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This was an SAP webcast provided today.  Below are my notes.

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Figure 1: Source: SAP

Figure 1 shows Big Data Analytics Challenges; trying to extrapolate to the future.  We are making assumptions.

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Figure 2: Source: SAP

Figure 2 shows that we don’t know what this slide is about

It shows nodes, with subsequent nodes

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Figure 3: Source: SAP

Figure 3 shows a network, but what is it about?

Links to videos on Big Data Visualization:

UX Week 2012 | Jonathan Stray | UI for Big Data Visualization:

http://vimeo.com/52634331

Terry Speed_Data Science, Big Data and Statistics – Can We All Live Together:

http://www.chalmers.se/en/areas-of-advance/ict/calendar/Pages/Terry-Speed.aspx

Big data visualizations in previous figures give you sense that it is more art than enlightenment

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Figure 4: Source: SAP

Figure 4 shows a “fuzzy mess”.  Analysis is needed to depict signals from noise

We need to find creative ways to make outcomes are clear

We need to find appropriate visualizations to reduce complexity so consumable by end users

Relationships show different types of charts depending on what communicate and tell context of a story

Interactive infographics  try to condense information into a storyline and are static – see visual.ly

D3.js Example:

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Figure 5: Source: SAP

Figure 5 shows a Sunburst example using data driven libraries built with Javascript

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Figure 6: Source: SAP

The speaker said D3.js integrates well with Lumira

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Figure 7: Source: SAP

Figure 7 shows the future, with the convergences of analytics and statistics and using report writing in statistical tools

Statistical analysis and forecasting and recommendations for action to take

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Figure 8: Source: SAP

Figure 8 shows the future for more predictive analytics, easier, why did it happen, and what will happen

As analytics becoming more mature, there will be optimization and recommended action

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Figure 9: Source: SAP

On this slide the speaker discussed Google queries around flu – recent searches were surrounding commemoration, and not a flu outbreak

The speaker said “HANA makes statistical analysis more feasible”

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Figure 10: Source: SAP

Figure 10 shows the outcomes of Statistical Analysis in a dashboarding tool

Model on top is plot from R

Thick blue line in Lumira shows the projection


Using Lumira you can create a visualization from data from HANA

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Figure 11: Source: SAP

Figure 11 shows the architecture for Big Data visualizations using Hadoop, HANA and Lumira with R

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Figure 12: Source: SAP

Figure 12 shows the summary and conclusions.

The speaker cautioned how to handle nulls in JavaScript code

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    1. Tammy Powlas Post author

      Hi Timo –

      It was Jay Thoden van Velzen, Program Director Global HANA Services/Big Data Services CoE

      My mistake for not including this in the blog.

      Tammy

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