Internet of Things (IoT) adoption is certainly being driven by the promise of real-time analytics and AI at scale, but its ultimate feasibility still depends on something much more mundane, namely how efficiently it can move data between connected devices and backend systems.
And yet, according to a recent GlobalData study, IoT practitioners haven’t yet learned that lesson, relying not on fit-for-purpose protocols like MQTT, but instead on the ubiquitous, now aging web standard, HTTP.
At Mobile World Congress this week, networking giant Cisco rolled out a new networking and device management platform for IoT practitioners that promises to enable the creation of extremely large-scale deployments without breaking the bank. IoT at scale is a no-brainer. More devices equal more data. More data equals deeper business insights. But, IoT at scale can be expensive in terms of delivering basic device interconnectivity and management costs. Continue reading “The Internet of Things Isn’t Driven by Devices as Much as by the Internet Itself”→
• Many organizations are unsure of how to best incorporate AI to meet their industry-specific challenges – often because the use case options are so vast and so varied.
• Organizations – particularly mid-sized businesses, companies starting out on their analytics journeys, or those rolling out IoT solutions – should explore the services available from their telecom provider, many of which have built out their professional services capabilities around digital transformation.
Amazon teamed up with Berkshire Hathaway and J.P. Morgan Chase to create a separate operating company to find a more cost-effective and efficient way to deliver healthcare to the company’s respective employees.
While all three companies bring unique characteristics that set this union apart from other alliances, it is Amazon’s history of transformative innovation that elevates the alliance.
When three giants of their respective industries strike an alliance around U.S. healthcare, the world is bound to react (as are markets). And when one of those companies is Amazon, the word ‘disruption’ almost automatically enters the conversation. So, when news hit the wires that Amazon, Berkshire Hathaway, and J.P. Morgan Chase are entering a healthcare-related partnership to benefit their employees and lower their cost structure, speculation went into high gear and the conjecture started. Continue reading “Amazon Enlists Marquee Partners Berkshire Hathaway and J.P. Morgan Chase to Take On Healthcare”→
• With big data and analytics, older ideas like predictive analytics and AI are coming together to solve long-standing problems, most notably data quality.
• Sisense is adding another twist by taking advanced design and visualization concepts and putting those to work at the very beginning of the analytics lifecycle.
Invention invariably involves theft. Each generation of inventors stands on the shoulders of its predecessors, borrowing freely from their available pool of knowledge. Ideas are deconstructed, mixed up, and reapplied in new ways and within unexpected contexts to form, well, something new. Sometimes these new inventions are simply the opportunistic reinterpretation of an existing idea, taking something unique but impractical and turning it into something incredibly useful. That’s the way it was with the invention of the automobile, the light bulb and the radio. And that’s how it is with big data and analytics, where older ideas are only now coming together to solve long-standing problems. Continue reading “To Improve Data Quality, Sometimes the Best Place to Start is at the Very End”→
Cyber threats are impacting the bottom line, leading to increased security spending.
Priority is being placed on managed firewalls, identity management, and SIEM.
Telcos like BT are stepping forward with shared threat intelligence initiatives.
Endless new threats impacting businesses and consumers are driving demand for IT and cybersecurity products and services both by besieged IT departments – with the thankless task of protecting against invisible thieves and miscreants – and by their bosses, who have been firmly pulled into cybersecurity decision making.
Artificial intelligence (AI) and machine learning (ML) are being developed for networking and network management, with the first iterations providing deep analytics and augmenting IT’s root cause analysis workflows.
There are a number of gaps that need to be closed before the full capability of AI and ML systems is realized.
Artificial intelligence and machine learning techniques continue to be improved as companies and researchers develop and test products. In networking, established vendors and startups are developing management systems that promise to automate the time-consuming, low-value work of data collection and correlation as well as the AI and ML techniques to provide actionable information to network IT, such as predictive trouble alerts and recommendations to resolve problems. Vendors’ products such as the recently announced Cisco DNA Center Assurance, Cisco Network Analytics Engine, and Mist Systems Virtual Network Assistant are also using sophisticated UI elements to help IT better understand networking problems and assist with root cause analysis. We’ve heard these promises in the past, and for one reason or another, these advanced techniques failed to deliver. Before you go the AI route, here are some key questions to ask. Continue reading “Four Interview Questions to Ask WOPR for a Junior Network Administrator Role”→