Archive for March 2017
As The Internet of Things continues to grow, huge amount of data is going to be generated. How huge is the “huge”? Really huge. I do mean that.
Physical devices across the globe are consuming and creating data to drive a continuously connected world. David Booth, CEO at BackOffice Associates believes that currently we are at the tipping point of the Internet of Things. He says, “It was not a big leap for the industry to realize that an IoT global network of continuously connected devices would mean that data would not only be created at geometric rates, but that it would become one of the most valuable commodities in the world.”
Alongside the fact that year 2016 was declared to be the year of the first Zettabyte in internet traffic, Cisco report says the number will reach 2.3 ZB by 2020. Before long we will be transferring this much data annually.
If it does not say anything to you, imagine a byte equals 1 character of text – a zettabyte would cover War And Peace by Leo Tolstoy(which is about 1,250 pages) at least 325 trillion times. Or if 1 gigabyte can store 960 minutes of music – technically a zettabyte would be able to store just over 2 billion years of music. If that still isn’t illustrative enough, let’s measure in cups of coffee. Cisco states that if the 11oz coffee on your desk equals to one gigabyte, a zettabyte would have the same volume as the Great Wall of China. This amount of information is mind-blowing. Zettabyte transformed Big Data into enormously Big Data.
The Internet of Things (IoT) is expanding rapidly and relentlessly. And as IoT grows, so do the volumes of data it generates. Ignoring this fact is not an option, and companies will do so at their own peril and risk.
Though there are many new start-up companies storing, analyzing and integrating massive amounts of big data created from the IoT, not many of them have actually considered how the IoT can and will transform organization thinking by implementing data quality and information governance.
With so much data being created, companies must understand what they want to do with it, what are their data requirements and ensure that they have access to the right data. Unless a company can find a way to accumulate, manage and, most important, monetize their data storage, data hoarding can be a real issue for them. Put simply, while the value IoT brings is in the information it creates, innovation gold lies in the filtered data an organization has extracted from the intermediate layer between the devices and the cloud (so called “fog”).
Obviously, data provides powerful potential for boosting analytics efforts. And analyzing the amount of data that is going to be created by the Internet of Things requires new, advanced analytic techniques. The good news is, artificial intelligence and cognitive computing are maturing at a fast pace.
When used properly analytics can help organizations translate IoT’s digital data into knowledge that will contribute to developing new products, offerings, and business models. IoT can provide useful insights into the world outside company walls, and help strategists and decision-makers understand their customers, products, and markets more clearly. It can drive so much more — including opportunities to integrate and automate business processes in ways never imagined before.
Rowan Trollope, Senior Vice President and General Manager of Cisco’s Internet of Things (IoT) and Applications, told participants at the Cisco Live conference, “One of the biggest mistakes you could make now is to underestimate the Internet of Things. This is a life or death issue for most of our customers. They have seen what has happened with Uber and taxi companies and with Netflix and Blockbuster”.
The bottom line is that IoT and Big Data can either disrupt your business or help you become more competitive compared to other businesses that are about to be disrupted.
Business Development Manager
Professional Software Development
When we look into the current trends in programming, few cornerstones dominate in modern programming languages:
• How fast they are
• How smart they are
• Few bugs
These three features were taken into consideration while preparing this article. Let’s see what programming languages share these features and are most likely to be trending in the year 2017.
Back in the year 2014 when Mozilla first launched Rust, it has never been on trending hiring suggests. It sounds confusing but Rust may put great influence on the programming itself. Let’s see why.
• Efficiency – Rust’s language goal is to enable fast, efficient programming
• Safety – with Rust, objects are managed without access to memory locations. It is impossible to reach the locations even accidentally.
Crystal comes to mind when one thinks of an easy-to-learn and expressive programming language.
It is another Ruby-like language spotless from ambiguity because its code is easy to understand. It also boasts the speed of C-like languages.
Crystal has some unique features:
• Fibers-special easy-to-create lightweight channels to achieve concurrency
• Macros to avoid boilerplate code
• Great deal of built-in tools for different purposes
The project is in alpha stage. Its releases occur fast and are interesting to follow. Whenever awaits Crystal in the year 2017, many developers see the language as a trendsetter.
Nim has an ambition to fill the niche of a multipurpose programming language. It has adopted distinctive features of established pros like Rust, Python and even Lisp.
Such multisource adoption of different features starts from creation of a solid standard library and excellent third-party modules. But Nim aims to succeed in both these enterprises.
Though in its alpha-stage, Nim helps get the necessary results very quickly. This language complements the fast-changing software development.
JetBrains made its new programming language for JVM and Android and launched the 1.0 version in February, 2016. The company searched for ways to replace Java in programming of JetBrains’ tools and they created it. It is interesting to see what is to become of this pragmatic, Java-like language in 2017.
Kotlin is easy to learn because it is open-source and approachable. It wasn’t created in a lab; it came out from a certain need –to complete the goals, which Java fails to cover.
Seen by many as an alternative to Node.js, Elixir is likely to evolve in the next couple of years. Its ecosystem is used for building scalable and maintainable applications.
The code is run in a series of lightweight processes, which are isolated and run concurrently in the same machine. Isolation of processes has many advantages, such as:
It is Ruby-like, so why not dig into it for the next year?
What are your top five promising programming languages? Do you agree or disagree with any of the choices for this list?
Business Development Manager
Professional Software Development