Cognitive computing is beginning to impact a range of industries due to its ability to ingest, analyze, and summarize massive data sets and facilitate self-service analytics, intelligent decision support, and smart advisory systems via the application of natural language processing (NLP), machine learning (ML), and intelligent reasoning capabilities. 

What you need to drive your digital transformation is a realistic stakeholders’ consensus about the purpose, expected results (for your customers and your organization), and a roadmap of actions to deliver those results. Such a consensus requires you to create a shared understanding about the nature of the digital business economic environment.

The most common pressures driving Agile data analytics investments are data stored in silos and poor data quality impacting decision making. Both complaints betray the burden of legacy business systems and analytics. Data in back-end IT systems is very often difficult to access, difficult to integrate, difficult to normalize, and therefore difficult to harness to answer the questions posed by the business. Mired in these inflexible and out-of-date sources of data, the efforts to create front-end tools and reports will have limited success.

By leveraging business architecture as the mechanism to connect across business areas and drive toward a collective intent, IT will be in a better position to plan its strategy and roadmaps. What comes down the pipe from the business should be self-consistent and offer a holistic picture of the collective intent of the organization.

This issue of Cutter Business Technology Journal is focused on cognitive computing. Cognitive computing is a term that is similar to, but currently more popular than, artificial intelligence (AI), and it refers to all those innovations in computing that are being driven by various types of AI research. Now is the time to start thinking about how to transform your organization with cognitive computing.

Where in security practice do we turn for inspiration when it comes to protecting our well-being and health from cyberattacks?

Research and discovery are big application areas for applying cognitive techniques, including for financial market analysis, marketing, and product development. Several versions of IBM’s Watson technology, in the form of focused applications, are now being utilized by banking and financial companies in these roles. In addition, commercial cognitive solutions such as Kenshoo, targeted specifically at supporting financial market research, are also available.

The transformation to an Agile culture starts with an understanding of what we mean by culture.

One of the biggest organizational design (OD) challenges facing many organizations is the switch from the more structured, hierarchical forms that were effective in the Industrial Age to more fluid, networked structures that are more appropriate in the Information Age. This is an often unspoken transition that lies at the heart of many enterprise architecture (EA) projects.

While some know-what is vital to understanding long-term implications of the IoT, organizations must begin generating know-how if they are to begin harvesting the potential of this emerging (and likely disruptive) technological paradigm.

Watson Virtual Agent is an important development because it aims to streamline the process of implementing intelligent agents and bots.

Projects are successful when the entire team has the same cohesive vision for the solution. Failure to understand the solution's goal will have rippling effects throughout the project and can lead to failure. It's imperative that the architect and the Agile team members be aligned.

In keeping with digital transformation’s principle of viewing a business holistically across a variety of contexts, viewing how a business delivers stakeholder value is a key element of this holistic perspective. Stakeholders are first and foremost customers, but they also include business partners, other third parties, and internal resources. The value stream provides a nontechnical, value-driven, end-to-end perspective that includes all of the enabling capabilities and participating stakeholders required to deliver the value proposition for that value stream.

AlphaGo is a major breakthrough in cognitive computing; it is a software application that can successfully play the hardest strategy game that people play and can beat human experts at it.

One of the top areas that business architecture teams struggle with is articulating the value of business architecture. Their challenges have less to do with building the business architecture blueprint or even applying it to various scenarios, and more to do with getting the buy-in to be able to do so in the first place. This is partially due to circumstances related to the discipline and its increasing maturity, but also related to the way we communicate.

For enterprises disrupting the marketplace, technology is the key enabler that is helping them create new business models and processes.

Those of us who have been in IT long enough have all witnessed it: the pride tax.

What is the pride tax? It is the amount of money organizations overpay for bad technology decisions. The pride tax takes many forms: runaway enterprise systems projects that persist because leaders don’t want to admit mistakes, choosing wrong vendors based on personal or short-sighted reasons, getting too attached to a set of tools or architectures then defending them at all costs, or even making strategic errors based on unquestioned acceptance of (so-called) best practices or the status quo.

Software has been a crucible of management practice. Since software development requires a wide range of types of work, from mostly routine to highly innovative, and software is often delivered into highly volatile environments, no single management solution can fit all needs.

It is difficult to think “outside the box” when you don’t realize that you are inside a box. This is what happens when enterprises get seduced into romanticizing abstract ideas such as “architecture” or “agility.” It is important to steel oneself to the allure of these siren calls and stay focused on what is of value to the business.

Digital transformation is aspirational. Everyone wants to transform their business, and every business person who's alive knows that transformation now primarily depends upon leveraging the right digital technology at the right time on the right processes and business models at the right cost. With this in mind, let me suggest five steps to successful corporate digital transformation.

In response to the growing number of data breach incidents, the data-centric security vendors have introduced new, advanced database threat-protection solutions employing machine leaning (ML) and behavior analysis techniques designed to monitor and protect databases in real time. Although these advanced solutions are a fairly new development, we wanted to gauge the extent to which organizations are adopting them.

Speed is the new currency of business; customers are expecting organizations to deliver changes and new products at a faster pace. If you’re not going fast enough, you can guarantee that you will be choking on the fumes of organizations that are. New startups are forcing companies to rethink the way they deliver change, but the delivery of the best designs remains an issue. Whilst you may now have your design plainly articulated around the needs of people and outcomes, there is still the matter of resolving the delivery challenge.

When we talk about wearables, most of us have one or two specific devices in mind that we use to add tangibility to our thinking. Yet the examples that occur to us most readily are typically those that require the least effort, rather than those that lend themselves to thorough consideration.

Aspects of planning, implementing, and operating a big data platform affect the traditional enterprise viewpoints of business, technology, information, and infrastructure. Managing the change within one of these viewpoints may be difficult, but due to the technical and business reach of big data technology, ensuring that these changes are cohesive across viewpoints and can be successfully delivered within the organization is even more challenging.

IBM has been working with healthcare providers to develop commercial applications for its industry for almost five years. Two particularly interesting applications are helping transform how patients are diagnosed and treated through the use of individualized, evidence-based medicine. Their development offers insight into the extreme processing and analysis capabilities of cognitive computing and the complexities involved in implementing and training cognitive applications.