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Forty years is a long time in analytics, and in that time much has changed. In the last four decades, analytics has become part of everyday life and helped solve some of society’s biggest challenges. From helping develop specialised medications to combatting crime networks and ensuring transport fleets are energy efficient.
Data analytics is playing an ever-increasing role in our businesses, economy, and environment. In the beginning, data analytics was used to find the solution to an existing problem. Today this approach has been turned on its head. Now we start with the data to uncover patterns, spot anomalies and predict new opportunities.
Data now informs organisations about trends and problems they never knew existed. It shapes how people interact, share information, purchase goods, and how they’re entertained and how they work. It dictates political decisions and economic cycles. Data is the raw power that helps us optimise decisions and processes to iron out inefficiencies through use of analytics. Analytics can be utterly transformative.
On the edge
For example, General Electric Transportation (GET) is a leading division in locomotive manufacturing and maintenance. It depends on the efficient running of its rail assets, with breakdowns and inefficient fuel usage threatening profits. To optimise its operations, each train has been equipped with devices that manage hundreds of data elements per second to improve operations. Analytics is then applied to the small, constrained devices that sit at the network’s edge to uncover use patterns that keep trains on track.
This ability to analyse and learn from data in transit is a game changer for all industries. Smart sensors on the production line are improving product quality by identifying faults before they happen or instantly as they occur. In turn, customer satisfaction and company competiveness are increased.
Connected devices are now generating more data than ever before. At the same time, customer demands are rising and the complexity of modern, global supply chains is growing exponentially. To stay competitive and provide the best products and services, companies require an unprecedented level of control and the ability to positively intervene at every stage of the process.
Moving at speed
Yet most are not up to the task. Any inefficient processes between capture, insight and action squander valuable opportunities for the business. It’s obvious that the static analytics approach of the past is no longer tenable. The increasing volume of sensors and the limitless possibilities for the fusion of their data has changed the conversation. Analytics now needs to be applied at the right time and in the right place, for the right level of return.
Take energy consumption as an example. A single blade on a gas turbine can generate 500GB of data per day. Wind turbines constantly identify the best angles to catch the wind, and turbine-to-turbine communications allow turbine farms to align and operate as a single, maximised unit. By using analytics, data can be used to provide a detailed view of energy consumption patterns to understand energy usage, daily spikes and workload dependencies so that we can store more energy for use when the wind is light.
The challenge is that new connected devices, the Internet of Things (IoT) and artificial intelligence (AI) put an infinite level of insight in the hands of organisations. This means that the analytics of the present and future has to become instantaneous. The ability to gather and analyse an ever-growing amount of data to deliver relevant results in real-time will become the deciding factor for whether organisations win or lose. Analytics has to move at speed and make the development of the most promising technologies possible.
When we speculate how analytics will be used in the future, it is clear we are on the edge of something revolutionary. It is old hat to think that analytics still resides in the server – it has been brought to the edge.
Yet it would be unrealistic to assume that all businesses can run their analytics on this scale. Most organisations are a complex patchwork of legacy systems and siloed data infrastructures which do not always speak to each other. Integration is a key part of the puzzle. Organisations require analytics platforms that understand the different states of play and can consolidate data from the edge to the enterprise, from the equipment in the field to the data centre and the cloud.
Unified, open and scalable
In recent years analytics has been made open and accessible. No longer the preserve of data scientists, businesses have realised considerable gains when analytics and its insight can be communicated and used at every level of the organisation. This evolution is driven by necessity. Data is growing exponentially and becoming more complex every day, and there is no organisation with a blank cheque for technology investment. In modern, complex data environments a business’s analytics has to be flexible. It must be able to adapt to infrastructure changes and the daily challenges of businesses.
For organisations and industries, it will mean they must have access to a single, unified platform that is constantly evolving. Organisations need a platform that can scale to their needs and is delivered flexibly to achieve the latest advances that allow them to solve problems and create new value. This means being cloud-native and having access to scalable, elastic processing and accessible open interfaces. This means an environment where organisations can easily log in, access data, build models, deploy results and share visualisations.
Organisations now need platforms that are open and integrated, leveraging future technologies to scale and provide instant insight through a consolidated data environment. Platforms that provide joined-up data and faster, more accurate insight will transform organisations’ decision-making and facilitate better integrated planning. Above all, they will allow business to make good on the opportunities that data offers.
