These days, it seems like you can’t read an article about business intelligence (BI) without seeing the term “self-service.” Self-service BI is often defined as an approach to data analytics that enables business users to access and work with corporate information with little involvement from IT.
These days, it seems like you can’t read an article about business intelligence (BI) without seeing the term “self-service.” Self-service BI is often defined as an approach to data analytics that enables business users to access and work with corporate information with little involvement from IT.
Perhaps the most critical, yet underappreciated aspect of self-service BI is personalization. In the context of BI, personalization is about giving the end user – the consumer of the data output – the ability to define or build the type of experiences they want, and to save them as personalized views.
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Through personalization, users are able to turn dashboards into custom portals; users decide which panels or objects they see; they decide the layouts and how they are arranged on their screens; and they decide what data is being displayed.
Personalization can also be applied to any report outside of the dashboard that includes custom parameters, custom built columns, formulas, the ability to group data, aggregations on the fly, pivot data, charts builds or changing how the data is being visualized. Even simpler concepts like sorting or re-sorting data offer opportunities to personalize the experience.
This trend is clearly visible across the Web in mainstream applications such as Facebook, or on pages such as Google Finance, both of which allow users to customize their encounters via news and entertainment content into designs that are comfortable for them. The same applies to BI applications with data and data visualizations.
There are various levels of personalization like these available on the market. Most BI platforms allow users to decide what objects they see within their dashboards or reports, and allow them to arrange their layouts. But the level of flexibility with many BI platforms is limited, especially with their ability to pull in data from multiple sources.
True personalization empowers users to define what additional types of data are aggregated into their BI applications. Companies that are looking for BI technologies with self-service capabilities should consider ones that not only allow users to customize the look and feel of their BI experience, but ones that seamlessly aggregate content from the “outside.” What’s more, users should be able to save their BI application interactions through bookmarking.
Bookmarking is one of the most underrated features for browsing the Web. The browser bookmark allows users to save and return to an exact page or versions of a page they previously visited and use it at a later time. Most people take this small feature for granted and generally don’t think about it as “personalization.”
In interactive BI reports, users have lots of ways to change both their view as well as what information they collect. Bookmarking is a way for users to save the parameters or choices they made while using reports. This is where personalization has power beyond just customizing a dashboard or report. With bookmarking, users can revisit their interaction without needing to renavigate, refilter, or redo their work, saving them time, resources, and future headaches.
Why is personalization important for end users? Data applications, by and large, are – and are becoming – very sophisticated, allowing users to access more types of data. However, the more data and information users are presented with, the harder it is to filter, navigate and interact with it. Personalization is important to end users because it lets them filter out noise; bookmarking, in particular, allows users to remember what’s useful to them and lets them find their way back to it quickly.
By contrast, an IT-controlled approach permits users to experience data in a silo only. In other words, IT dictates what data business end users have access to – their walled garden of information – and what data they will see and interact with. This is what a lot of traditional BI vendors do, despite a growing demand to give users access to more.
With personalization, you are letting users decide what data they want, how they want to consume it, and how they can come back to it. Additionally, personalization adds value to a company’s existing application by giving it the ability to extend and better meet internal requests, customer needs, or even regulation inquiries.
Personalization is also important to IT. Putting the power and responsibility of BI in users’ hands drastically cuts down on the amount of work needed from IT. User requests for changes to dashboards and reports decrease, so too does the need for IT to create different experiences for each of them. Imagine having 20 different BI users with 20 different roles and being required to create and manage 20 different dashboards or reports with 20 or more different data streams. Unfortunately, this is reality for many IT professionals.
Through personalization, IT can create one dashboard which all users can customize on their own – the way it looks and what data it brings in – delivering faster time to value and increasing company productivity.
Business intelligence technologies that are best suited for personalization are web-based or have web-based architecture. Web pages, Web applications – these things are more geared towards getting information to large groups of people, then letting them decide how they want to use it and whether or not they want to share it. Business intelligence technologies that are not web-based often put the burden back on IT, which runs contrary to the notion of and reasons for self-service BI.
If business intelligence is about arming people with information so that they can make better, data-driven decisions for their organizations, then it makes sense to give them the ammunition they need through personalization.
