As we head into a new year, IT improvements and management should be top of mind for any business looking to amp up their customer experience, delivery and service in 2018. Recently, at CA World ‘17, I talked about how every business strategy is now an IT strategy. With that in mind, I have a few predictions for 2018 that I encourage companies to have on their to-do list as they look to find greater success in the new year.
The hotel and hospitality industry, enabled with advanced technology and more collaboration with associated businesses, will see some important trends in 2018 as hotel brands reinvent themselves to cater to a new type of clientele. Millennial guests will dominate the landscape, and reshape the industry with demands for more automated options and conveniences and the ability to do everything from a smartphone, and hotels - eager to deliver more conveniences to this younger audience - will forge closer alliances with retailers and community destination
How is DevOps going within your organization? If you need some help measuring just how well it is going, we have prepared a list of some key DevOps metrics to track. These metrics can help you understand how your team is doing over time. The word DevOps means different things to different people. Some say it a culture and every vendor in the industry claims that their tools help with DevOps. Depending on how you define DevOps, some of these metrics may matter more or less to you and your team.
Decentralization of everything, the great new idea of which the web can’t stop babbling, might still seem a bit utopian if you inspect it closely. Yes, blockchains are likely to reshape our economy, or a huge part of it, and benefit considerably those who are currently unbanked. They might also facilitate the creation of rating/reputation systems that are not controlled by any single entity and thus allow people (say Uber drivers who’d like to work for Lyft) to switch employers without having to establish their credibility anew. They might give users complete control over their assets; protect them, to a degree, from being robbed and provide tools to sustain privacy even when a state-level actor – a bank or a government – is after their identity.
This phrase is new and it originated at Netflix back in 2010. I was listening to Nora Jones, a Netflix engineer at the AWS re-Invent conference few weeks back, where she talked about this. The principle of Chaos goes like this, “Chaos Engineering is the discipline of experimenting on a distributed system in order to build confidence in the system’s capability to withstand turbulent conditions in production.” Distributed systems have too many moving parts and failures can occur at various levels – hard disks can fail, the network can go down, a sudden surge in customer traffic can overload a functional component—the list goes on. All too often, these events trigger outages, poor performance, and other undesirable behaviors. Chaos Engineering is a method of experimentation on infrastructure that brings systemic weaknesses to light. This empirical process of verification leads to more resilient systems, and builds confidence in the operational behavior of those systems.
The time of year when crystal balls get a viewing and many pundits put out their annual predictions for the coming year. Copying off since 2012, rather than thinking up my own, I figured I’d regurgitate what many others expect to happen. Top 10 Cyber Security Predictions for 2018 – Infosec Institute kicks off this year’s Top 10, Top 10 list with a look back at their 2017 predictions (AI, IoT, etc.) and dives head first into 2018 noting that Ransomware will be the most dangerous threat to organizations worldwide; cryptocurrency will attract fraudsters looking to mine; cloud security will (again) be a top priority; cyber insurance will explode and cyber-bullying, especially for teenagers, is at the emergency stage.
Bitcoins are a digital cryptocurrency and have been around since 2009. As a substitute for legal tender, they are becoming the rage for investors and others but because there is no government agency auditing or performing regulatory oversights, you wonder if it is the perfect breeding ground for electronic nanocrime. Since the introduction of the Bitcoin, some competitors have emerged and the whole segment of cryptocurrencies are defined as Altcoins. Altcoins include Dogecoin, Ethereum Feathercoin, Litecoin, Novacoin, Peercoin, and Zetacoin. Some of these cryptocurrencies are considered improvements on the original Bitcoin algorithm structure, and they are gaining some traction as well.
Robotic process automation (RPA), a concept that has emerged over recent years, is still in a state of rapid evolution, existing without a clearly defined end-state or direction. As such, vendors are experimenting and pushing their products into uncharted waters - successfully or otherwise. Nonetheless, we can be sure that artificial intelligence and machine learning will continue to develop and impact on automation solutions as whole, even if at the moment these capabilities do not frequently exist within the RPA space.
