Adjectives like “agile” and “self-service” have long been used to describe approaches to BI that enable organizations to ask their own questions and produce their own answers. Applied to both processes and products, these labels are applicable any time an organization can relax the “IT bottleneck”. Over the past decade, the core tenets of the Endeca vision (“no data left behind, ease of use, and agile delivery”) have shaped a product that has empowered organizations to unlock insights in their enterprise data in ways never before possible while simultaneously reducing their reliance on IT to do so. Notice I said “reduce” their reliance, not “eliminate”.
Data discovery is a quest not a destination. It is a never-ending initiative. As soon as new truths come to light from your discovery apps, inevitably, new questions arise as well. Ideally, these new questions can be answered within the application at hand. Sometimes, however, finding answers to these new questions requires experimentation and alternative data “mash-ups”. Almost always in these cases, the time comes to pick up the phone, call IT……and wait.
All of the discovery tools on the market today that promise self-service and agility still require IT’s involvement when new data sources or new data models are required, OEID included. However, through some new features in the the latest v3.0 release, it appears as if Oracle is making strides to address this dependency.
Granted this is just one man’s opinion and largely speculative, but a few of the new features in the product have me convinced that Oracle is pushing to democratize data discovery. Through subtle (and not so subtle) changes, it seems they’re shifting the product to a platform — one that empowers the business to broaden their own exploration and answer the next round of questions, further reducing your organizations reliance on IT.
Here’s what got me thinking
A Collaboration Platform
The revamped “home page” experience surfaces new ways to provision and share your applications. Casual users can now create their own applications, associate them to a data domain, and start composing their apps. Initially, the applications are “private”, and only made accessible to a group of users hand-picked by you. You can make your application “public” once you feel it is ready for the prime-time and mass consumption.
Self-Service Data Upload
Another nod in v3.0 to democratization comes with the introduction self-service data upload. Not only will the upload move data into your data domain, but it will profile your data and (usually) arrive at the proper attribute configuration (data types, etc.) Currently, this only supports Excel file formats, but if you’re like me, you can see where this is heading…
Better Cluster Management
At first I was a bit miffed by Endeca Server’s move from Jetty to WebLogic 11g (and even a little frustrated by the involved installation process), but reading the v3.0 literature around improved cluster management, it became clear that more sophistication in the cluster support might mean there is a future in the cloud for the product. Adding and subtracting nodes from your data domains will be required if end users are actively adding more data or opening up their data mashups to more users in their organization. Elastic computing would have to underpin such a platform with such dynamic, unpredictable resource demands.
Again, this is just one man’s hope for the product. These changes indicate a shift in the way “self-service” is approached. In future releases, “self-service” and “agile” BI may no longer mean simply asking your own unanticipated questions. It may mean introducing new data, new applications and collaborating across the enterprise to further fulfill the promise of data discovery without IT.
I hope Oracle continues down this path. I long for a future where data discovery happens in the cloud so organizations do not have to fumble with infrastructure, scale and upgrades. I see a future with data uploads across a variety of formats which can then be added to a data marketplace within the product for the whole organization to leverage. I hope for new capabilities in Studio so that the data configuration, joining, and cleansing that happens in integrator today by ETL experts and data stewards can be accomplished intuitively by the end users and analysts.
It is my hope that 3.0 is not the end game, but the first step of many towards democratizing data discovery and offering a broader definition to “self-service” BI.