Presentation / Visualization / Self-Service

Allen May(CompuNet)

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Priyanka Bole(Hobart Service)

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6/26/2015

Today’s Agenda

• Presentation/Self-Service
• CompuNet Case study - SSRS
• Hobart Service Case Study - Excel based Self-serve
• Data Sources - Data warehouse, SSAS Cube
• Excel
• SQL Management Studio
• Visualization
• Dashboard
• Common Issues
• Best Practices

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CompuNet Self-Service SSRS Reports

Two project examples of moving to SSRS from a legacy process

Turnaround Test Reports

• Background - 10 years of daily e-mail
• Challenge - Vague purpose, Normalize reports
• Project - Consolidate and make self-service

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Project:

CompuNet QA Report

• Background - Originally created in MS-Access
• Challenge - Access database hard to use and frequently became corrupted. Data was copied into Access.
• Project - Convert QA Report to server-based solution that pulls data from CRM.

CompuNet QA Report

Hobart Service

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Another Example of Self Serve

Excel with SQL Server and SSAS Cube

Data Sources - Data warehouse

• Updated nightly from our 3 transactional applications including our main ERP system and 3 external sources.
• Has historical data from our mainframe systems
• Build various summary tables including complete service history table.
• Most of the SSRS reports and data reports are based on data warehouse.
• Very limited SSRS reports are based on transactional data.

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SQL Server Analysis Services

Multidimensional Cube

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A cube is a multi-dimensional data source which has dimensions and facts(also know as measures) as its basic constituents. The measures and dimensions in a cube are derived from the tables and views in the data source view on which the cube is based.

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Some of the main advantages of a SSAS Cube

• Speed: Aggregating (Summarizing) the data for performance
• Multidimensional analysis
• Support Hierarchies
• Built in Advanced time-calculations

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Hobart Service BI Cube

Our BI cube covers various areas of our business including all streams of revenue, service history, contract and claims data.

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It is based on our data warehouse and it is refreshed nightly.

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Our users are able to connect to this cube via Excel.

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Demo - Excel Based Reports

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Front to Back Analysis using BI Cube

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Service History Data using SQL

Visualization

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A primary goal of data visualization is to communicate information clearly and efficiently to users via the statistical graphics, plots, information graphics, tables, and charts selected. Effective visualization helps users in analyzing and reasoning about data and evidence.

Visual data processing provides optimal support for the following:

• Seeing the big picture
• Easily and rapidly comparing values
• Seeing patterns among values
• Comparing patterns

Source:

Stephen Few – Perpetual Edge

Wikipedia

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What is a Dashboard

"A visual display of the most important information needed to achieve one or more objectives that has been consolidated on a single computer screen so it can be monitored and understood at a glance”

- Stephen Few

http://www.perceptualedge.com/

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Dashboard based on

SSAS Cube Data

Common Data Visualization Issues

• Poor and/or incomplete requirements
• Business wants everything on their dashboards/Too much information
• Lacks actionable information
• Is more sizzle/Misusing or overusing colors
• Inappropriate Media of display i.e pie chart or 3-D charts
• Encoding quantitative data inaccurately
• Examples: http://www.perceptualedge.com/examples.php

Source:

Stephen Few – Perpetual Edge

Data Visualization Best Practices – Jen Underwood

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Data Visualization – Best Practices

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• Simple and communicates easily
• Reduce distractions
• Use a single Hue
• Increase the Intensity for low to high values
• Try shades of grey
• Must fit entirely on one screen
• Important to provide adequate context

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Source:

Stephen Few – Perpetual Edge

Victoria Hetherington: Dashboards Demystified