A real focus for the projects I've been working on recently has been around building analytical applications. These applications are often referred to as dashboards by the teams involved in designing, building or consuming them, but they are so much more than a few pages of data visualizations.
They are analytical suites (re-designed, re-imagined and digitized reporting packs), accessible via browsers and mobile devices. Business users are demanding analytical applications to interact with their data to drive insights and action.
They need bespoke content, layouts, interaction, and navigation options along with the ability to converse between guided/set navigation and self-service capability.
It's a balancing act of building content that quickly gives the user an updated business position, a stance on exceptions they need to address, as well as to possibly explore the data for any on-the-fly analysis.
It all needs to be engaging and efficient too.This content is all being demanded at speed. People need information quickly (take too long to build them something, and they'll just go and build it themselves).
They also demand that the content constantly evolves, again at speed. Business is dynamic, therefore so is decision-making and analytics. There's a real need to ensure you have the right technology solutions and processes to be able to build and deliver analytical content that can:
1. Continually deliver content fast.
Analytical content needs to be delivered quickly and often. Business users can’t wait. If they do they'll go and build themselves (often through point solutions with little thought for integration, scalability, or governance).
You need to have a technology and process in place that allows you to embrace speed and agility rather fight against it. Being able to develop at speed can be supported by a solution that allows you to deliver content with little to no code.
2. Co-exist with the ability to execute an action.
Applications that only allow the analysis of information means that users have to go elsewhere to then act on that information (contact a customer, create a workflow task, etc.).
You need to have a composite environment where the ability to analyze and act can all take place in the same place (ideally the same screen) and at the same time.
This can be a challenge for traditional analytics/business intelligence (BI) tools because they are designed to focus on the analysis part. This is why embedding BI capabilities, content, and products into transactional systems is important.
3. Span across all your sources of data.
It's very rare that all data exists in one single place or systems (whether you have a single vendor or technology platform strategy in place or not). You therefore need something that can easily integrate and sit across any system.
These of course aren't the only challenges that analytics currently faces but those that have been the most prevalent for me on recent projects. I'm interested to hear your thoughts. Let me know what you think.
