Access Usage Service Abstraction Retrieve Report Rendering Capability Service Abstraction Security and Privacy Management Requirement Standards Group Related Standards Infrastructure Security INCITS CS1 & ISO/IEC JTC 1/SC 27 ISO/IEC 15408-2009 Information technology -- Security techniques -- Evaluation criteria for IT security ISO/IEC 27010:2012 Information technology -- Security techniques -- Information security management for and inter-organizational communications ISO/IEC 27033-1:2009 Information technology -- Security techniques -- Network security ISO/IEC TR 14516:2002 Information technology -- Security techniques -- Guidelines for the use and management of Trusted Third Party services Data Privacy ISO/IEC 29100:2011 Information technology -- Security techniques -- Privacy framework Data Management, Securing data stores, Key management, and ownership of data ISO/IEC 9798:2010 Information technology -- Security techniques -- Entity authentication ISO/IEC 11770:2010 Information technology -- Security techniques -- Key management Integrity and Reactive Security ISO/IEC 27035:2011 Information technology -- Security techniques -- Information security incident management ISO/IEC 27037:2012 Information technology -- Security techniques -- Guidelines for identification, collection, acquisition and preservation of digital evidence System Management Requirement Standards Group Related Standards ? Distributed Management Task Force ISO/IEC 13187: 2011 “Information Technology – Server Management Command Line Protocol (SM CLP) Specification” ISO/IEC 17203 2011 “Open Virtualization Format”
Life Cycle Management Multi-stakeholder Collaborative Initiatives Summary The following significant gaps exist in standards to support the Big Data Reference Architecture described in this document: Support for Data Store Registry and Location services Support for a standard way to query, summarize, and retrieve data across disparate data stores ???? Features and Technology Readiness Technology Readiness Author: Dan The technological readiness for Big Data serves as metric useful in assessing both the overall maturity of a technology across all implementers as well as the readiness of a technology for broad use within an organization. Technology readiness evaluates readiness types in a manner similar to that of technology readiness in Service-Oriented Architectures (SOA). However, the scale of readiness is adapted to better mimic the growth of open source technologies, notably those which follow models similar to the Apache Software Foundation (ASF). Figure 1 provides a superimposition of the readiness scale on a widely recognized "hype curve." This ensures that organizations which have successfully evaluated and adopted aspects of SOA can apply similar processes to assessing and deploying Big Data technologies. Types of Readiness Architecture: Capabilities concerning the overall architecture of the technology and some parts of the underlying infrastructure Deployment: Capabilities concerning the architecture realization infrastructure deployment, and tools Information: Capabilities concerning information management: data models, message formats, master data management, etc. Operations, Administration and Management: Capabilities concerning post-deployment management and administration of the technology Scale of Technological Readiness Emerging Technology is largely still in research and development Access is limited to the developers of the technology Research is largely being conducted within academic or commercial laboratories Scalability of the technology is not assessed Incubating Technology is functional outside laboratory environments
As-Is Architecture IT Roadmap IT Team (Skills and Aptitude) IT Services Catalogue Bill-of-IT Vendor Strategy Below is an output example of how a template can assist stakeholders in articulating their Big Data needs: Business Conversation Value Big Data Feature Readiness Level Use Cases Actors Agility: IT needs to provide Marketing the ability respond real-time to acquiring customers Value Statement: Lower cost of acquiring new customers by ‘X’ percent by October 1st. Roadmap Feature: Business Intelligence (Real-Time BI) [Reference Architecture capabilities can also be outlined here as well.] Technology: Reference Implementation -One or more reference implementations are available -Reference implementations are usable at scale Organization: Ad Hoc -Awareness of Big Data exists -Some groups are building solutions -No Big Data plan is being followed Use Cases: #1, 3,6 Management: -On-line Marketing Officer -Revenue Officer Analyst: -Online Marketing Leads (5) Technical: Network SME Datacenter SME Infrastructure SME CRM Data SME Storage SME (TBD) End Consumer: -Online Customers -Retail Stores (TBD) Resourcing What are the types of skills, how many types of people, where should an organization start with building their Big Data team? If we can provide the types of skills, and an estimate of how many (obviously dependent on organization size), we could give organizations a starting point for building their Big Data team. Alignment with readiness indicators. Author: Dan