Predictive Maintenance in Software Systems Using AI
Date: 13/11/24
By: Krzysztof Lewczuk
The ‘power crunch’ of 2022 has put the West’s continued reliance on fossil fuels under the microscope, making the race to find and commission alternative energy sources more urgent than ever before. But that’s only half the picture: without accessible real-time data and advanced analytics it’s hard to trade competitively, given the intrinsic volatility of renewables and the number of variables at play. Being a data driven organisation is fast becoming a base line requirement for survival. What does this really mean and how can you make it a reality?
Company decision makers know that managing and understanding data is key to running a successful business. Data is no longer viewed as a cost and of low priority.
For some time, company CIOs have been beating at the Boardroom doors to get budget to properly organise their companies’ data, however this has always been seen as a cost, and something more important always seemed to supersede data in the priority stakes.
Many years of this kind of thinking have compounded the issues, with the resultant legacy of myriad intertwined systems running on top of disorganised, disconnected, and unfit for business data pools.
At last, company boards are beginning to understand that it’s the data that counts, and finally companies are investing in data architectures to optimise and build their businesses for future growth. Data really is the beating heart of the business.
Global initiatives such as the drive to net zero and the challenges of the current ‘power crunch’ have made this move to data even more important, and especially so in companies that have had to react swiftly to these world events such as Energy and Commodity Trading companies. The biggest challenge is data and gaining maximum value from it.
Data-driven approaches may be the norm for some parts of an organisation, but there is some way to go before data is embedded in nearly all processes, decisions and employee interactions. A data driven culture means that the business, nearly all of the time, relies on hard evidence to drive it forwards. It supports a goal of continuous improvement and productivity that gives competitive edge as well as superior employee and client experience.
Data driven transformation requires creation of a single view of the truth – a unified view of data with the right data architecture in support of it as well as the skills to build it. Team capabilities in relational databases, data lakes, data mesh and Lambda and Kappa architecture can be trained or hired, bearing in mind the opportunities for skills transfer with the latter approach.
The limitations of legacy technology structures can inhibit data from being processed and analysed in real time. However, building modern data architectures means benefiting from the power of advanced analytics, and for energy trading this is transforming the competitive landscape.
As markets become closer to real time, traders need to keep a competitive edge, maintaining or increasing margins through the availability and accessibility of market data. Weather data, satellite, vessel tracking and predictive analytics being some of the variables to inform trades.
For intra-day power trading, achieving real time data agility is the difference between profitability and exposure to risk of income shortfalls.
Digiterre worked in close partnership with Uniper’s Market Analytics and Data Management teams to develop the new Market Data Analytics Platform (MDAP) with the aim of creating a step change in the speed and quality of data analysis and reporting for the company’s traders and analysts. This kept Uniper’s energy trading business well ahead of the competition in volatile markets.
The main goals of the project were to:
Amongst the main benefits of getting their data strategy right included a 30% reduction in operational costs, so real, tangible business benefits. This in parallel with the systems 10x performance improvements from cutting edge technology choices. (Read the full case study here)
Becoming data-driven requires transformation to take place. At Digiterre, our view is that transformation happens at the intersection of technology, data and culture and it’s this multi-disciplinary and complex challenge that we have become best known for solving for our clients.
With the current global uncertainty, accessing real time data is even more important to manage hour by hour volatility, not to mention the longer term aims of moving towards net zero.
If you would like to find out more about our data engineering work and how we can help you solve your data transformation problems, and to hear how we’ve worked with our clients to solve theirs, please get in touch.
Date: 13/11/24
By: Krzysztof Lewczuk
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If you would like to find out more, or want to discuss your current challenges with one of the team, please get in touch.