Technical barriers include a broad range of issues involving the hardware and software involved in Big Data systems. These issues affect every part of the Big Data system, as represented by the components and fabrics of the NBDRA. The provides detailed discussion of the NBDRA and it NBDIF: Volume 6, Reference Architecture functional components. Technical barriers have been identified in the literature, some which are summarized in Table 5. The amount of survey respondents that cited a particular barrier are expressed as a percentage in the table. Table 5: Technical Barriers to Adoption Technical Barriers Aggregate Surveys Category CDW Accenture Knowledgent Hitachi TDWI Information Week Subcategory Reduced performance during concurrent usage Integration problems with 35% 35% existing infrastructure Moving data from source to analytics environment NRT 45% Blending internal & external data; merging sources Organization-wide view of data movement between apps Moving data between systems and clouds Hadoop data Hadoop specific Backup and recovery Availability Performance at scale 27% Lack of user friendly tools 50% 29% Security Compliance, privacy, and 42% regulatory concerns S&P securing deployments from hack S&P inability to mask, sensitive data S&P lack of fine control to support hetero user population Governance: auditing access; logging / tracking data lineage Analytics layer technical misspecifications Lack of suitable software 42% Lack of metadata management 25% 28% Difficulty providing end users 33%
Technical barriers include a broad range of issues involving the hardware and software involved in Big Data systems. These issues affect every part of the Big Data system, as represented by the components and fabrics of the NBDRA. The NBDIF: Volume 6, Reference Architecture provides detailed discussion of the NBDRA and it functional components. Technical barriers have been identified in the literature, some which are summarized in Table 5. The amount of survey respondents that cited a particular barrier are expressed as a percentage in the table. Table 5: Technical Barriers to Adoption Technical Barriers Aggregate Surveys Category Subcategory CDW Accenture Knowledgent Hitachi TDWI Information Week Reduced performance during concurrent usage Integration problems with existing infrastructure 35% 35% Moving data from source to analytics environment NRT Blending internal & external data; merging sources 45% Organization-wide view of data movement between apps Moving data between systems and clouds Hadoop data Hadoop specific Backup and recovery Availability Performance at scale Lack of user friendly tools 27% Security 50% 29% Compliance, privacy, and regulatory concerns 42% S&P securing deployments from hack S&P inability to mask, sensitive data S&P lack of fine control to support hetero user population Governance: auditing access; logging / tracking data lineage Analytics layer technical misspecifications Lack of suitable software 42% Lack of metadata management 25% 28% Difficulty providing end users 33%