Despite large amounts of data generated within the resources industry, underinvestment in information technology places resources behind other industries in handling of Big Data and gaining insights. Resource companies spend only 1% on information technology compared with the average 5-7% across other industries. This means that resource companies collect vast amounts of data but have limited view of how it can inform and improve business. In mining for example, extreme swings in variability are an everyday challenge. Mining has significant opportunities within Big Data solutions, smart data assets and data quality that can produce step change productivity improvements across operational assets. 


To date, manufacturers have been able to reduce waste and variability within their production processes, dramatically improving product quality and yield through implementation of business improvement initiatives. The key challenge for manufacturing remains as the ability to integrate data across complex and often fragmented supply chains to unlock the next opportunities in business improvement. Big Data is generated and stored from data sources across the supply chain including process control instrumentation, supply chain management systems and systems that monitor the performance of products after sale. At Data Engineering, our pioneering Advanced Business ImprovementTM solution allows us to identify and analyse process events from existing data and information assets to provide step-change productivity and operational intelligence for our Manufacturing clients. Insights from our Advanced Business ImprovementTM solution can be applied to all facets of Manufacturing processes including product design and production, product quality, sales forecasting and business process management.

Transport & Logistics

Logistics and transportation companies continue to differentiate themselves through information technology in the relentless pursuit of reducing costs and improving customer service. They must optimise goods consolidation with timeliness of delivery (customer satisfaction) in order to achieve maximum productivity whilst maintaining strong customer satisfaction.


Big data is now playing a pivot role in providing logistics and transportation companies with timely information and insights into their performance and therefore improving decision-making quality and responsiveness. Predictive analytics is becoming a common solution today to optimise vehicle routing, crew resource allocation and goods delivery attributes. Similarly, asset maintenance is also quickly becoming dependant on data to empower business leaders with the ability to assure asset reliability whilst mitigating total production losses. Data also plays a pivotal role in managing employee health and safety, by including various business rules in predictive algorithms that optimise route planning and crew resource allocation whilst factoring in employee fatigue management safety for example. Sensor driven data will continue to expand and provide business users with more information about assets in the continuous drive to improve asset predictability and therefore maximise asset utilisation and performance. Big Data deployment solutions will continue to expand across the Logistics and Transportation industry as business leaders continue to see the benefits of a data-drive enterprise. 

Retail & Trade

The future of Big Data in the Retail industry is very promising with information and operational technologies unlocking the ability to generate rapid consumer intelligence, a new strategic lever for competitive advantage. The Retail industry has some of the tightest margins and is one of the greatest beneficiaries of Big Data solutions. Data Engineering can stream and analyse vast amounts of consumer behavioural information to optimise inventory management and pricing, resulting in inventory management intelligence. This intelligence coupled with IoT technologies can be used to optimise inventory performance, through rapid pricing tactics to match predicted consumer behaviours. Data Engineering can leverage off IoT technologies to develop solutions that bolster sales and marketing strategies for a fraction of the cost of a typical marketing campaign.


Over the past decade, Healthcare has seen a dramatic increase in the amount of data generated and analysed to improve patient services and reduce costs. Digital Health is a big movement in the Healthcare industry today empowering healthcare professionals with the ability to track, manage and improve patient health and wellbeing by collaborating with digital technologies. The more advanced features of Healthcare analytics are being used to predict epidemics, cure disease, improve quality of life and avoid preventable deaths. With population and average life expectancy continuing to increase across the world, models of treatment delivery are rapidly changing, where many of the decisions behind those changes are being driven by data. Healthcare professionals appreciate the power of data in assisting to predict early detection of preventable diseases or illness, promoting more effective treatment. 

Public Administration

Big Data & Advanced analytics provides great opportunities for the public sector and government agencies, for departments to collaborate more efficiently and effectively with each other. Data enrichment opportunities exist between departments and via third party partners to improve every day decision making across all areas. Empowering Public Administration employees with quality information at their fingertips has huge benefits for citizen services including improved citizen experiences and reduction to workflow backlogs. Quality information can also significantly save on costs through productivity improvements of people and business process performance. 



The Agriculture industry is undergoing transformational change, being driven by the need for more data to help mitigate risks to yield performance. Farming today involves sensors monitoring and reporting on every asset. Autonomous harvesters, robotic drones and virtual fencing are just some of the newer technologies available to support farmers in preparing, seeding, watering and harvesting crops. All stages of the farming process are now an exact science with data controlling when and where to act to maximise yield and market performance. Data consumption is on the rise with increased need for storing and processing Big Data evident, predominantly driven by scanning technologies. Data Engineering can help Agriculture clients collect and prepare data from drone surveys for descriptive and diagnostic analytics. Vast quantities of un-prepared data can take significant time to process, where Data Engineering can provide cost-effective and reliable data preparation services. 


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