Big Data Drives Big Demand for Storage, IDC Says
As demand for Big Data technology and services continues to escalate, all levels of the Big Data technology stack will experience significant growth. Storage is a critical piece of the infrastructure component, increasing at a compound annual growth rate (CAGR) of 53% between 2011 and 2016.
International Data Corporation (IDC) has just published two in-depth studies - Storage for Big Data: Insight Into Usage Patterns (IDC #240372) and Influencers in Deployment of Storage for Big Data (IDC #240451) - built on findings from its first-ever survey on storage infrastructure for Big Data and analytics (BD&A).
The amount of data generated, processed, and stored by most organizations will continue to grow aggressively for the foreseeable future. "Storage will be one of the biggest areas of infrastructure spending for Big Data and analytics environments over the forecast period," said Ashish Nadkarni, Research Director, Storage Systems. "Revenue from storage consumed by BD&A environments will increase from a mere $379.9 million in 2011 to nearly $6 billion in 2016. This growth will come largely from capacity-optimized systems (including dense enclosures), however, software-based distributed storage systems with internal disks to store post-processed data will also be embraced by some users."
Additionally, businesses will continue to tap into newer data sources as they move their analytics efforts from search to discovery. This shift will accelerate spending on Infrastructure and data organization platforms will continue to accelerate
Storage for Big Data: Insight Into Usage Patterns
This IDC study assesses the results of IDC's Big Data Survey, conducted in the first calendar quarter of 2013, regarding trends in storage. Storage is a tremendously important subsystem that can determine the success of a Big Data and analytics implementation. Capacity growth and application performance continue to be the top challenges facing organizations of all sizes as they relate to how storage is attached to Big Data and analytics environments.
-- Performance was cited as the primary driver for selecting storage architecture among 68.6% of respondents. Another 59.5% indicated cost as a primary driver (multiple responses were allowed).
-- Just under 31% of respondents said they had no deployment of enterprise storage systems for data analytics infrastructure, but plan to start deploying in the next six months.
-- The type of converged infrastructure deployed for Big Data infrastructure was split almost evenly between discrete converged infrastructure (30.1%), Compustorage (29.4%), and Neither, we have done the integration in-house (28.4%).
Influencers in Deployment of Storage for Big Data
This IDC study examines some of the qualitative and "behind the scenes" challenges faced by businesses with their Big Data infrastructure — either during or after deployment. Businesses will continue to struggle with what data to analyze, how to store data before and after it is analyzed, and how to feed the results of data analysis back into the business.
-- Analysis of operations-related data was cited by 63.7% of respondents as the primary use case for deploying data analytics infrastructure. Analysis of transactional data from sales or point-of-sale systems was cited by 53.3% of respondents.
-- IT was by far the greatest influencer of data analytics infrastructure. Operations was a distant second.
-- Improving customer satisfaction is the greatest business challenge to be solved with data analytics deployments, according to just over 61% of respondents.
The amount of data generated, processed, and stored by most organizations will continue to grow aggressively for the foreseeable future. "Storage will be one of the biggest areas of infrastructure spending for Big Data and analytics environments over the forecast period," said Ashish Nadkarni, Research Director, Storage Systems. "Revenue from storage consumed by BD&A environments will increase from a mere $379.9 million in 2011 to nearly $6 billion in 2016. This growth will come largely from capacity-optimized systems (including dense enclosures), however, software-based distributed storage systems with internal disks to store post-processed data will also be embraced by some users."
Additionally, businesses will continue to tap into newer data sources as they move their analytics efforts from search to discovery. This shift will accelerate spending on Infrastructure and data organization platforms will continue to accelerate
Storage for Big Data: Insight Into Usage Patterns
This IDC study assesses the results of IDC's Big Data Survey, conducted in the first calendar quarter of 2013, regarding trends in storage. Storage is a tremendously important subsystem that can determine the success of a Big Data and analytics implementation. Capacity growth and application performance continue to be the top challenges facing organizations of all sizes as they relate to how storage is attached to Big Data and analytics environments.
-- Performance was cited as the primary driver for selecting storage architecture among 68.6% of respondents. Another 59.5% indicated cost as a primary driver (multiple responses were allowed).
-- Just under 31% of respondents said they had no deployment of enterprise storage systems for data analytics infrastructure, but plan to start deploying in the next six months.
-- The type of converged infrastructure deployed for Big Data infrastructure was split almost evenly between discrete converged infrastructure (30.1%), Compustorage (29.4%), and Neither, we have done the integration in-house (28.4%).
Influencers in Deployment of Storage for Big Data
This IDC study examines some of the qualitative and "behind the scenes" challenges faced by businesses with their Big Data infrastructure — either during or after deployment. Businesses will continue to struggle with what data to analyze, how to store data before and after it is analyzed, and how to feed the results of data analysis back into the business.
-- Analysis of operations-related data was cited by 63.7% of respondents as the primary use case for deploying data analytics infrastructure. Analysis of transactional data from sales or point-of-sale systems was cited by 53.3% of respondents.
-- IT was by far the greatest influencer of data analytics infrastructure. Operations was a distant second.
-- Improving customer satisfaction is the greatest business challenge to be solved with data analytics deployments, according to just over 61% of respondents.
