Data Engineering

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With a solutions oriented service model and business improvement spirit, each and every one of our solutions have been designed with step change productivity and sustainable value in mind

"40% of business initiatives fail to achieve targeted benefits because of bad data” – Gartner, 2013

data quality


Just as we safely assume that the process of manufacturing soft drinks, or any food or beverage product for that matter, has passed rigorous quality checks before it arrives on retailer shelves, can the same be said for business users who continue to use data without much thought of data quality? The short answer is no, not in 2016 at least. With 46.2% of businesses in 2016 indicating that their data quality is “fair” and that data quality “still has a long way to go”, this should raise eyebrows for all business decision makers out there, especially those making strategic level decisions where even slight inaccuracies can translate to major losses later on. With expectations of business activities today requiring data to drive decision making, it is extremely important for business leaders to understand the criticality of data quality and the value in data quality management. What you think you know about your business including customers, suppliers and operation will likely be distorted by poor quality data and the continuous use of poor quality data will have detrimental impacts on business performance.


Gartner forecasts 6.4 billion connected things will be in use worldwide for 2016 with projections of 20.8 billion connected things by 2020. Is your business ready for the Internet of Things?

data quality


As data requirements continue to grow exponentially, so too does the pressure on your existing IT storage and processing infrastructure. For businesses today that still solely rely on EDW schema based IT infrastructure, on average these setups process 8% of the total data created. Just imagine the potential of processing even double this number let alone the full 100%! With the added load from emerging markets like Big Data, Internet of Things and Predictive Analytics, the lack of storage and processing scalability will only restrict future processing performance. Now, imagine an environment where you could reliably process all of your data to identify and capitalise on opportunities whilst avoiding threats as they occur? Imagine this same environment being scalable for any future data requirements where you only pay for what you need at a given time? The time for imagining is over as this is exactly what the right Big Data solution can offer your business, regardless of size.


The ability to generate operational intelligence through advanced analytics is the key lever required to gain competitive edge in today’s business

data quality


So you’ve heard of Business Intelligence (BI) but what is Operational Intelligence (OI) exactly?
Quite simply, OI is a subsection of BI and is all about transforming data into insights at business operations. This often includes real-time data transformations requiring in-depth knowledge of transforming business requirements into data requirements and subsequently implementing solutions that avoid significant overheads to sustain. OI has huge productivity and competitive advantage benefits going forward and is a key focal point for business leaders that are looking for the next big opportunity for improving productivity. Data Engineering offers several key solutions within OI that deliver operational insights without the overheads. Our Insight DashboardsTM, Data Marts and Advanced Business ImprovementTM solutions deliver insights and productivity improvements minus the reliance on a handful of employees who spend hours deriving insights from information or data.



To empower people to make powerful decisions