Everyone could agree that silos created unnecessary separation, protectionism, and bureaucracy. No one would dare argue that having rigid silos were somehow good for the organization.
Silos were, therefore, the easy target. They became the mantle onto which leaders could lay all past transgressions, and, in so doing, they became a convenient artifice to allow the leader to proclaim the dawn of a new era of integration, collaboration, and communication.
Silos are dead!
Except they never quite died, did they? In spite of all the talk, silos have persisted. They now just have different names. But the danger remains just as real, and their negative impact grows more significant every day.

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Our cities have been connected since the dawn of urbanization in the Indus Valley and on the plains of Mesopotamia nearly ten millennia ago. Cities exist to gather and connect people, bringing us together into communities and joint ventures that need complex networks of communication. But in recent years the connected city has come to mean something more. Today and in the future, the connected city will not just be about people connecting with people, but people with machines, people with people via machines, and perhaps most importantly, machines with machines.

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I’ve always felt that bringing an economics perspective to our big data and digital transformation discussions is more important than a traditional accounting or even information technology (IT) perspective. Heck, I believe that a Chief Data Officer’s background should be more along the lines of economics than IT. Economics brings a forward-looking perspective on creating value (wealth). In fact, economics is defined as “the branch of knowledge concerned with the production, consumption, and transfer (capture) of wealth.”

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SYS-CON Events announced today that IBM has been named “Diamond Sponsor” of SYS-CON’s 21st Cloud Expo, which will take place on October 31 through November 2nd 2017 at the Santa Clara Convention Center in Santa Clara, California. In an era of historic innovation fueled by unprecedented access to data and technology, the low cost and risk of entering new markets has leveled the playing field for business. Today, any ambitious innovator can easily introduce a new application or product that can reinvent business models and transform the client experience.

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There are many solutions that claim to democratize analytics, but they are really constrained. A meta-learning approach democratizes without limits.
The democratization of analytics has become a popular term, and a quick Google search will generate results that explore the necessity of empowering more people with analytics and the rise of citizen data scientists. The ability to easily make better use of your (constantly growing) pool of data is a critical driver of business success, but many of the existing solutions that claim to democratize analytics only do so within severe limits. If you have a complex business scenario and are looking to get revolutionary insights using them, it’s easy to come away disappointed.

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As more and more companies are making the shift from on-premises to public cloud, the standard approach to DevOps is evolving. From encryption, compliance and regulations like GDPR, security in the cloud has become a hot topic. Many DevOps-focused companies have hired dedicated staff to fulfill these requirements, often creating further siloes, complexity and cost. This session aims to highlight existing DevOps cultural approaches, tooling and how security can be wrapped in every facet of the build and release cycle and how to get sales and customer facing resources wrapped in.

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Digital transformation will come from increased investments in technology. But, at the same time, it will also come from increased scrutiny and commitment to quality of the existing services. To ensure this outcome, companies must be committed to the quality spelled through common acronyms such as SLAs, MTTR and MTTD. While these concepts have been around since the time of gurus such as Edward Deming, they are as critical as ever to ensuring technology meets its goals and sets itself up correctly for the future. SLAs and ITOps can inform each other and bring about mutual modernization.

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Today’s businesses run in the virtual world. From virtual machines to chatbots to Bitcoin, physical has become last century’s modus operandi. Dealing with this type of change in business even has its own buzzword – Digital Transformation. From an information technology operations point of view, this has been manifested by organizations increasingly placing applications, virtual servers, storage platforms, networks, managed services and other assets in multiple cloud environments. Managing these virtual assets can be much more challenging than it was with traditional physical assets in your data center. Cost management and control are also vastly different than the physical asset equivalent. Challenges abound around tracking and evaluating cloud investments, managing their costs and increasing their efficiency. Managers need to track cloud spending and usage, compare costs with budgets and obtain actionable insights that help set appropriate governance policies.

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In recent years AI has grown significantly and become a substantial area of business investment. What has changed, and how does this affect you?

For a long time, artificial intelligence was pure science fiction, relegated to books, television and movies—and you don’t need us to tell you that we are well past that point today. In the last few years we have seen extremely rapid advancement in a series of technologies that have come together to unlock a wave of AI investment. According to Accenture, 85% of executives plan to invest extensively in AI in the next three years, and in the same time period, Forrester estimates that businesses using AI will “steal” $1.2 trillion from companies that don’t.

Mark Troester

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I recently visited my dentist and found the experience, well, less than satisfactory. I was subjected to 45 minutes of lecturing while strapped into the dentist chair:

“You don’t brush enough times a day. You don’t brush long enough. You don’t brush correctly. You aren’t using the right type of toothbrush. You aren’t replacing the brush head soon enough. You aren’t flossing enough. You aren’t flossing correctly. You aren’t using the right type of floss.”

Good lord! It’s any wonder that my teeth aren’t just falling out of my head!!
No one likes being lectured. It’s not constructive and after a while, you just turn it off. That’s probably similar to the feeling of going to these Big Data conferences – constantly being told what you aren’t doing right. And maybe I’m guilty of doing that as well. If I am, then I’m sorry because from an audience perspective, it sucks.

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