Big Data has achieved rapid adoption in the large corporate world, as evidenced by participants in the NewVantage Partners 2013 Big Data Executive Survey, which was published on September 9, 2013.
“Big Data differs from traditional approaches in the quantum leap in
affordability, scale, and variety of analytics it can support.”
The value of improved data and analytics is not new to most businesses. Organizations have been utilizing data and analytics for several decades in a quest to gain insight, identify correlations, and provide decision makers with timely answers to critical business questions.
Big Data differs from traditional approaches in the quantum leap in affordability, scale, and variety of analytics it can support. This leap lowers the “transaction cost” of using analytics and data, providing ready access to data and insights across the corporation.
Companies are radically expanding the scope, scale, and impact of data and analytics in their day-to-day business processes and decision-making, realizing the power of their information assets.
Fortune 1000 enterprises are implementing Big Data solutions and capabilities to:
- Transform the speed at which companies are turning data into value, by accelerating the Time-to-Answer (TTA) for critical business questions
- Reduce the costs of traditional business processing, by migrating processes from traditional high-cost platforms to low-cost Big Data platforms to maximize process efficiency
- Accelerate speed-to-market by transforming core business processes used to produce and deliver products and services, such as client on-boarding, fraud detection, anti-money laundering, threat identification, dynamic pricing, client and fiduciary reporting, market risk models, portfolio valuations
- Innovate through rapid exploration and discovery, such as cost-reduction through transparency and rationalization of critical business processes.
How NewVantage Partners Can Help
Our focus is on helping our clients mitigate the risk of Big Data strategic business and technology initiatives — from up-front planning and design, alignment of business drivers and technology capabilities, and organizational readiness — through successful execution, implementation, and business adoption. Our Big Data expertise includes:
Vision | Strategy | Governance | Adoption
- Understand capability and readiness – information maturity and culture change
- Align Big Data to the business model – value levers | usage scenarios | priorities
- Develop the Big Data strategy — approach | roadmap | implementation plan
- Design a governance model and detailed operating model
Data Management | Architecture | Technology
- Assess current architecture and technologies
- Identify technology fit for Big Data implementation with a detailed evaluation model
- Detail design drivers, criterion, principles and architecture of Big Data and the coexistence model with existing enterprise technology investments and standards
- Detail information provisioning and distribution architecture at the departmental and organizational level [information integration architecture]
- Detail architecture for integration of streaming information
- Assess non-functional needs and the capability and capacity to meet them
Enterprise | Integration | Business Process Optimization | Business Architecture
- Integrate sources of structured, unstructured and semi-structured content inside and outside enterprise boundaries that fits business model
- Ensure architecture aligns well to integrate, store, process, retrieve and analyze content
- Include event processing and business processes that interact with content to support deep analytics
- Design and integrate meta data, taxonomies, classification, ontologies for information exploration, discovery, access and retrieval
- Define a framework for collaborative analytics modeling that aligns with lines of business’ needs
- User and business friendly tools, technologies and user interfaces selection, design and implementation
- Integration of hard and soft data for Deep Analytics
- Ensure the integration architecture can integrate with real time decision applications, event engines and business processes to deliver deep analytics from Big Data
- Ensure the architecture supports historical retention of models and meta data