big data readiness assessment
TRANSCRIPT
P A G E 1
Big Data Readiness AssessmentV E R S I O N 1 . 2
P A G E 2
EIM goals and strategies are business-driven for the entire enterprise,
underpinned by guiding principles supported by senior management
Roles, responsibilities, structures and procedures to ensure that data assets are
under active stewardship
Processes, procedures and policies to ensure data is fit for purpose and monitored
Metadata capture, management, & manipulation
to place data in business & technical context
Proactive planning for the information lifecycle including from acquisition through manipulation, access, & use to archiving & disposal
The identification of appropriate data integration approach for business challenges e.g. ETL, P2P, EII, DV, EII or EAI
Appropriate and fit for purpose Information security processes & controls to manage & provide authorization, authentication, access & audit of information assets
Organise information to align with business & technical goals using
Enterprise, Conceptual, Logical & Physical models
Management of Data Warehouses and creation of actionable Business Intelligence to provide intelligence and analytics for business benefit
Identification, management and delivery to consuming applications of the core shared data concepts required enterprise wide
Manage diverse data sources across the organisation from transaction data
management, to data warehousing and business intelligence, to Big Data
analytics
Enterprise Information Management FrameworkDevelopment of realistic Information Management strategies to align the desired Information capabilities and services with business motivations and strategies. The information initiatives can be accelerated by use of our Reference Architecture models to understand the capabilities, and typical functional areas for each IM discipline under consideration (such as MDM, DQ, Data Integration etc.). Our Architecture Reference models contain the typical areas of functionality & capabilities observed in each IM discipline. Our EIM framework has capability & maturity models for each of the IM disciplines together with the typical processes and activities observed in mature organisational services for each.
Manage & exploit Big Data analytical approaches to yield new actionable
insights
P A G E 3
Big Data Readiness Assessment
1. IM & Enablers Maturity: The organizations IM maturity level is measured, IM processes & technology capabilities & human resource skill sets reviewed.
2. Data Governance: A strong governance program combined with a metadata management policy will help lessen or mitigate risk intrinsic in broadening the types of information accessed.
3. Data Sourcing & Access: Identify the big data sources required and the business case for each.
4. Integration & Exploitation: Determine how to gain value from, interpret and integrate the data. Big Data vs RDBMS will be assessed.
5. Data Lifecycle: Review the data retention period for each source, what should be kept long term vs passed through to help in the next step.
6. Technology Enablement & Services: What portfolio of big data services should be offered, & what are the most appropriate technology enablers
7. Transition: What is the roadmap & pragmatic transition path to accomplish your Big Data vision?
NewInsight
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Manage & exploit Big Data analytical
approaches to yield new actionable insights
What does Big Data really imply, do you need it and are you ready to exploit it?
Our Big Data readiness assessment helps organisations address these questions, determine which of the “little data” disciplines absolutely must be in place before embarking on a Big Data initiative, and what other foundational aspects must established for a project to succeed.
Information Management Maturity Assessment*Our EIM Framework has methods, principles, roles & responsibilities, and Maturity assessment models for each of the IM disciplines. Current state maturity is assessed, and a target state determined. Following a gap analysis we develop a framework for improving the IM capabilities and a prioritised realistic transition plan.Note*: IM maturity frequently varies across business areas & a first cut review assesses overall IM Maturity
IM PrinciplesData Governance
IM Planning
Data Quality
IM Lifecycle ManagementData Integration & Access
Data Models & Taxonomy
Metadata Management
Master Data Management
DW & BI
012345
21.52
1.51.521.5
1.5
1.52
44 4
3443.54
3.54
IM Maturity Assessment
Current
Target
People
Processes
Executive Sponsorship / Leadership
Technology
Compliance
Measurement
0
2
4
1.51.51.52
1.51.5
3.53.5
43.53
3
IM Enablers Maturity Assessment
Current
Target
What? Content and ArtifactsCONTENT FRAMEWORK
When and How?Current and Target Maturity
MATURITY MODEL
Who? Skills and RolesSKILLS FRAMEWORK
IM Maturity Assessment
To mature the IM Practices within the existing IT Processes, there is the need to mature people and process along
with technology
Across all of the IM disciplines key enablers exist whose maturity impacts the success of an IM
initiative.
IM maturity is a assessed across the core IM disciplines. Maturity also
includes the provision of technology to support the IM area.
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