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Data Quality

Data quality comes from the source.  If there are issues with data quality, more often than not it is where and when the data is created i.e. think of a manual form on the internet that is not filled out correctly.  Data quality issues increase the overhead of data preparation and if multiple knowledge workers are consuming data from sources with data quality issues, they're doubling up on improving data quality prior to the data set being used in a meaningful way.  This is a source of waste and an opportunity for business improvement.


Even if data quality is sound, data preparation is still a fundamental process for knowledge workers, engineers and analysts in particular, in preparing data for reporting and analyses.  Data quality and data integrity (can I trust the data) are two key dimensions knowledge workers must consider prior to consuming data sets.  Designing solutions that deliver high data quality and data integrity are critical to maximise productivity and efficiency of knowledge workers.  For frequent business reporting, data sets should be tailored towards elimination of data preparation requirements and automating the production of those business reports.


Our Data Quality solution helps both knowledge workers and management develop application specific data sets that produce consistently high data quality and data integrity, resulting in a scalable increase in productivity and efficiency of knowledge workers.  This solution is targeted at knowledge workers who are proficient in visualisation tools like Spotfire, Tableau and PowerBI and have issues around data quality creating excessive overheads for data preparation requirements.  This solution can be extended to automate the data preparation requirements for any repeatable reporting and analytical applications.

Fast Data Application


A new opportunity has emerged to  better manage the increasing  amount of real time event data that is generated from mobile application, field sensors, video images in business operation. The ability to respond to events in real time while making intelligent decisions is a new lever for operational advantage.  Businesses need to create streaming applications or fast data applications in order to stay relevant and grow. These FAST data applications can take the never ending streams of data from people interaction with devices and process them in real time (i.e. apply machine learning & AI ) to make better decisions and enhance experience. 


Choosing the right streaming engines and architectures is not an easy task because this technology is complex and rapidly evolving. If you choose incorrectly then you need to change your solution and this process can be very expensive and time consuming to rectify. Your choice should be a streaming engine and architecture that requires less time to integrate, which is why Data Engineering have partnered with Mesosphere and other big data vendors to help you in choosing the right streaming engine and architecture for your Fast data application.  

Operational Intelligence

Operational Intelligence is Business Intelligence for business operations.  In general this means data assets (data sets and algorithms) combined with visualisation tools for reporting purposes.  Reporting today can be either static or dynamic, with the latter being delivered through interactive dashboards.  Visualisation tools like Spotfire, Tableau and PowerBI have become extremely popular for communicating information, with most of them providing discovery functionalities for basic analyses.


An Operational Intelligence solution is for any operational manager who needs to know what is happening in their business.  There is a spectrum of maturity around this, from transparency of business performance through to basic predictive capabilities of future events.  All Operational Intelligence solutions can be automated, freeing up time of knowledge workers to spend on analytics.


For corporate, business reporting from an ERP solution usually serves generic needs and not the specific needs of operational management.  Operational Intelligence today looks to leverage generic reporting from a company Business Intelligence solution and tailors it towards operational management.  As an operational manager, this means you can have any reporting requirement, in any format, at any time.

Robotic Process Automation

Most medium to large businesses have invested in developing business processes and systems that ensure that employees are more productive, however these processes are often bypassed by some employees because they consider them to be boring, complex, demanding or repetitive. Such employees often cut corners by following their own process purely because it make their works easier to complete. This is often the case in the operations part of the business - where time to complete a task is often a measure of success. For those who choose to follow the process, they often have emotional complains around stress and frustration which they experience when completing their day to day tasks. This is a key problem that robotic process automation is promising to address in today’s business.


Data Engineering have partnered with Help systems to bring  robotic process automation to medium to large businesses. This cutting edge technology can enable rapid business improvement, significantly reducing the time it takes to complete repetitive task. Automating business processes significantly reduces workflow processing costs and gives back time to employees for value-adding tasks. Robotic process automation is a new focus area of waste elimination for business improvement and a new strategic lever for bottom-line competitive advantage. This solution is rapidly gaining popularity across many industries as businesses can achieve step change productivity and improved employee morale by deploying them.  


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