Every year about this time, we gaze into crystal balls to divine the future of our industry – or at least where it’s headed over the next 365 days. The result is often a triumph of incrementalism: we predict that we will get more of what we already have. The truth is, technology isn’t as revolutionary as we often think – and commenting on incremental changes alone may not help us understand what lies ahead. Along with a few near-term predictions – so hard to resist – I’d also like to make some predictions not just about technology per se, but about related changes to organizations, processes, and the cultures around them. Here’s my main prediction: By 2030 what we’ve come to know as “IT” today will be virtually unrecognizable.
A strong declaration from a historically antagonist foe should put chills in the hearts of Americans preparing themselves for the world ahead: Russian President Vladimir Putin says the nation that leads in AI will be the ruler of the world [1]” … The ruler of the world! From the article (with some modification to avoid political landmines), we get the following: “The development of artificial intelligence has increasingly become a national security concern in recent years. It is China and the US (not Russia), which are seen as the two frontrunners, with China recently announcing its ambition to become the global leader in AI research by 2030. Many analysts warn that America is in danger of falling behind, especially as the [current US] administration prepares to cut funding for basic science and technology research.”
While walking around the office I happened upon a relatively new employee dragging emails from his inbox into folders. I asked why and was told, “I’m just answering emails and getting stuff off my desk.” An empty inbox may be emotionally satisfying to look at, but in practice, you should never do it. Here’s why. I recently wrote a piece arguing that from a mathematical perspective, Messy Desks Are Perfectly Optimized. While it validated the genius of my friends with messy desks, it also generated a barrage of good-natured ribbing from my super-neat friends. Emotions aside, the math is the math! By putting the last paper you looked at on top of the pile, you are organizing your desk using an algorithm called LRU (Least Recently Used). It is based on the idea that the papers you most recently used are the ones you are most likely to use again. Conversely, the papers you have not used in a long time will probably remain unused. It is the closest you can come to predicting what data you are most likely to need next. But what about the papers on the bottom of the pile? When and where should they be filed?
The enterprise data storage marketplace is poised to become a battlefield. No longer the quiet backwater of cloud computing services, the focus of this global transition is now going from compute to storage. An overview of recent storage market history is needed to understand why this transition is important. Before 2007 and the birth of the cloud computing market we are witnessing today, the on-premise model hosted in large local data centers dominated enterprise storage. Key marketplace players were EMC (before the Dell acquisition), NetApp, IBM, HP (before they became HPE) and Hitachi. Company employees managed information technology resources (compute, storage, network) and companies tightly controlled their data in facilities they managed. Data security, legal and regulatory concerns, for the most part, were very localized. The data itself was highly structured (i.e., Relational Databases and SQL) in support of serially executed mostly static business processes. This structured approach worked because consumer segments in most industries were homogeneous, segregated and relatively static. Companies also felt relatively safe in their industry vertical due to the high financial and operational barriers prospective new competitive entrants would face.
Following a tradition dating back to 2002 at ZapThink and continuing at Intellyx since 2014, it’s time for Intellyx’s annual predictions for the coming year. If you’re a long-time fan, you know we have a twist to the typical annual prediction post: we actually critique our predictions from the previous year. To make things even more interesting, Charlie and I switch off, judging the other’s predictions. And now that he’s been with Intellyx for more than a year, this Cortex represents my first opportunity to see if his auguries made the cut.
The cloud revolution in enterprises has very clearly crossed the phase of proof-of-concepts into a truly mainstream adoption. One of most popular enterprise-wide initiatives currently going on are “cloud migration” programs of some kind or another. Finding business value for these programs is not hard to fathom – they include hyperelasticity in infrastructure consumption, subscription based models, and agility derived from rapid speed of deployment of applications. These factors will continue to drive cloud adoption into the foreseeable future.
