The enterprise content management (ECM) industry was founded on the same principles some 15 years ago. But instead of dealing with data streams, it was created in order to deal with the increasing amount of unstructured information emerging at the time in the form of documents, e-mails, video, and more. Well, the growth of unstructured information certainly hasn’t slowed any, and when you add to it information coming from big data sources like the Internet of Things, social media, the Web, and business applications, you can see how organizations can be overwhelmed.
The good thing is that if you are versed in ECM, you should be familiar with some of the basic tenets of managing big data. Let’s take a look at some areas of crossover:
- Capture: Capture is the act of ingesting unstructured information and making sense of it so that it can effectively be utilized in a business process. While big data technically has some structure to it, in many cases, it needs to be examined more closely in order to really be utilized. For example, a big data application may be able to ingest 1,000 Tweets about a business, but it might take capture technology, like semantic understanding, in order to help efficiently determine what they mean.
- Analytics: Analytics obviously plays a big role in big data—in fact, it is probably the key element to managing big data. Analytics has only recently been fully introduced into ECM applications. But the goal is the same: On a high level (at first, at least, with the option to drill down further later), figure out what information is in an application so that a user can make better business decisions.
- Workflow: Once those decisions are made, they are typically used in order to kick off a process, which can often be managed by an automated workflow application. This is really the ultimate intersection of big data and ECM. Potentially, a user could have separate capture and analytics methods for each discipline, but if big data and unstructured content are affecting the same area, it’s probably optimal to bring them together into a single workflow.
- Information Governance (IG): We discussed this in an earlier blog post, where we stated “IG is designed to optimize the control and use of an organization’s information.” Obviously, big data is part of an organization’s information. Being able to apply IG to big data is a natural extension of applying IG to ECM.
The bottom line here is that a lot of the same policies and procedures that can be applied to ECM can be applied to big data. It’s our view that big data is really part of the next generation of ECM. In fact, some people have already started to refer to the evolving ECM market as “information management,” and we think big data clearly fits under this expanded definition.
As a reseller of ECM technologies, we encourage you to embrace big data and see if you can leverage it within the business processes that your ECM applications are already managing. Content is evolving, and it will continue to evolve. In order to be successful in the information management market, you need to evolve, too—from managing paper to images to electronic documents to, now, big data. Embrace this change and you will be able to continue to address your customers’ needs. Ignore it and you risk them finding somebody else who can.
Creating the complete ecosystem of Enterprise Content Management can be tricky to navigate. Be sure to encompass all areas of the solution including the data center infrastructure to the document process or workflow that is needed. IBM’s ECM solutions cover the entire catalog of data handling solutions that are also industry specific to help speed deployment methods. From capturing, process, redact, and digitally file documents with IBM DataCap, process workflow with IBM Content Manager, securely share protected documents with Daeja ViewONE, while creating an a repository that not only stores the content but additional metadata related to the content with IBM FileNet. Be sure your ECM approach involves the people and process of data!