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Big data (Mobile BI (Challenges (Creating a roadmap, Getting started right…
Big data
Mobile BI
Kind of information provided
Push reporting
Pull reporting
Exceptions and alerts
Sharing
Top users
Senior executives
Line managers
Outside salespeople
Top information access benefits
Give executives faster and easier access to information
Easier, self-service access to data sources
Right-time data for users' roles
Top business benefits
Improved customer sales, services, and support
More efficiency and coordination in operations and business processes
Faster deployment of BI and analytics applications and services
Challenges
Creating a roadmap
Getting started right
Meeting user expectations
Design for screen size
Creating an appropriate technology architecture
Providing for security
Characteristics
Volume
Variety
Velocity
Veracity
Ethical issues
In supply chain level
Issues with downstream customers and uses of big data
Value destruction
Diminished rights
Disrespectful to someone involved
Issues with upstream sources
Quality of information
Biases in the data
Privacy issues in data collection and sharing
In industry level
Creating negative externalities
Contributing to destructive demand
Creating sustainable big data industry
Important firms
Possible leaders
Organizations with unique influence and knowledge
Providers of key products
Guidelines
Identify and communicate data stewardship practices
Differentiate data due process requirements for personal data
Quantify activity in the secondary market for big data
Institute data integrity professional or board for big data analytics
Disruption in information value chain
Involving different set of people, processes, and technologies
Greater amalgamation of technologies into platforms and processes into pipelines
Greater reliance on data scientists and analysts
Big data research opportunities for behavioral IS
Epistemological concerns
Computational social science, privacy and security, other ethical considerations
Nature of decision making, leadership, organizational culture, cognition and usability, trust and big data versus intuition, adoption, big data outcomes
Big data research opportunities for design science research
Paradigmatic considerations
Novel artifacts for prediction or description, modeling formalisms and integration artifacts
Novel IT artifacts for decision support, business process improvements and automation, big data action design research
Big data research opportunities for economics of IS
Epistemological and/or methodological concerns
Value of data, volume, and variety; cost of veracity; social media and economics of IS; impact of location and geography
Qualitifying value and impact of four Vs on decision making, value of big data IT artifacts