More than ever before, organisations are storing, processing, and extracting value from data. At the same time, the systems that support this trend are increasing in demand, as is the demand for greater speed of systems adoption and processing execution.
Organisation-wide digitisation is a contributing factor, which includes the rise of strategies seeking to take organisations into the cloud – that is, moving applications to the cloud and out of the data centre, which also holds true for big data and processing systems.
Financial return is expected to be a tangible positive by-product of these changes. Both in terms of finding new opportunities through the use of data as well as reducing corporate spend on traditional data storage solutions, viz. data centres.
The creation of data lakes is a recent phenomenon born out of these trends. These proverbial water bodies are man-made reservoirs filled with data used for a variety of purposes, from security to machine learning to predictive analytics.
Various technologies have been on the rise in order to fulfil the demands of big data and analytics. However, highly complex, heterogeneous organisations are now seeking to leverage enterprise-wide data from a variety of sources, thus encouraging agnostic technical solutions beyond the likes of Hadoop alone.
Internet of Things (IoT) data is a future endeavour for many organisations in order to expand the sources of data input from what has traditionally been entered by humans. Additionally, what might be considered ‘dark data’ – i.e. vaulted data in paper-based documents, photos, videos, and other such assets – might also be used to expand current data sources.
Self-service analytical tools have been and will continue to be in demand. Businesses will hope to seamlessly connect to a wide variety of data sources to explore and discover hidden opportunities. Achieving this will be a challenge, especially as users expect to reduce the time and complexities associated with self-service.
With self-service and the range of data sources becoming available, security will be a chief concern. Although all users may be able to use the same data, they may not all have the ability to access everything. Data users are likely to have certain access permissions, thus requiring new standards of enterprise-wide governance, policies and procedures associated with data.