Big Data and Advanced Analytics: A Lasting Investment
These days, there’s hardly a business that isn’t considering the challenges of Big Data and Advanced Analytics. Whatever their size, whatever their sector, they have all realised that hidden away in their data there is enormous potential for improvements in efficiency and new revenue opportunities. But after the initial stages of breakthrough and proof-of-concept test runs, the time has come to look at the longer term: enterprises are now thinking about the structures they need to put in place to keep moving forward and make the most of their data on a permanent basis.
What’s clear is that Big Data and Advanced Analytics are here to stay. Despite apparently recent arrival, it’s just another step on a path that began long time ago with Business Intelligence (BI) and aims to continually improve how the enterprise operates by utilising the available information. BI, with its dashboards, shed light on the past but left it to human intuition when it came to drawing conclusions about the future. With Advanced Analytics , the science of prediction has superseded mere description, with the ability to identify weak signals and hidden explanations. And as systems become ever more powerful and increase our knowledge, the need forprescriptive analytics is emerging, which will provide direct assistance and practical decision support, as well as cognitive analytics, which will enable even more advanced automation. This is not only a technological roadmap, but it is also about how organisations are becoming increasingly mature in their ability to organize themselves around data. So, although we may be only at the beginning, it’s obvious that those who advance the fastest will reap a significant competitive advantage.
Nevertheless, feedback from early Big Data & Advanced Analytics projects already hints at the challenges looming on the horizon which call for a flexible framework to allow agile business implementation. Firstly, the constantly changing nature of data (be it in volumes, in diversity from different sources)as well as a growing demand for real-time analytics capabilities. Secondly, the relative lack of expert resources, with good Data Scientists having long been a rare and expensive commodity in the face of increasing demands. And thirdly, the already noticeable risk of silos between use case implementation reappearing and the resulting inefficiencies.
In the same way that digital technology calls for specific organizational and operational provisions (Cloud, DevOps, etc.), Big Data requires appropriate responses to anticipate and overcome these pitfalls and ensure that investments in it are sustainable. That means rapidly establishing an industrialised approach, that draws together an organisation’s initial Big Data projects to optimise cost control, rationalise resources and capitalise on experience.
To achieve this without restricting the room for manoeuvre that is essential to the business, the solution lies in the orchestration and close co-ordination of four dimensions which make the Atos Codex Solution:.
- Firstly, upstream, consulting teams that can engage with the business to rapidly identify and qualify effective business use cases using proven methodologies.
- Then comes what we at Atos call the ‘Codex Design Labs’: teams and tools that enable you to rapidly design, qualify and calibrate prototypes to validate these use cases.
- After that, it’s time to go into production with the rapid implementation of a multi-purpose analytical platform that is compatible with various computing environments, including private or public clouds, and is responsible for collecting, formatting, processing and presenting data (managed by the IT Department, it is the foundation stone of industrialisation). This is where Atos Codex Analytics Platform comes into play
- Finally, let’s not forget the underlying infrastructure, which provides the necessary performance (even up to High-Performance Computing levels if the amount of data or complexity require it), underpins the effective operation of the source systems and guarantees security.
It is this philosophy of vertical integration that Atos uses in its Atos Codex solution, to ensure that Big Data and Advanced Analytics is not just a series of disjointed initiatives within an organisation, but rather a sustainable and concerted strategy for value creation. Founded on the belief that Big Data & Advanced Analytics supports a long-term strategy, this approach is not only facilitating today’s projects – by promoting the emergence and implementation of use cases – but also those of tomorrow, creating the conditions for industrialisation and future capitalisation. By using Atos Codex, the enterprise is making a genuine long-term investment in Big Data while also speeding up its route to optimum exploitation of all the data it can access.