Many organizations have been experimenting and committing to self-service analytical tools over the last 3-5 years. Typically the business side has led the charge, wanting to take more control of their data driven business opportunity, being able to upload their own data, mash it with other sources, and generate a variety of insights.
Self-service can be very powerful and of great value to the business, but over time a couple of significant challenges have emerged:
Silos / Bad Data
Analytical silos are typically formed by self-service users, who prepare their own data, create reports and charts, and share them within their own work group. Their data preparation and content creation can often lead to errors in the data and views, and decisions can easily be made from erroneous insights.
Reinventing the Wheel
Users are also often recreating similar reports, charts and views because they have no idea that someone else might have created something similar. And when two people arrive at a meeting with a similar chart or report, with differing data and conclusions, the age-old 'multiple versions of the truth' issue reappears.
This is where a fully featured and unified platform can save the day.
A fully featured BI and analytics platform can deliver both 'traditional' business intelligence (in the form of reports, charts, dashboards, analytical documents, information applications), and more agile self-service analytics (visualizations, infographics, stories), all under the governed foundation of an enterprise grade platform.
'Fully Featured' as a term is a moving target, as the industry innovates. Platforms must be updated with those innovations that add real value to a BI and analytics audience, for example:
- Augmented analytics have appeared over the last couple of years, where some aspects of the BI and analytics content/insight generation process have become automated to assist users with their objectives. Within WebFOCUS, our new Intelligent Objects is a good example of how authored analytical views are automatically indexed as metadata, and contextually relevant views are presented to other users. This type of augmentation helps to stop the reinvention of the wheel, and multiple versions of the truth.
- Data science is appearing in mainstream BI and analytics: whether via data specialists incorporating complex predictive, AI and machine learning models into business processes, or via citizen data scientists easily able to leverage statistical models into their everyday analytics and decision making. Implementing data science via the WebFOCUS enterprise BI and analytics platform provides the ability to deploy the outcomes of models and algorithms to hundreds even thousands of users. The power of the platform is critical here.
All in all, there are many moving variables that organizations need to understand and manage, in order to truly benefit from all the opportunities that data driven business offers. We think that if the platform can help both IT and business deliver governed BI and analytics to a very broad range of users, at scale, at speed and on the users terms, then organizations will be in position to succeed.
Take a look at "10 Reasons to Love the New WebFOCUS" for more information.
Thanks for your time today!