5 Technologies That Might Turn Startups into Multibillion-Dollar Ventures

Despite its stagnant appearance, the world is about to be hit by a massive way of digital transformation and technology-driven economic change eventually leaving us with two options, either ride that wave into a new era of prosperity…or be swept away by the wave. In the following post, you will come across five most dazzling technologies available in the “Golden Age” and how they might earn you a big fortune. Whether you are listed among the fortune 500 companies or a startup, these technologies can surely give you a head-start in your career. Go through them in order to satisfy your inner desire for doing any innovation in the world. Java Launched in 1995, Java is mainly used to develop Client-server web applications, J2EE web and enterprise applications all across the globe. Highly rich in APIs, Java offers API for I/O, networking, utilities, XML parsing, database connection, and almost everything. Online community- It comprises of a huge community from javaworld.com, oracle.com, javacodegeeks.com and many other popular sites. In addition to this, Java can even go for Android-based mobile application development. Well-known sites such as @LinkedIn, @Amazon, @Facebook ( @HBase, a java based #NoSQL DB), @EBay, @Googleplus, @Gtalk are powered by @Java. As of now, there are approx. 9 million Java developers. Python @Python was launched in 1994, a tool mainly used for web crawler development and data analysis. From @Microsoft Windows to #MacOSX, @Linux, and many other operating systems and devices, Python even works as a service. In fact, it is considered as one of the fastest growing fan base in past 10 years and has obviously increased in demand. It also has a diverse community support including python.org. Other than crawler development and data analysis, Python is used for small-form devices, such as the Raspberry Pi. In addition to this, the technology runs on microcontrollers — small, low-powered chips designed to run on embedded devices, appliances, remote controls and toys. Google, Facebook, YouTube, Yahoo Maps, Yahoo Groups, Bing, Reddit, Dropbox are some of the known companies making use of the technology. Android One of my favorites is Android! Launched in September 2008, Android is a mobile operating system based on Linux kernel and currently developed by Google. In the current scenario, there were total 1.5 million Android apps available with over 25 billion downloads. Further speaking about the development process, applications are usually developed in Java programming with the help of the Android software development kit (SDK). It is simply an open source operating system staked by Google, developed to run on any small electronic devices such as cell phones, tablets, e-books, netbooks, Media Internet Devices (MID). The hardware is developed by many different companies from all across the globe with famous brand names such as Samsung, Motorola, Sony, Dell, LG, HTC, Acer, etc. It is no surprise that the technology has a giant size community in the form of developers.android.com, androidcommunity.com. iOS Launched a decade ago, IOS is another leading mobile operating system created and developed by Apple Inc. and distributed exclusively for Apple hardware. Presently, it powers many of the company’s mobile devices, including the iPhone, Mac, Apple watch, iPad, and iPod touch. If we take a closer look at the current demand for IOS developers, it is increasing on the rapid basis. Owing to huge opportunities in eLearning, social networking, warehouse management, order fulfillment, orthodontia, accounting, consumer analytics, gaming, and image, data, and video analysis, the technology has major community support in the form of discussions.apple.com, enterpriseios.com. NodeJS Launched 27 may, 2009, NodeJS is an open source, cross-platform run-time environment for server-side and networking applications. The technology offers an event-driven architecture and a non-blocking I/O API that optimizes an application’s throughput and scalability. Commonly used for real-time web applications, the technology can also be run within Node.js runtime on OS X, Microsoft Windows, Linux, FreeBSD, NonStop, IBM AIX, IBM System z and IBM I. Companies involved: LinkedIn, PayPal, Netflix, New York Times. Due to healthy online community support has given rise to several NodeJS development companies like eTatvaSoft, theninehertz, espeo, itexus and many more worldwide. AS of now, there are tens of thousands of job requirements for the same. The demand for node JS is increasing at an exponential rate especially in the last five years. Final thoughts Just by looking at where we are today, we can already see how powerful technology has been in shaping our world. The introduction of new-fangled pieces of knowledge especially in the field of software development has radically altered this world in so many ways. Which eventually becomes even more evident in the continuous development of forward-looking devices and systems that people before never knew could exist.

https://bdaily.co.uk/articles/2017/10/12/5-technologies-that-might-turn-startups-into-multibillion-dollar-ventures

5 open source tools for developing IoT applications

The internet of things is growing at a staggeringly fast pace, and is quickly coming to revolutionize virtually every aspect of modern life. Aspiring developers hoping to hop on board and profit off the growing phenomenon are constantly looking for the right tools to use. So what are the open source tools best suited for working with the IoT, and where can developers find them?

