Big Data analytics in the Cloud Ahmed Alhanaei

What is Cloud computing?  Cloud computing is Internet-based computing, whereby shared resources, software and information are provided to computers and other devices on-demand, like the electricity grid

Different models for Cloud service  Architecture models  Infrastructure as a Service (IaaS)  Platform as a Service (PaaS)  Software as a Service (SaaS)  Deployment models  Private Cloud  Public Cloud  Hybrid Cloud

Cloud deployment models Managed ByOwned ByLocated atShared by PublicThird Party Provider Third Party provider ExternalMultiple tenants PrivateOrganizationOrganization or third party Internal and external Single tenant HybridOrganization and third party Organization or third party Internal and external Single and multiple tenants

Advantages of using the Cloud  Scalability  Cost Efficiency  Easy System deployment

Challenges in the Cloud  Security and Privacy  SLA management  Service Quality

What is Big Data Analytics  Big data refers to the huge data sets that are orders of magnitude larger ( volume ); more diverse, including structured, semi-structured, and unstructured data ( variety ); and arriving faster ( velocity ) than you or your organization has had to deal with before. This flood of data is generated by connected devices. So called the 3V of Big Data  Big data analytics is a set of advanced technologies designed to work with large volumes of heterogeneous data, using sophisticated quantitative methods such as machine learning, neural networks, and artificial intelligence to explore to discover interrelationships and patterns.

Big Data analytics and cloud computing  Introducing the Big Data as a Service (BDaaS)  Unlocking the Potential of Big Data in Clouds  Clouds offer flexibility and efficiencies  Cost effective solution  Easy deployment

What is Big Data as a Service (BDaaS) ?  Big data as a service (BDaaS) is a term typically used to refer to services that offer analysis of large or complex data sets, usually over the Internet, as cloud hosted service.  BDaaS stands for two things:  A highly functional ‘Service-oriented’ data architecture  The instantaneous growth/promise of Cloud virtualization

BDaaS Framework

BDaaS Business models

Core BDaaS (PaaS)  Considerably generic and uses infrastructures such as Hadoop, Google’s Map Reduce, Spark or individually written Java-scripts  Combines this basic infrastructure with storage applications  Example: Amazon’s Elastic MapReduce (EMR)  EMR integrates well with many of the other services like the NoSQL store DynamoDB or S3 storage

BDaaS Business models

Performance BDaaS (IaaS+PaaS)  Database ecosystem with optimized infrastructure  Focused on helping companies already working with Hadoop to streamline their infrastructure and optimize Hadoop performance  Suitable for companies building their own data architecture and related SaaS layer  Example: Altiscale

BDaaS Business models

Feature BDaaS (PaaS+SaaS)  Database ecosystem with features for productivity and exchangeable infrastructure  For organizations that require additional features that go beyond those offered in the common Hadoop ecosystem  Example: Qubole which supports already Amazon and Google’s IaaS

BDaaS Business models

Integrated BDaaS (IaaS + PaaS + SaaS)  Comprise out of both Performance and Feature BDaaS  Allow maximum performance while supporting business owners  Example BigML

Tips for selecting BDaaS  Understand your business needs and capabilities  Data governance should be in place  Start small when using a BDaaS and grow from there  Clearly understand what is and what is not the responsibility of the provide

Infrastructure as a Service (IaaS) Providers  Amazon Web Services  Citrix CloudPlatform  Windows Azure  OpenStack software  Rackspace  Savvis  Verizon Terremark  VMware vCloud Suite  Google

Platform as a Service (PaaS) Providers  Force.com  Google App Engine  Red Hat OpenShift  VMware Cloud Foundry  Windows Azure

Software as a Service (SaaS) Providers  Cetas by VMWare analytics solutions  Google BigQuery services  Rackspace Hadoop service  Windows Azure HDInsight

Thank you