Effective data and information management has become the foundation for competitive advantage for enterprises in any industry. Where speed and scale were once technology’s most important requirements, today’s challenges are no longer simply a question of computing power. The opportunities presented by “making sense” of our data and information come with new requirements for comprehension, context and connection.
The proliferation and importance of effective data management has the industry taking note of late. In fact, in an International Data Corporation , Chief Analyst Frank Gens says, “We’ll see massive upshifts in commitment to DX initiatives, 3rd Platform IT, the cloud, coders, data pipelines, the Internet of Things, cognitive services, industry cloud platforms, and customer numbers and connections. Looked at holistically, the guidance we’ve shared provides a clear blueprint for enterprises looking to thrive and lead in the DX economy.” When it comes to cognitive services and we couldn’t agree more.
Organizations are increasingly using cognitive computing, to quickly respond to changes in their business, gain insight into customers, industries and markets and overall improve productivity and be proactive. Looking ahead, in 2016, we predict this technology will prove to add increased value and business agility in 10 key areas:
Cognitive Computing Enhanced Business Applications
People expect to be able to ask a PC or a smartphone for what they want (driving directions, the nearest ATM, etc) and receive an intelligent response. This is the new norm due to all of the available Artificial Intelligence technologies. These same expectations are driving cognitive computing systems into organizations. The core of a cognitive system is compromised of the ability to mimic human understanding; therefore, semantics is and will remain a major enabler of these applications.
A Full-Circle Information Management Solution
User created information—text documents, emails, social media posts, etc. is a valued asset inside an enterprise. Strategic activities that leverage this unstructured information, such as operational risk management, marketing intelligence or customer support, require our information systems to perform difficult tasks that are made even more challenging when they must be performed at scale.
Putting the Meta in Data
As a company’s knowledge base grows, the implementation of a consistent and effective metadata strategy is becoming a vital aspect of information creation, sharing, and distribution. Semantic technology is a critical cornerstone of any metadata strategy because of its essential role in various phases of the metadata process. Not only does semantics support creating pragmatic taxonomies based on an analysis of the available content, it also identifies relevant dynamic tags for each piece of content.
Enhancing the Return on Information Assets
Finding the information you need quickly is important to the success of your business (and to limit frustrations!) The key to helping company’s get the most from their knowledge assets comes from combining content categorization and knowledge collaboration. This is essentially the business value of the effective metadata strategy outlined above. In this case, however, we are talking about the impact it could have across the enterprise on common information management applications (and major investments) such as SharePoint or Google Search Appliance.
The Difference is Meaning (also in the Internet of Things)
Things are changing. Our interactions with the devices we use in our daily lives are becoming more focused on communication. As the “internet of things” becomes an increasingly common component of our daily lives, the transition of simple data collection to communication will logically follow. People do not communicate via data, systems do. Data is an abstraction, understanding is communication, and to understand and communicate one must know meaning. No technology is stronger at executing this than semantic technology.