Businesses constantly evolve and highly competitive environments are pushing them towards more effective and rapid decisions that are necessary to reflect emerging threats and safeguard sustainability and prosperity. Data and information are key assets that could be used to arrive to evidence-based and more informed judgments and try to simulate impacts of important decisions, while one should not neglect that any kind of decision has a direct or indirect impact on other business decisions that may be required either later, or in parallel.
Today, the abundance of data coming from various sources has triggered the realisation of completely new types and methods for taking decisions and for conducting business analysis. It is the same abundance that calls for new means of processing and analysis. The complexity of today’s business operations, the flexible and constantly changing business ecosystems and the pathways towards big data characterise the transformation of raw data into knowledge and intelligence as a very difficult process. Moreover, this quest becomes even more difficult when it concerns the analysis of real-time data, coming from different sources (either machines or even humans) and that needs to be provided in a personalised and comprehensive way to each recipient, regardless of the devices and the infrastructure s/he is using.
It is indicative that, according to Gartner, the worldwide business intelligence and analytics market was 18.8 billion dollars by the end of 2013. Along the same lines, a report from Salesforce claims that by adding new apps in analytics, the same market is projected to increase its Total Addressable Market (TAM) to 82 billion dollars for calendar year 2018, fueling an 11% Compound Annual Growth Rate in their total addressable market from 2013 to 2018.
In the next few years, thanks to smart devices, and to the unparalleled deployment of sensor grids and the progress in IoT technology, enterprises will be in a position to collect enormous amounts of data, and will possess raw business knowledge that could be turned into intelligence in a credible manner. Enterprise data will be delivered in real-time and in huge amounts, and new novel approaches for appropriately extracting the meaningful part of it would be necessary, while data transfer would also require next generation network infrastructures.
This will be made possible by the power of next generation cloud computing, the progress in data analytics algorithms and the application of new, interactive and personalised visualisation methods, which could be used to transform the knowledge collected both from within the boundaries of the enterprise and from the outside operational environment.
The intelligence to be generated through these processes would reach the proper recipients in a personalised manner, in order to allow them to focus on the part that is really needed and meaningful to them, without getting distracted by noise. Wearables and mobile devices are key in this direction, as they allow the delivery of data at the right time and at the right place. Moreover, through the use of such devices, every decision taken based on the intelligence required will be fed back to the system in order to cross-analyse the various implications that could emerge and to generate new pieces of intelligence that should be taken into consideration for the next steps.
As such, the construction of a pervasive, intelligent, proactive but also rapidly responding and user-friendly business environment that will constantly assess the various factors that affect the operation of an enterprise and will constantly push intelligence (and not just information) to its stakeholders, in a personalised manner becomes of the utmost importance. This will allow enterprises to grasp a better understanding of their operational environment and of their own performance, identifying strong and weak points, and emerging opportunities and threats that should be constantly considered and tackled in order to become context-aware and responsive to the best possible extent.
As the European Big Data Value Partnership reports in its Strategic Research and Innovation Agenda, a more efficient use of Big Data, and understanding data as an economic asset, carries great potential for the EU economy and society. The setup of Big Data Value ecosystems and the development of appropriate business models on top of a strong Big Data Value chain must be supported in order to generate the desired impact on the economy and employment.There are specific smaller-scale challenges that should be addressed in the upcoming years in order to facilitate the envisioned developments:
- Multi-source Data Analytics Services for Real-Time Business Critical Decisions.
- Predictive and Prescriptive Crowd-based Analytics powering Business Innovations.
- Human Intelligence and Machine Information Flows’ Blending Platforms.
- Smart and Personalised Intelligence delivery systems.
- Shared Anonymised SMEs Analytics over federated cloud-based platforms.
- Smart and Collaborative APIs for cognisant business processes.
- Responsive and Dynamic Visualisation and Augmented Reality Services for Business Functions.