Internal Analytics: A Data Driven Approach
The first selling point for Qlik Sense is the powerful associative difference. After blending multiple data sources to capture the work done by Mashey, we can build associations in the data model between hours spent, payments, customers, and project tasks, using Qlik Sense’s indexing engine by which equal values across identical field names are automatically linked.
This is shown via green white and grey. When users make selections (green), they automatically see alternate states (light grey), untapped relations and further drill downs (white), and unassociated values (grey). The power to dynamically reduce the data set in real time without the need to pre-define hierarchies or hardwired visualizations is the data exploratory power we seek to deliver to our clients. A specific use case which other technologies lack, is the ability to take high level invoices and reports and relate that to hourly detail from employees. The ability to show clients outbound invoices, and previous costs alongside corresponding detail down to the minute sets Mashey apart.
The small portion of a much larger data model shown above contains the crucial relationship between invoices and time entries. Through the back-end capabilities of Qlik Sense we can apply a set of logic and business rules which tie invoice details to hours worked down to a particular clients project. This allows detailed invoice tracking by which a user can select an invoice and see the minute level detail, and associated notes from Mashey employees. The result shown below (blurred out details for privacy purposes) is the most granular level a user can see.
Additionally, we can track ourselves, seeing where time is spent most efficiently and consistently. Constant visualization of our habits and overall health make us a better functioning business and help us grow the most efficient way possible. An example of these internal visualizations is shown below.
The next phase of this 24 hour window was taking our Qlik Sense app and exposing it in our web environments. Qlik Sense provides out of the box capability to embed analytics in a variety of ways. Some so simple, it would require only remedial training in web development concepts, and others with far reaching capacity to reach any look and feel you’d require. Qlik Sense is ultimately a product as powerful as its APIs, so when you’ve reached a capacity with the Server and Desktop product, the next ceiling is as high as your creative and internal web development talent. We set up a framework in React JS, which leverages the Qlik Sense Application discussed earlier. With libraries such as Angular and React, we can use all the capabilities of the Qlik Sense engine, and associative difference in the background while the visualizations are much more custom and controlled. An example of our interface is shown below.
As is shown above, the ultimate destination of our 24 hour voyage did not stop at creating powerful visualizations and an all-encompassing data model, but passing these off to the hands of a React JS framework which complements the Qlik Sense engine to show data in the most beautiful and insightful way. The relative ease of embedding Qlik Sense analytics should be clear in the small time frame, one of the many differences this product, through our team of experts, has shown to happy customers.