Big-data-related server shipments will increase from 6% of all servers shipped in Europe, Middle East and Africa (EMEA) in 2015, to 16% by 2019, and shipments are set to increase from $1 billion in 2015 to $2.7 billion by 2019.
This is according to market research firm IDC, which recently completed an in-depth market sizing of the EMEA big data infrastructure market, focusing on servers, storage, and cloud resources used for big-data-related activities.
These include value creation from merging different data sources, various analytics, log files, and metadata that help identify patterns and generate predictions.
Big data storage capacity share of new shipments is expected to reach 20 exabytes by 2019, with a value of $2.7 billion, the firm points out.
"According to our market sizing, 134 000 server units were shipped for big data purposes in 2015, and 764 petabytes of storage capacity deployed, with the majority being external storage," IDC says.
While most current big data projects are starting off in companies' own data centres, analytics workloads are increasingly being moved to the public cloud, while sensitive data needs to remain on-premises in many cases for compliance reasons, it adds.
IDC expects the public cloud infrastructure share of big data workloads in the region to increase from 13% of server shipments in 2015, to 34% by 2019, and new storage capacity deployed on public cloud infrastructure to increase from 25% of big data workloads in 2015, to 55% by 2019. Most organisations are expected to deploy some form of hybrid solution, it notes.
"Big data and analytics have risen to the top of executives' and developers' agendas as the technology has evolved and mindsets are starting to change in organisations in EMEA," says Andreas Olah, senior research analyst, European data centres and big data at IDC.
"The main challenge is not the data or its volume, but the ability to generate value from it. Many customers are still at the beginning of their journey and still don't know where to start. Others have high ambitions and clear ideas but are slowed down by increasing complexities and the lack of highly skilled data scientists and developers."
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