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Altaridey Demo

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real-time stream analytics

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Altaridey Demo

  1. 1. ALTARIDEY:ALTARIDEY: Real-Time Stream ProcessingReal-Time Stream Processing Teaching machines to react
  2. 2. Real-time stream analysis for:Real-time stream analysis for: Monitoring Prediction Control
  3. 3. The Benefits of Real-TimeThe Benefits of Real-Time “Smart” data warehousing ◦ Retain raw data only around graph inflection points Real-time exploitation ◦ “Complex” alarms, etc. Dynamic Control Systems ◦ Control VoI by the best means available And many others…
  4. 4. A bit of TheoryA bit of Theory “Everything is a Control System” ◦ Basic structure: ◦ Objective is always: conserve some quantity ◦ Control systems:  Simple: thermostat, cruise control  Complex: society, language  Key to recognizing a control system is recognizing what is being controlled
  5. 5. A bit more TheoryA bit more Theory Control systems from scratch: ◦ An ab initio thermostat Generalizing: ◦ Observation of system relationships within system
  6. 6. Detect RelationshipsDetect Relationships Shazam for data: Real-time correlation: Serial correlation:
  7. 7. Relationship bank ControllerRelationship bank Controller Select the variable controlled for Use relationship graph to find variables that can control it Use response function formalism to build controller
  8. 8. Let’s automateLet’s automate Our application loop automates the process just described Dynamic control system:
  9. 9. DemoDemo “Shazam for data”, in action Relationship detector in correlated data
  10. 10. The practical sideThe practical side A cloud-based solution that lets you: ◦ Monitor (via Web/Desktop/Custom UI) ◦ Control (via API) Cutting-edge technology saves money (one server does the work of 5) Software is tuned to meet specific needs
  11. 11. Unique Features + BenefitsUnique Features + Benefits Your data streams can be anonymous to protect privacy Deals with missing data Intuitive relationship browser (via network graphs)
  12. 12. In SummaryIn Summary Automate data stream analytics at the apex of the value chain Utilize the result to predict/control Make a friend of the data avalanche!
  13. 13. www.altaridey.comwww.altaridey.com
  14. 14. Is This ML?*Is This ML?* Principle of ML: X 1000000’s ◦ Accumulation of knowledge ◦ Don’t repeat mistakes (hopefully) *Not quite
  15. 15. Case Study:Case Study: Maximize PUE in a datacenter *Maximize PUE in a datacenter * Conditions: 120 signal streams An explicit value function Google Deepmind Approach: Reinforcement learning (ML) via Neural Nets Can altaridey do well with this problem? *http://www.theverge.com/2016/7/21/12246258/google-deepmind-ai-data-center-cooling
  16. 16. Case Study, cont’dCase Study, cont’d ML (ANN) Altaridey Analogy Brain-like, cognitive Cell-like, reactive Gets smarter with age possibly no Vert Data requirements high low Advantages Very fast once trained; Real-time; system- agnostic; Disadvantages Training is system- specific and takes time Resource utilization high throughout; Dynamic control theory requires frequent maintenance of the model; “substitute speed for intelligence”

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