Business intelligence (BI) involves taking raw data and discerning important patterns, principles, and information from event- or transaction-level data. It is recognized as a valuable solution to the common problem of deriving value in the data archives that most businesses have. However, its use is still limited. One reason for this is that BI software has been difficult to use and implement. Another is that data is increasing in size and complexity. So the key issue to address is how to broaden BI’s accessibility and success rate so that more companies can take advantage of it to increase value within the organization.
Small organizations can compete better and larger organizations can run more efficiently when data is harnessed. The problem is that BI hasn’t scaled past the experts. The industry, then, must broaden BI’s accessibility and success rate so that more people in more organizations can take advantage of it.
An answer to this is a BI technology that is more compact, more embedded, often cloud-hosted, and often self-service. With self-service, BI implementers are no longer the central players for BI adoption within an organization. As a result, the awareness of BI, demand for its capabilities, and raised standards for its features and usability increase at the same time costs fall.
Key highlights in this research include:
- At this point, most users of Software-as-a-Service (SaaS) solutions expect BI to be a required failure.
- Traditional BI delivers raw capability, but embedded, self-service BI delivers results more readily.
- Embedded BI is driven from data that has been curated, so it is easier to understand and work with.
- Embedded BI can also address the siloed nature of data.
- The next area for democratization is predictive analytics.
Image courtesy of flickr user Anton Fomkin