization plug-ins available from online library

Demo: Self Service Analysis – Gross Sales

Cool DV Features

Not Just Visualizations – You can Model with Data Flows • You can use data flows to produce curated (combined, organized, and integrated) data sets • Data Flows are available in the DV UI • Build data sets from a predefined sequence • Refresh your data regularly on a schedule • Load data into an Essbase cube • Load to relational table • Data flow results are available in BI & Published Reporting

Related: OAC BI Guided Analyses & Dashboards • Guided dashboards and analytics for “click the button” users • Model sources for BI consumption • Users can consume data and interact with data through guided prompts, controls, and action links • Mobile devices can be used to create analyses and interact with the data • Essbase, relational, or any data source

OAC DV vs. OAC BI BI Cloud Data Visualization (DV) OAC DV OAC BI ▪ ▪ Create analyses and Create DV projects dashboards ▪ Data exploration and ▪ Guided user experience analytics through pre-existing ▪ Modern interface Self service dashboards Guided analyses ▪ exploration and Self service analytics ▪ and dashboards Traditional BI interface visualization ▪ Single OAC Essbase cube ▪ Report and dashboard per project designers create content for Analyses and ▪ DV Projects audience Click and drag UI to create Dashboards powerful visualizations ▪ Reusable / repeatable ▪ presentations with updated Create multiple canvases data and insights Old school tried Cool new solution and true ▪ ▪ More modeling capabilities / Presentation and story telling RPD mode ▪ ▪ Relational data Any user / no tech skills required ▪ Slightly more technical requirement

DV Connections & Data Sets Create a DV Data Set

̶ ̶ Data Prep for File Based Project • DV accepts file of type: .xlsx, .xls, .csv, and .txt (custom delimited) • Currently, files have a maximum size of 50 MB • One or more files can be uploaded with “numbers” (measures). Numerical data is considered to be the “facts” (like in the relational world). If uploading data files from multiple sources, it is best if the data across the files matches exactly (i.e. don’t have “TX” in one file and “Texas” in another) • (Though there are other cool features to assist with this later on) • The other columns are considered the “attributes” of the facts Avoid null values in these columns

̶ ̶ ̶ Data Flows • A Data Flow is similar to an Extract Transform and Load (ETL) process used in data warehouse systems, but simpler. Data Flows allow power users to combine data from a number of different sources and create a new data set for use in DV projects • Right click and Add Step to add another spreadsheet It’s easiest to use a data flow if the two source files aren’t exactly the same, to use some fun transformation options Can be opened to edit or run to refresh the data file that has been created by the flow

̶ Data File • Once a data file is uploaded, it is displayed in DV Attributes (dimensions/attributes) and Measures (numbers) will need to be tagged accordingly. Data Flows read the file to the best of their ability, but it’s best to review each column and confirm it is correct (and fix it if not).

̶ ̶ ̶ ̶ Data Wrangling and Calculated Columns • Data Wrangling and Calculated Columns Data Wrangling is the process of manually mapping data from its original format to another that can be read easier Create a calculated column to replace a symbol so metadata matches Join the data sets Remove the excess columns

Blended Data • Blending is the joining of two or more files or sources and this can also be done within a project

Creating a Data Connection & Data Set (Essbase example)

Must Grant Security for Data Sources

Creating a Project in DV: Basics

̶ ̶ Overview • When you create data visualizations, you group them by “project” • For some source types, you can combine them with other data sources into a single DV project One exception is Essbase Cloud cubes; you can only choose one cube per DV Project in the current version • From Data Sources screen, in the bottom of the left pane, there are options for creating new Data Sources, Connections, and Data Flows. You can either add them from here or you can add them from within a project (shown in next slide)

Basic Steps • From the DV home screen under Create, click “Project” • Select the appropriate data source • Visualize mode to create graphs and charts • Drag and drop members and generations from the left panel.

DV Project Window

̶ ̶ Left Navigation Bar: Data Elements • Data Elements tab Lists the data elements from all data sources Select one or more data elements or columns and drag into the Canvas area

̶ Left Navigation Bar: Analytics • Analytics tab Lists available analytics highlights that can be added to visualizations like trend lines or outlier highlights

̶ ̶ Left Navigation Bar: Visualizations • Visualizations tab Lists the types of visualizations that can be added to the Canvas Visualizations are grouped for easier access