Analytics current and future
The survey also studies different types of business functions that advanced analysis is currently supporting and is expected to support in the future.
The top business functions that are currently performing advanced analytics, like business reporting (71.9%), planning and forecasting (56.8%) and budgeting (53.5%), are ranked much lower for future advanced analytics performance.
The survey indicates current analytics are predominately used to perform operational roles. More strategic business functions, like strategy management (64.8%), profit modeling (58.7%), business performance management (58.6%) and R&D (58.3%), are expected to dominate the use of advanced analytics in the future.
The finding suggests Hong Kong enterprises understand the strategic value of big data analytics. Advanced analytics are expected to move from business operations support to a more strategic role. With larger volumes and increased variety of data captured, and analytical models advancing, organizations expect to reply on big data analysis for strategic business decisions.
Speed still matters
Although data-analytics speed is rated lowest (Figure 2), performance appears to be an issue for local enterprises.
The study asked IT users about optimal timeframes for results from analytical queries. While most IT users (42.1%) could wait for a minute for the result, more than one-third (37.3%) expect analytical results to be available in less than 10 seconds, in order to satisfy business needs.
The finding suggests demand for speed and volume together will put stress on IT departments and processes. If the data architecture and IT infrastructure aren't ready to process 100TB of data for advanced analytics in under 10 seconds, some users may they find that unacceptable.
The survey's results indicate a majority of IT users are concerned (58.5%) with their current state of information infrastructure to adopt big data. Lack of confidence in data architecture and IT infrastructure are major concerns for Hong Kong enterprises—without such confidence, big data adoption will be slow in coming.
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