When Big Data and Predictive Analytics Collide: Visual Magic Happens
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Big data is useless data unless you have a way to handle and perform meaningful analysis that drives a business outcome. Data visualization has transformed complex data sets into patterns now being used to constructed predictive models. In the massive exploding world of social data and content engagement the need for intelligent data mining and pattern prediction is required to realize data driving marketing. In this presentation, we will explore techniques, key takeaways and examples behind this fast growing market of predictive analysis.
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When Big Data and Predictive Analytics Collide: Visual Magic Happens
- 1. Insights – Analysis – Content Engineering 1 When Big Data and Predictive Analytics Collide: Visual Magic Happens
- 2. The Problem: Massive data explosion (mobile, social, wearable, cloud, m2m etc.) and brands are struggling to make use of this data. 2
- 3. 3
- 4. PREDICTIVE ANALYTICS 4 Predictive Analytics enables decision makers to predict future events and proactively act on that insight to drive better business.
- 6. THEN, NOW & WHERE WE’RE GOING 6
- 7. 7
- 8. MOST COMMON PREDICTIVE MODELS • Clustering – finding groups and predicting themes • Classification – most popular “Decision tree” • Association – multi assurance connected buckets • Link Analysis – relationships • Text Mining – unstructured data to meaning • Time Series – predicting a continuous value • Graph Structure – structure predicts behavior 8
- 9. PREDICTIVE ANALYSIS USE CASES 9
- 12. IN DATABASE PREDICTIVE ANALYTICS 12
- 13. BIG DATA VISUALIZATION & ANALYTICS 13
- 14. TABLEAU 14
- 15. NEURAL CONNECTIONS ARE LIKE A SOCIAL GRAPH A simulation of a macaque monkey's neural connections. It shows 4,000 centers of neuronal attachment, each represented as a dot along the ring, connected by more 15than 320,739 arcs.
- 16. 3.5 BILLION WEB PAGES AND 128 BILLION HYPERLINKS • Pajek and (large) network analysis and visualization. 16 http://webdatacommons.org/hyperlinkgraph/
- 18. WHERE WE’RE GOING – PATTERN PREDICTION 18
- 19. WHERE TO GO 19
- 20. KDD-Nuggets http://kdnuggets.com RapidMiner http://rapid-i.com R Statistical Computing http://www.r-project.org Revolution Analytics http://www.revolutionanalytics.com Teradata http://www.teradata.com Tableau http://tableausoftware.com Spotfire http://spotfire.tibco.com SAS http://www.sas.com IBM SPSS http://www.ib.com/software/analytics/spss Mahout https://cwiki.apahce.org/confluence/display/MAHOUT/Algor iths Weka Open Source Data mining http://www.cs.waikato.ac.nz/ml/weka Pajek and (large) network analysis and visualization. 20
- 22. 22
- 23. CONTENT MARKETING FLOW = DATA 23
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- 26. 26
- 27. We’re Here to Help You Great Social Engagement Is About Knowing what drives engagement 27 @chasemcmichael sales@infinigraph.com @infinigraph http://smo.infinigraph.com http://www.infinigraph.com YouTube /infinigraph Slideshare /infinigraph
Hinweis der Redaktion
- InfiniGraph solves a problem for marketers enveloped in massive amounts of data by enabling them to identify what is truly relevant to their customers.We simplify trend identification, enable the production of higher quality content, and empower brands to create better engagement.InfiniGraph is like the Comscore / Nielsen for engagement performance and competitive intelligence
- Companies are fighting for attention and fighting blind. Massive explosion of data as more consumer engage on content over many networks. Brands need to know what’s working what’s relevant and be shown what’s trending. They need to know more than ever what’s effective. What their target audience is finding relevant and more importantly what’s driving the consumer to act on what content that turns into sales.
- Decision making and the techniques and technologies to support and automate it will be the next competitive battleground for organizations. Those who are using business rules, data mining, analytics and optimization today are the shock troops of the next wave of business innovation Tom Davenport Competing on Analytics
- Extrapolating relationships around data and past events to create a statistical model for predicting future event. Automating the discovery of patterns and connect the dots with past, present and future
- A simulation of a macaque monkey's neural connections. It shows 4,000 centers of neuronal attachment, each represented as a dot along the ring, connected by more than 320,739 arcs.
- InfiniGraph has invested over 3 years of data organization/collection on >250K brands categorized into Industry segments. Scoring trillions of post over may content types give brands the right information to understand what’s driving engagement. This is a big deal and the historic data isn’t available unless you captured it. Brands need this level to extract the right insights InfiniGraph provides. The social graph is a mess with massive unstructured data, brands must have content scoring and analytics to measure what’s working in their industry NOT JUST THEMSELVES (what happens on your brands pages). Before you start developing a content strategy first step is brands need to know what their target audience is collectively doing and on what. Insights are automatically generated along with content curation feeds provides a brand ongoing intelligence used on every marketing initiatives. The toll creates highly strategic as well as tactical data ongoing.
- Place content where the customers are at. Example of trending content on purchase pages or company blog page.
- Everyone has a genius moment you’re just not having them every day. But around us there are continuous genius moments happening all the time. InfiniGraph taps that genius