Computing Big Data Review 2016
This year's review looks at the extent of big data rollouts, organisational success factors and data scientists
Computing Big Data Review 2016
Learning from the leaders
Key highlights from the research include:
- Organisations consisting of 5,000 employees or more are at the forefront of big data analytics.
- Leading industries are telecoms, business services, finance and media. Large organisations in these industries are by far the most likely to be analysing external data as well as internal operational data.
- Leaders are more likely to emphasise the identification of new opportunities and competitive edge, whereas less advanced practitioners are more likely to focus on operational efficiencies.
- The integration of data from multiple sources is of primary importance when evaluating analytics tools.
- Established technologies such as Hadoop dominate present deployments but advanced organisations are more likely to be evaluating platforms such as Apache
- Spark which combine real-time and batch analytics.
- A yawning skills gap in big data talent exists which is acting as a brake on faster growth. Skills such as those possessed by data scientists are expensive and often perceived to be difficult to lure from those businesses at the front of the big data race.
- The volume of data is expected have the greatest impact on their organisations in the short to medium term, rather than variety and velocity, and the Internet of Things (IoT) is expected to be the source of much of this new data. The impact of technologies such as machine learning and artificial intelligence is expected to be felt in the longer term.