Innovation continues to occur at a breakneck pace, forcing business leaders to continuously manage change as emerging technologies become more mainstream. We are currently in a phase of digital transformation and every business is seeing a shift. New technologies have fueled globalization, redefined our concepts of software and computing, crushed costs, and fueled data-driven decision making.
In this blog post, I would like to talk about four of these tectonic technology shifts and relevant Qlikproduct innovations that could pave way for new analytics use cases.
Cloud computing vs Edge Computing
Cloud computing has become a major trend over the last decade. However, the trend towards edge computing seems to be slowly pushing cloud computing to the edge. A lot of tomorrow’s analytics will be done locally at the “edge,” or in multi-cloud and I think, instead of trends replacing each other, they’ll merge and generate a blended approach creating more efficient solutions for businesses and consumers.
One element in working out analytics solutions with this trend will be figuring out how and where to apply analytics, especially for Internet of Things use cases, and leveraging an analytics platform that can support both. Here, I see a lot of benefits for using Qlik Core. Qlik Core is Qlik’s analytics development platform built around Qlik’s powerful Associative engine and Qlik-authored open source libraries. The technology is built by leveraging the latest cloud technologies with Linux, Docker and Kubernetes. With Qlik Core, developers can build analytics solutions that works at the edge (on or near the sensor) for speed; and then by leveraging Qlik’s multi cloud environment, variety of data can be sent to cloud to be analyzed at scale.
Closed-source to open-source
In the past decade, adoption of open source software at the enterprise level has flourished as more businesses discover the considerable advantages. There are many reasons for this shift, like leveraging the collective power of a community of talented individuals working in concert delivers not only more ideas, but quicker development and troubleshooting when issues arise.
Qlik’s open source libraries supports these needs while developing analytics solutions. Whether loading data (halyard.js), interacting with the Associative Engine (enigma.js) or looking for visualization frameworks (picasso.js), Qlik authored open source libraries allows enterprises to leverage the power of the crowd. You can see many innovative solutions built by Qlik’s developer community at Qlik Branch.
Human to machine (AI)
Artificial Intelligence is no longer just a futuristic notion, it's here right now. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly or to completely reimagine them.
At Qlik, our approach to AI is Augmented Intelligence. It puts human intuition in the middle of data and advanced algorithms. Qlik’s AI technology–Qlik Cognitive Engine–supports users during their full analytics workflow by making their analytics processes more fluid, speeding up time to insights, and increasing data literacy across all users.
Real to virtual (AR/VR)
AR and VR are the new reality. Digi-Capital, a leading research company in AR & VR Technology predicts that Ubiquitous $90 billion AR to dominate focused $15 billion VR by 2022. Although not yet widely in use, these technologies will soon be used by more companies to create unique, engaging, and meaningful experiences for their customers and users. A great example is IKEA’s Place app.
To inspire some ideas about innovative analytics possibilities with some of these tectonic shifts, I would like to share a Qlik Research project that we have built by using Qlik Core.
The solution uses AR, and provides a new level of interaction between the physical products and users by immersing them in augmented reality. It focuses on shelf space analytics and optimization.
In a store, a product’s position can greatly affect its performance. Having the right space allocation for products and categories plays a critical role in its retail success. From a retailer’s perspective, given the value of shelf space positions, it is very critical to ensure that retail space is working for value maximization for the store.
With this need in mind, we built a solution that would enable the retail employee to be “augmented”, where he can see product specific analytics by just looking at it.
The solution is created by integrating Qlik’s Associative Engine (by using Qlik Core) with Microsoft HoloLens. When the user looks at a product with HoloLens, the system triggers a selection on the data to calculate and visualize product specific sales and affinity metrics on the fly and displays them in augmented reality. With this information, the employee can immediately decide where to position the product on the shelf.
This article was written by Elif Tutuk and originally appeared here: https://blog.qlik.com/the-rise-of-digital-and-four-tectonic-technology-shifts