A plethora of open source tools lay at the disposal of any would-be developer eager and wise enough to use them. By utilizing these five, you’ll find yourself tackling challenges and developing successful applications in no time.

Arduino

An Arduino development kit stands out from the rest of the crowd by offering both software and hardware to would-be developers. The cloud-based system allows developers to easily send messages from one board to another, and includes its own Arduino programming language.

Arduino is well suited to anyone seeking to make an interactive application well-suited to the IoT economy. The software and hardware is designed for customers who don’t necessarily have a background in programming, and is thus a great option for beginners who want to break into the marketplace.

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Home Assistant

Perfect for an aspirant with high-hopes to exploit the rising smart home market, Home Assistant is suited for developers looking to increase connectivity between people’s living spaces and the internet. Tailor-made for the internet of things, this platform, which runs on Python, is great for tracking and interacting with sensors and smart devices in your home.

While using Home Assistant is incredibly easy on a laptop or desktop, the tool lacks a cloud component, meaning it’s not the best for those looking for a constant internet connection. Nonetheless, this means Home Assistant is particularly useful during internet outages, and can be relied upon to keep your data secure at all times.

Zetta

A fascinating, server-based platform, Zetta is perfect for taking devices from numerous brands and turning them into API. Built on Node.js and explicitly marketed toward pioneers of the internet of things, Zetta heavily relies on the cloud so that is can be run from virtually anywhere.

Often used in tandem with Arduino, Zetta expertly welds together the best parts of reactive programming and WebSockets, making it perfect for data-intensive IoT endeavors.

http://www.cio.com/article/3209712/internet-of-things/5-open-source-tools-for-developing-iot-applications.html

