Agenda © 2015 | Tel: (980) | Big Data: Types of data and benefits Implementation Challenges / Risks Tools & Platforms Landscape BD Implementation: Cloud Deployment & Service Models Piloting a BD project Implementation Models Risk Assessment/Audits

Types of data used in BD projects © 2015 | Tel: (980) | Customer data collected by the company (addresses, purchasing history, etc.) Transaction data collected by the company (POS data) Externally collected financial data (competitive intelligence) Supply chain/inventory data (sensor data, product tracking, etc.) Inputs from customer service interaction (web, call logs) Demographic or other third party supplied data (Census, social media, etc.)

Big Data benefits © 2015 | Tel: (980) | Improving insights about our customers Improved decision making Competitive advantage Innovation/Service creation Controlling and reducing operating costs Productivity Shorten time to market for product/service It could replace human /support human decision making with automated algorithms

Big Data Implementation Challenges © 2015 | Tel: (980) | Lack of management support Limited Budget Legacy Issues Difficulty integrating initiatives surrounding unstructured data Poor data quality Difficulty uncovering actionable insights/inadequate reporting Escalating infrastructure and maintenance costs due to data growth

Big Data Implementation Challenges © 2015 | Tel: (980) | Limited availability of skilled employees to manage big data Development time Regulatory, compliance, privacy issues Security issues Ownership/control issues Ability to demonstrate ROI from investments Difficulty integrating or analyzing real-time data Access and usability for end users Growing demand on storage capacity/infrastructure Scalability issues

Big Data Tools & Platforms Landscape © 2015 | Tel: (980) |

BD Implementation: Cloud Deployment Models © 2015 | Tel: (980) | Public Convenient (easy to set up, use and access) Pay per use No long term contracts Less secure Scalability is the driving factor Private More secure, clouds are not shared Reliability—existence of SLAs Costly Requires in house IT skills Hybrid Mix model—choose elements from private and public Balance of convenience and security

BD Implementation: Cloud Service Models © 2015 | Tel: (980) | Software-as-a- service Application Operating System InfrastructureNetwork Platform-as-a- service Operating System InfrastructureNetwork Infrastructure- as-a-service InfrastructureNetwork Salesforce CRM, Google Drive, Google Calendar Google App Engine, Microsoft Azure Amazon EC2, Microsoft, VMWare, Rackspace

Piloting a Big Data project © 2015 | Tel: (980) | Understand big data Ensure management buy-in (and define ROI) Create a roadmap- milestones, deliverables, timeline, action items, best practices Gaps/Priorities- list gaps, current data available, list data owners, priority list, guidelines, etc. Whose and where to ease the pain Create a multi-disciplinary team- project sponsor, stakeholders, PM, IT teams, Testing team, etc. (hire and grown your BD team) Define criteria- identity 5-10 potential use cases for the pilot Prioritize 1-3 use cases for the pilot Select Proof of Concept - start the pilot on the cloud or choose an in-house infrastructure model Implement preferred alternative Document key findings and share the results & organize a workshop to educate the broader audience Integrate with existing IT Lookout for new tools and efficient technologies Repeat: Expand the team and start new projects

Big Data Risk Assessment / Audits © 2015 | Tel: (980) | Data & Computation Integrity Regulatory, Legal and Compliance Access and Security Confidentiality and Privacy