Cloud Analytics

Cloud Analytics:

Cloud analytics is a service model in which elements of the data analytics process are provided through a public or private cloud.

Cloud analytics applications and services are typically offered under a subscription-based or utility (pay-per-use) pricing model.

Gartner defines the six key elements of analytics as
  1. Data sources
  2. Data models 
  3. Processing applications
  4. Computing power
  5. Analytic models
  6. Sharing or storage of results
In Gartner's view, any analytics initiative “in which one or more of these elements is implemented in the cloud” qualifies as cloud analytics.

Examples of cloud analytics products and services include
  1. Hosted data warehouses
  2. Software-as-a-Service business intelligence (SaaS BI) 
  3. Cloud-based social media analytics
It provides users with a better forecasting technique to analyze and optimize the service lines and provide a higher level of accuracy.

Cloud Business Analytics Competencies:
  1. This cloud analytic service is supported by different type of competency areas.
  2. The cloud analytics strategy helps clients to achieve their business objectives faster with less risk and at a lower cost. 
  3. Another competency is business intelligence and performance management that helps to increase performance by providing accurate and on time data reporting. 
  4. The next is analytics and optimization that provides different types of modeling techniques, deep computing and simulation techniques to increase the performance. 
  5. The other competency is a content management system that includes the different service architecture, technology architecture. 
How Cloud Analytics Work?
  1. Cloud Analytics works with the combination of hardware services and middleware.
  2. The system features include the platform that provides data reporting analytics based on text mining activities and analytics techniques. 
  3. This system also takes care of storage optimization and different high performance data warehouse management techniques. 
Analytics Business Outcomes:
  1. Analytics help to get the right information as and when they are required identify how to get it and point out the right sources to get it.
  2. Analytics also helps in designing the policies faster based on the information available in the organization. 
  3. This gives the option through which the organization can increase its profit, reduce cycle time and reduce defects.

More topics from Cloud Computing to read

Cloud Computing:

EasyExamNotes.com covered following topics in these notes.

  1. Introduction to Cloud Computing
  2. Historical development of Cloud Computing 
  3. Vision of Cloud Computing
  4. Characteristics of cloud computing as per NIST
  5. Cloud computing reference model
  6. Cloud computing environments
  7. Cloud services requirements
  8. Cloud and dynamic infrastructure
  9. Cloud Adoption and rudiments
  10. Cloud application: ECG Analysis in the cloud
  11. Cloud application: Protein structure prediction
  12. Cloud application: Gene Expression Data Analysis
  13. Cloud Computing Architecture
  14. IaaS
  15. PaaS
  16. SaaS
  17. Types of Clouds
  18. Cloud Interoperability & Standards
  19. Scalability and Fault Tolerance
  20. Cloud Ecosystem
  21. Cloud Business Process Management
  22. Cloud Service Management
  23. Cloud Analytics
  24. Testing Under Control
  25. Virtual Desktop Infrastructure
  26. Cloud Resiliency
  27. Cloud Provisioning
  28. Asset management
  29. Concepts of Map reduce
  30. Cloud Governance
  31. High Availability and Disaster Recovery
  32. Virtualization in cloud computing
  33. Server virtualization
  34. Hypervisor management software
  35. Third Party Cloud Services
  36. Case Study: Google App Engine
  37. Case Study: Microsoft Azure
  38. Case Study: Hadoop
  39. Case Study: Amazon
  40. Case Study: Aneka

A list of Video lectures

References:

  1. Buyya, Selvi ,” Mastering Cloud Computing “,TMH Pub
  2. Krutz , Vines, “Cloud Security “ , Wiley Pub
  3. Velte, “Cloud Computing- A Practical Approach” ,TMH Pub
  4. Sosinsky, “ Cloud Computing” , Wiley Pub
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Java Programming ↓ 👆
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Principles of Programming Languages
EasyExamNotes.com covered following topics in these notes.

Practicals:
Previous years solved papers:
A list of Video lectures References:
  1. Sebesta,”Concept of programming Language”, Pearson Edu 
  2. Louden, “Programming Languages: Principles & Practices” , Cengage Learning 
  3. Tucker, “Programming Languages: Principles and paradigms “, Tata McGraw –Hill. 
  4. E Horowitz, "Programming Languages", 2nd Edition, Addison Wesley

    Computer Organization and Architecture ↓ 👆

    Computer Organization and Architecture 

    EasyExamNotes.com covered following topics in these notes.

    1. Structure of desktop computers
    2. Logic gates
    3. Register organization
    4. Bus structure
    5. Addressing modes
    6. Register transfer language
    7. Direct mapping numericals
    8. Register in Assembly Language Programming
    9. Arrays in Assembly Language Programming

    References:

    1. William stalling ,“Computer Architecture and Organization” PHI
    2. Morris Mano , “Computer System Organization ”PHI

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    Computer Network

    EasyExamNotes.com covered following topics in these notes.
    1. Data Link Layer
    2. Framing
    3. Byte count framing method
    4. Flag bytes with byte stuffing framing method
    5. Flag bits with bit stuffing framing method
    6. Physical layer coding violations framing method
    7. Error control in data link layer
    8. Stop and Wait scheme
    9. Sliding Window Protocol
    10. One bit sliding window protocol
    11. A protocol Using Go-Back-N
    12. Selective repeat protocol
    13. Application layer
    References:
    1. Andrew S. Tanenbaum, David J. Wetherall, “Computer Networks” Pearson Education.
    2. Douglas E Comer, “Internetworking with TCP/IP Principles, Protocols, And Architecture",Pearson Education
    3. KavehPahlavan, Prashant Krishnamurthy, “Networking Fundamentals”, Wiley Publication.
    4. Ying-Dar Lin, Ren-Hung Hwang, Fred Baker, “Computer Networks: An Open Source Approach”, McGraw Hill.