OpenText vows to take on IBM Watson with new Magellan AI platform

IEnterprise information management company #OpenText has announced the general availability of its new #artificialintelligence ( #AI ) and cognitive computing platform, #Magellan, at its Enterprise World conference in Toronto. Attendees at the show were left in little doubt as to how senior executives at the Waterloo, Ontario-based company would like them to view Magellan: as a direct competitor to #IBM ’s #Watson. OpenText isn’t targeting Salesforce’s Einstein, nor similar AI-based initiatives from #SAP or #Pegasystems, CEO Mark Barrenechea stressed in a press conference at the event: It’s Watson [that we’re targeting]. What differentiates us is that the information-centric applications that we already have will be integrated directly with Magellan. We don’t want to extract information – from contracts, for example – out of applications and into an AI platform. The fact that you have to feed Watson with data extracted from multiple resources, I think, is a weakness. In other words, OpenText is aiming to embed Magellan’s AI capabilities in some of the tools that comprise its vast portfolio of software products. These typically focus on unstructured and semi-structured information, in areas such as enterprise content management, customer experience and data discovery. Where the company believes Magellan can stand out is in its understanding of human language (as opposed to transactional data), as it is expressed in documents such as reports, memos, emails, contracts and requests for information, via text mining and semantic analysis. Built by OpenText? This looks likely to be a significant challenge, because OpenText has largely been built through acquisition. In the last 20 or so years, it’s acquired over 50 different information management companies. Most recently, these have included its $1.62 billion purchase of #DellEMC s enterprise content software, which included former arch-rival #Documentum, in a deal that closed in January, and its April acquisition of customer experience software and service assets from #HPE, for $170 million. In fact, #Magellan itself has its roots in technology acquired in two acquisitions: the 2010 purchase of #NsteinTechnologies, which brought text mining and auto classification capabilities to OpenText; and the 2015 purchase of Actuate, which brought it analytics capabilities. On top of these technologies, OpenText has introduced integration with two open source products: big data framework #ApacheSpark and #ApacheMLlib, a machine learning library. Algorithms for Magellan can be programmed in languages including #Scala, #Python and R. But as Barrenechea stressed: There’s also a whole ton of our own engineering in there. We may start with M&A, but if we can’t grow a product, if we can’t innovate, if we can’t get it to evolve, then we’re not interested in buying it. Magellan is built by OpenText. Challenges ahead It’s no surprise that Barrenechea is keen to stress OpenText’s engineering and innovation credentials. With the launch of Magellan and the shift into AI, the company will find itself in a fiercely competitive and fast-moving field of technology. It could prove to be an unforgiving environment for a company built on acquisition, as opposed to organic growth fuelled by new products. As Barrenechea told analysts on the company’s third quarter results call: M&A remains our leading growth driver, and we will continue to grow and invest in our M&A team. It’s hard, then, not to draw parallels with the kind of strategy made famous by CA Technologies during the 1990s and early 2000s: buy up intellectual property from other software companies, provide basic maintenance and milk the installed base. The fact that Barrenechea worked at CA Technologies (then known as Computer Associates) in various roles during those years – as product development head, president of technology strategy and chief technology officer – simply reinforces that comparison. To sweeten the deal for prospective Magellan customers, the product will be sold at a much lower price point than IBM Watson, will be available as an appliance that runs on preconfigured, commodity hardware and be available on premises or via the cloud. A lower cost of entry could appeal to a wider range of customers than might consider IBM Watson a viable investment. As Barrenechea put it: With OpenText Magellan, we are moving towards a more open, scalable and affordable future for AI. OpenText is committed to ensuring AI is designed into its offerings from day one.

http://diginomica.com/2017/07/14/opentext-vows-take-ibm-watson-new-magellan-ai-platform/

Why Java in Big Data? What about Scala?

Why #Java ? Why not? What about #Scala ? Or #Python. I use all three for various parts of #BigData projects. Use the best tool for the job. A lot of things can be orchestrated and managed without any coding through #Apache NiFi 1.0. Some things like #TensorFlow are best done in Python, while #Spark and #Flink jobs could be Scala, Python, or Java. #ApacheBeam is Java only (Spotify added a Scala interface, but it's not official yet. If you are a really strong Java 8 developer and code clean, you can write #Hadoop #MapReduce, #Kafka, Spark, Flink, #Apex. Apache NiFi is written in Java and so is most of Hadoop, so it's Big Data scale. Spark and others are written mostly in Scala. Ecosystem Scala and Java share a ton of libraries, as they run on the JVM. Python has its own huge ecosystem, but for many Hadoop things the JVM languages have a bit of an advantage. You can run JPython on the JVM, but I really haven't seen that used for Big Data, Spark, or Machine Learning. I am wondering if anyone is doing this? Please comment here. Python has TensorFlow and some nice Deep Learning and Machine Learning libraries. They are also starting to get more Universities teaching Python instead of Java. Not too many Universities are teaching Scala.

https://dzone.com/articles/why-java-in-big-data

How to use Python with Nutanix REST API – Part 1

#Nutanix has been built with a strong set of APIs for managing all cluster aspects and AHV virtual machines. REST API’s can be called from a browser and also from pretty much any existing language out there. I have been using mostly #Python Language to create my toys and prototypes, so I decided to share some instructions and code about how to use Python to connect to a Nutanix Cluster and manipulate objects. If you are not familiar with Python Language I recommend this Python For Beginners; Python is very easy to learn! If you are trying to connect to Nutanix API with an untrusted SSL certificate, you will get the InsecureRequestWarning: Unverified HTTPS. Adding certificate verification is strongly advised, but if you want to bypass the SSL certificate you will need to execute following code snippet.

https://www.dabcc.com/how-to-use-python-with-nutanix-rest-api-part-1/