Presentatie AI: Graph analytics

1. GRAPH ANALYTICS

2. WHAT ARE GRAPH ANALYTICS
• Analytics tools used to apply algorithms
• Helps to determine strength and direction of relationships between objects
• Focus on:
• Pairwise relationship between two objects at a time
• Structural characteristics of the graph as a whole
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3. WHAT CAN IT BE USED FOR?
• Social network influencer analysis
• Detecting financial crimes
• Spotting fraud
• Optimizing routes in the airlines and retail and manufacturing industries
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4. EXAMPLE OF A GRAPH
REPRESENTING RELATIONSHIPS
• Graph analytics can help answer questions like:
• How many other individuals does the average individual “friend” with?
• How interconnected are groups of users with one another?
• How many “friend” relationships does it take to get from one user to another user?
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5. DIFFERENT KINDS OF GRAPH
ANALYSIS
• Path analysis
• Connectivity analysis
• Community analysis
• Centrality analysis
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6. BUSINESSES THAT USE GRAPH
ANALYTICS
• TigerGraph
• Headquartered in Redwood City, California
• The world’s fastest graph analytics platform designed to unleash the power of
interconnected data for deeper insights and better outcomes
• TigerGraph’s proven technology is used by customers including Intuit, Wish, China
Mobile and Zillow
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7. IS GRAPH ANALYTICS DISRUPTIVE?
• The survival of any business will depend upon agile, data-centric architecture that
responds to the constant rate of change
• Analytic leaders would do well to heed this warning, and begin researching and
investing around this trend
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8. GARTNER HYPE CYCLE
METHODOLOGY
• The Hype Cycle should help to make clear whether the new technology is really
becoming mainstream or whether it remains a hype and the technology goes out
like a night candle again.
• What do you really need to invest in, where are the opportunities and what
technology will it make in the coming years?
• Peak of Inflated Expectations:
• The technology is reaching its "hype peak". First success stories appear, but failures are
just as widely measured. Some companies start working with the technology, others do
not.
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9. WHY GARNTER CHOOSE THE RIGHT
PLACE IN THE CYCLE
• Graph analytics will become the standard tool for analyzing a brave new world of
complex data relationships
• Businesses and organizations continue pushing the capabilities of big data and
analysis
• Graph analytics is a must-have for today’s needs and tomorrow’s successes

10. SOURCE REFERENCE
• About Tigergraph. (n.d.). Retrieved December 4, 2019, from https://www.tigergraph.com/about/ (slide 6)
• Graph Analytics. (2018, June 12). Retrieved December 4, 2019, from
https://developer.nvidia.com/discover/graph-analytics (slide 2)
• IBM. (n.d.). What is graph analytics? Retrieved December 4,
2019, from https://www.ibmbigdatahub.com/blog/what-graph-analytics (slide 2-5)
• Wermter, P. (2019, April 10). Prepare for Disruption: Gartner’s List of Disruptive IT Trends Is Out. Retrieved
December 4, 2019, from https://www.apexofinnovation.com/prepare-for-disruption-gartners-list-of-
disruptive-it-trends-is-out/ (slide 7)
• What is graph analytics? (n.d.). Retrieved December 4, 2019, from
https://whatis.techtarget.com/definition/graph-analytics (slide 2 +3)
• De Gartner Hype Cycle: welke technologie blijft plakken en welke gaat nodeloos ten onder? (2018, 23 april).
Retrieved December 4, 2019, from https://robertvaneekhout.nl/2018/04/gartner-hype-cycle-welke-
technologie-blijft-plakken-en-welke-gaat-nodeloos (slide 8)
• Alter, L. (2017, 5 juni). What’s at “the peak of inflated expectations” now? Retrieved December 4, 2019, from
https://www.mnn.com/green-tech/research-innovations/blogs/whats-peak-inflated-expectations-now ( slide
9)
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