You know your business and have great ideas for a business transformation strategy. Time to make it happen. In his session at @ThingsExpo, Jay Mason, Associate Partner at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He discussed the evaluation of communication standards and IoT messaging protocols, data analytics considerations, edge-to-cloud technical architecture, IoT platform selection, end-to-end security, enterprise systems integration and monetization techniques. Seize market opportunities by following this methodology to design and implement a systems architecture that meets complex demands for security, flexibility, durability, and scalability.

While the focus and objectives of IoT initiatives are many and diverse, they all share a few common attributes, and one of those is the network. Commonly, that network includes the Internet, over which there isn't any real control for performance and availability. The current state of the art for Big Data analytics, as applied to network telemetry, offers new opportunities for improving and assuring operational integrity. In his session at @ThingsExpo, Jim Frey, Vice President of Strategic Alliances at Kentik, discussed tactics and tools to bridge the gap between IoT project teams and the network planning and operations functions that play a significant role in project success. Speaker Bio: Jim Frey is Vice President of Strategic Alliances at Network Traffic Intelligence company Kentik.

You know your business and have great ideas for a business transformation strategy. Time to make it happen. In his session at @ThingsExpo, Jay Mason, Associate Partner at M&S Consulting, presented a step-by-step plan to develop your technology implementation strategy. He discussed the evaluation of communication standards and IoT messaging protocols, data analytics considerations, edge-to-cloud technical architecture, IoT platform selection, end-to-end security, enterprise systems integration and monetization techniques. Seize market opportunities by following this methodology to design and implement a systems architecture that meets complex demands for security, flexibility, durability, and scalability.

As we end 2017, I'm tired of writing "lecturing" blogs about what organizations should be doing to master data monetization in order to power their business models and achieve digital transformation. While the objective of every organization should be to master big data and data science (artificial intelligence, machine learning, deep learning) to drive "data monetization," let's take a breath and have some fun. My recent ankle surgery afforded me the opportunity to binge watch "Game of Thrones." As I watched the impending battle between the White Walkers and humanity, I couldn't help but identify a number of lessons that we can learn from Jon Snow's battle with the leader of the White Walkers…and the power of Valyrian steel! Game of Thrones and data, not exactly two things you think are in harmony, but this is where I find myself.

By 2020, 90 percent of all new cars will have some sort of built-in connectivity platform, and by 2022, there will be 1.8 billion automotive M2M connections. As cars join the Internet of Things, cars will stop being independent entities and will become part of a larger, connected ecosystem. "Everything that moves will become autonomic, it's just a matter of time," says Vishnu Andhare, Consulting Manager at ISG, a global technology research and advisory firm. Andhare notes that all of the big automotive players are already moving towards a future of shared mobility, and mobility-as-a-service - although it will take time. "In the future, it will not be limited by technology, but by the psychological barrier, and by public policy," he says.

In his session at 21st Cloud Expo, Raju Shreewastava, founder of Big Data Trunk, provided a fun and simple way to introduce Machine Leaning to anyone and everyone. He solved a machine learning problem and demonstrated an easy way to be able to do machine learning without even coding. Speaker Bio Raju Shreewastava is the founder of Big Data Trunk (www.BigDataTrunk.com), a Big Data Training and consulting firm with offices in the United States. He previously led the data warehouse/business intelligence and Big Data teams at Autodesk. He is a contributing author of book on Azure and Big Data published by SAMS.

In a world where the internet rules all, where 94% of business buyers conduct online research, and where e-commerce sales are poised to fall between $427 billion and $443 billion by the end of this year, we think it's safe to say that your website is a vital part of your business strategy. Whether you're a B2B company, a local business, or an e-commerce site, digital presence is key to maintain in your drive towards success. CloudExpo DXWorldEXPO have announced the conference tracks for Cloud Expo 2018, introducing DXWorldEXPO. DXWordEXPO, colocated with Cloud Expo will be held June 5-7, 2018, at the Javits Center in New York City, and November 6-8, 2018, at the Santa Clara Convention Center, Santa Clara, CA. Digital Transformation (DX) is a major focus with the introduction of DXWorld Expo within the program.

The Internet of Things will challenge the status quo of how IT and development organizations operate. Certainly the fog layer of IoT requires special insights about data ontology, security and transactional integrity. But the developmental challenges are the same: People, Process and Platform. In his session at @ThingsExpo, Craig Sproule, CEO of Metavine, demonstrated how to move beyond today's coding paradigm and shared the must-have mindsets for removing complexity from the development process, accelerating application delivery times, and ensuring that developers will become heroes (not bottlenecks) in the IoT revolution. Speaker Bio Craig Sproule is the CEO of Metavine where he is responsible for the company's vision, product development and customer success.

Will I ever understand the nuances of the advanced analytics landscape? Well, maybe the better question is will the advanced analytics landscape ever stop changing? The advanced analytics landscape, into which I include Deep Learning (DL), Machine Learning (ML), Reinforcement Learning (RL) and Artificial Intelligence (AI), seems to be in a constant state of evolution. New advanced analytic algorithms and tool sets seem to be coming out of every university, every startup, every digital media company and every technology company. And many of these new advanced analytic algorithms and tool sets are open source, which means that they are available for others to build upon.

Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more business becomes digital the more stakeholders are interested in this data including how it relates to business. Some of these people have never used a monitoring tool before.