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The coming year almost certainly has some surprises in store for the technology space, but one factor IT professionals can bank on is that digital transformation will remain a top goal for enterprises. Digital transformation provides a solid advantage by facilitating operational excellence; it enables service or product innovation, and it increases customer value over time. That’s why enabling digital transformation is among CIOs’ top three objectives in 11 out of 15 industries, according to Gartner’s 2018 CIO Agenda Industry Insights report.

Both the agent and currency of every digital transformation initiative is data. IT professionals seeking to help their companies pursue digital business models in the coming year must be ready to quickly integrate an ever-increasing number of endpoints and applications required by business leaders. They must also be ready to manage and deploy digital assets and data from new data sources, a majority of which will be cloud-based, and do so at the speed of innovation. For IT leaders, the challenge will be to develop an IT strategy and architecture that can support the integration and data management needs of digital transformation.

Source de l’article sur DZONE

To understand the current and future state of IoT, we spoke to more than a dozen IT executives active in the space. Here’s what they told us when we asked, "How can organizations get more from IoT?"

Use Case

  • We’ve seen a lot of B2B implementations with high novelty, smart devices of every kind. There needs to be a legitimate use case. With the continued miniaturization of sensors and devices and the proliferation of 5G, there will be plenty of compelling business problems for IoT to solve. 
  • We are making the transformation from just connecting things and getting data to now figuring out the problem we’re trying to solve. There’s a data explosion. We need to determine how to manage and get value from the data. You need to think about business first. What business problem are you trying to solve? Play the “what if?” Dream ask the big question and put in business metrics. Align people from the technology with the business needs and the business partners. Quantify the business value. Identify the vision, strategies, goals, and hypotheses to validate. Have a clear destination. 
  • I think companies can get the most out of IoT if they start by looking for problems or opportunities that can be addressed by IoT technologies like a temperature monitoring system with alerts or remote control capabilities. Too often, companies look at the products or solutions on the market first and then try to think of ways they could apply them. It’s generally just faster and more productive to go after solving a well-defined issue first — and besides, building some expertise and practice in implementing IoT, it often leads to faster wins and a sense of momentum. 
  • In order to get the most out of the IoT, companies should focus on two things: leveraging most of your technology and building a true revenue model. For example, are you leveraging your data in the best ways? If not, what can you adjust in your business model to ensure you are properly leveraging that data. Companies also need to ask themselves: can I create a business model around connectivity that justifies the recurring cost incurred by connected devices? Many companies work backward by imagining the connected product first, and then the value proposition. These IoT projects are hardly ever successful because the company never took the time to fully understand the problem they were trying to solve. Simply adding an Internet connection to your widget doesn’t mean your business will make immediate profits. IoT products come with significant ongoing costs — web infrastructure, networking, and other connectivity and data-related costs. If you can’t justify the added value to your customers, those costs will eat away at your margins. The most successful IoT products are those that deliver recurring, continuous value for your customers (and recurring revenue for you). Companies are finding ways to deliver this recurring, continuous value by using IoT for preventative maintenance, asset tracking, and environmental monitoring. These are business models that not only contribute back to the business but help the customer as well.

Value of Data

  • One thing IoT companies don’t realize is how valuable their data really is. Take a home automation company. The amount of data streaming through their service is staggering — temperatures, energy usage, humidity, the list goes on. They can take that data, turn it into a data firehose, and make it consumable as a business in itself.
  • 1) Think about short-term design to feed into the long-term. Value comes from applications and services that make use of the data. You need to address a real business need and be able to generate the real value, which is to sell and make money.
    2) In the long-term, you need to be able to support and scale. That’s where standards and open source come in. Devices needed to get smart and detected aren’t real expensive. Make sure you have a support structure to manage the cost so as not to eat up benefits. Right now, every time you get a new IoT device, you get a new app for your smartphone. That doesn’t scale; hence, we have a need for standards. You need to be able to bridge to other ecosystems.
  • Connect the data to the problems people have. Five years ago, we focused on the data but didn’t gain traction until realize how data impacts the people in the industry. Business improvement and optimization software — how it impacts the people in their day-to-day life. If you don’t make the connection, you won’t get the adoption.

Other

  • The main benefit that APIs bring is the ability to stitch together IoT deployments within a wider ecosystem of other applications and capabilities across the business. When IoT assets are exposed internally as APIs, they form part of an application network, which provides a way of connecting IoT capabilities with other applications, data, and devices. In this model, these assets are reusable across the business, removing the need for IT to create point-to-point connections for every IoT deployment. As such, APIs become the ‘digital glue,’ providing a future-proof way of combining IoT with other business systems to create a rich ecosystem that gets the most benefit from IoT deployments, all within a secure-by-design approach.

    Source de l’article sur DZONE

In the pursuit of data protection, businesses nowadays face more hurdles in the security landscape than ever before. We know there’s a growing demand for reliable, scalable infrastructure, but issues with downtime are complicating businesses’ confidence in their existing systems, implicating all-too-precious data in the process.

For example, 31 percent of respondents in the 2018 Data Center Industry Survey experienced severe and damaging downtime, and almost 80 percent note that the downtime they did experience could have been avoided. Not to mention, prior to IoT, organizations had to protect their datacenter and ROBO locations. With the emergence of IoT, organizations need to protect their infrastructures at the edge and ensure reliability beyond the core of their datacenter alone.

Source de l’article sur DZONE

“Smart but insecure” sounds like you’re talking about a high achiever who needs therapy.

Which you could be. But in the online world, it applies to semi-animate objects — the hundreds of millions of devices in American homes that are, at one level, smart.

Source de l’article sur DZONE

I am going to open up a controversial subject, the 10x developer myth.

This subject has been debated by the industry for decades, so why bring it up again?

Source de l’article sur DZone (Agile)

Mark Brewer is CEO of Lightbend, the company known for bringing Reactive to JVM application development. With Strata Data Conference in New York, DZone caught up with Brewer to hear more about trends he is seeing around microservices in the enterprise, and to learn about the 2.0 version of Lightbend’s Fast Data platform.

As the company behind the Scala language, Lightbend was very early on making new abstractions for microservices and data-driven applications available to the broader JVM ecosystem. Talk us through that a little bit.

Source de l’article sur DZONE

The recent surge of data has empowered a field of computer science that uses statistical techniques to give computer systems the ability to learn: Machine Learning. Modern Machine Learning Algorithms are able to overcome strictly static program instructions and make data-driven predictions that help companies make decisions with minimal human intervention.

IDC forecasts that spending on Machine Learning will grow from $12 billion in 2017 to $57.6 billion by 2021. What’s more, Machine Learning patents grew at a 34 percent CAGR between 2013 and 2017, making it the third-fastest growing category of all patents granted.


Source de l’article sur DZONE (AI)

This year Apiumhub partnered up with Coding Sans and other software related companies like InstabugClutchShippableCode GiantStrideCodeshipUsersnapGitKraken, and took part in global software development research to find out how companies attract software developers, what are the most popular languages, what are the most frequent challenges, etc. We got more than 300 answers from different countries around the world and we really hope that you will find this report interesting. To get the full report with Interesting facts about software development, click here.

Sneak Peek: Interesting Facts About Software Development

And now, let’s look at some of the data from the report to get an idea of what to expect from this report. Let me highlight that in this article you won’t find a detailed explanation of each graph and question. It is just a sneak peek.

Source de l’article sur DZone (Agile)