The goal of Microservices is to improve software delivery speed and increase system safety as scale increases. Microservices being modular these are faster to change and enables an evolutionary architecture where systems can change, as the business needs change. Microservices can scale elastically and by being service oriented can enable APIs natively. Microservices also reduce implementation and release cycle time and enables continuous delivery. This paper provides a logical overview of the Microservices Reference Architecture that highlights various sub systems needed to support Microservices deployment and execution.
"Grape Up leverages Cloud Native technologies and helps companies build software using microservices, and work the DevOps agile way. We've been doing digital innovation for the last 12 years," explained Daniel Heckman, of Grape Up in this SYS-CON.tv interview at 21st Cloud Expo, held Oct 31 – Nov 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA.
The impact of emerging technologies has taken the business by storm. Everyone is familiar with Virtual Reality and 360-degree virtual reality. The immersive experience offered by these emerging technologies have replaced the way people shopped, interact and have fun. Though, the virtual reality and 360-degree virtual reality are new in the marketing arena. Therefore, most of the marketers are not familiar with how to incorporate into marketing and sale strategy. The survival of any business in today’s world is only possible by integrating emerging technologies within the organization. In this article, we are going to discuss how to incorporate VR in your marketing campaigns.
SAP HANA was released as a work in progress. Tenants could leverage the increased speed of the HANA database immediately, but had to wait for the updated SAP S/4HANA applications to be released. Each release has allowed applications to more fully harness HANA, creating new, compelling reasons to migrate for a range of use cases. With the S/4HANA 1709 release, SAP has taken yet another step toward creating a complete product, with substantial benefits over Suite on HANA for most use cases. As with any ERP software, there will be future improvements and innovations, but at this point upgrading to S/4 is a worthwhile investment for nearly every landscape still on SAP ECC or Suite on HANA.
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.
The end of the year is a time for reflection. It’s when most of us are looking back at the choices, accomplishments, and mistakes of the year prior and setting goals to improve the following year. It’s also when businesses analyze the year’s trends and behaviors to determine necessary strategic changes to be made; however, if you aren’t analyzing the right metrics, such reflection is a useless effort. Below is an excerpt from an article provided by Elad Rave, founder and CTO of Teridion, explaining why TTLB (Time to Last Byte) should be one of the performance metrics on your radar.
For better or worse, big data has irrevocably altered the digital landscape. The explosion in variety, velocity, volume and value of information presents an abundance of previously unimaginable opportunity. But it also creates a number of challenges that need to be successfully navigated. This reshaped technical world poses the following question to organizations: do you risk presenting, stale, incorrect or erroneous data to your customers? Because, with 2.5 quintillion bytes of data now being created every day, finding a way to manage and harness such potential is a new experience for everyone. And if you don't take advantage, your competitors will.
Widespread fragmentation is stalling the growth of the IIoT and making it difficult for partners to work together. The number of software platforms, apps, hardware and connectivity standards is creating paralysis among businesses that are afraid of being locked into a solution. EdgeX Foundry is unifying the community around a common IoT edge framework and an ecosystem of interoperable components.
Recently I read somewhere this statement – As we end 2017 and look ahead to 2018, topics that are top of mind for data professionals are the growing range of data management mandates, including the EU’s new General Data Protection Regulation that is directed at personal data and privacy, the growing role of artificial intelligence (AI) and machine learning in enterprise applications, the need for better security in light of the onslaught of hacking cases, and the ability to leverage the expanding Internet of Things.
Large industrial manufacturing organizations are adopting the agile principles of cloud software companies. The industrial manufacturing development process has not scaled over time. Now that design CAD teams are geographically distributed, centralizing their work is key. With large multi-gigabyte projects, outdated tools have stifled industrial team agility, time-to-market milestones, and impacted P&L stakeholders.
Data Monetization! Data Monetization! Data Monetization! It’s the new mantra of many organizations. But what does “data monetization” really mean, how do you do it, and more importantly, who in the organization owns the job of “data monetization”? The role of Chief Data Officer (CDO) would seem to be a godsend to answer the data monetization challenge. They should be the catalyst in helping organizations to become more effective at leveraging data and analytics to power the digital transformation.