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RPA – Hype of The Future?

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Robotic Process Automation or RPA is pegged to be one of the next ‘big things’ in tech. However, the rate of innovation and change in the tech world is unlike any other industry. New buzz words like RPA appear every other week and it can be hard to distinguish the difference between hype and reality. A number of insiders from the industry say that RPA is not only the future of controllership, but it is fast becoming the present.

To understand the future of RPA, we must first consider what RPA is, the main players pushing RPA and the venture capital behind it.

RPA is the application of technology that enables one to configure computer software or a ‘robot’ to capture and interpret existing applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems. RPA is essentially a software robot that mimics human actions. It is often conflated with artificial intelligence (AI) and machine learning (ML) but there is a clear distinction between the two. At the most basic level, RPA is associated with ‘doing’ whereas AI and ML are concerned with ‘think and learning’.

A simple example of RPAs applicability is automating the grunt work of retrieving emails. Retrieval is based on the email’s subject, downloading the attachments (e.g. invoices) into a defined folder, and then inputting the bills into accounting software (typically through copy and paste actions). RPA is highly process driven, it is simply automating repetitive, rule-based processes that typically require interaction with multiple, disparate IT systems.

This is the key difference between RPA and AI, AI is concerned with high quality data. AI is required to intelligently “read” the invoices, and extract the pertinent information such as invoice number, supplier name, invoice due date, product description, amounts due, and many more. Since every activity in RPA needs to be explicitly programmed or scripted, it is practically impossible to teach the bot exactly where to extract the relevant information for each invoice received. Hence the need for AI to intelligently decipher the invoice just as a human would.

RPA tech is hot. Industry experts have valued the industry at €2 billion with forecasts indicating this figure will rise to nearly €4 billion by 2022. These valuations are supported by venture capital investments into RPA companies. In 2018, RPA specialists Automation Anywhere secured €270 million from SoftBank, Kryon secured €35 million, Softomotive secured €22 million, and Automation Hero secured €12.5 million. The dominant force in the RPA sphere is UiPath, a New York based company founded in 2005. In 2018, UiPath received a sizeable €500 million investment in a series D round of funding led by hedge fund Coatue Management. This brought the company’s total funding figure to €1 billion with the company now being valued around the €7 billion mark, not so bad for ‘hype’.

The big players like UiPath’s core selling point is that it brings automation to enterprise processes through “intelligent software robots” that help businesses carry out laborious, repetitive tasks using computer vision and rule-based processes. UiPath state that their software streamlines work processes by eliminating the laborious elements of a job, freeing up valuable time for employees to work on other things.

As with all automation software, the impact on human jobs is a real concern. To date, the impact has yet to be assessed and the main players in the RPA industry are downplaying the potential negative impact of their software on jobs. Like many others in the automation world, they argue that RPA removes laborious elements of jobs rather than removing the job itself. Only the future will tell the impact technologies like RPA will have on the workforce. Regardless, it’s safe to say that all indications seem to convey that RPA is not just a fad or the future, it is fast becoming the present.

Posted by Craig Field on 21 May 2019

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What is Python Being Used for in 2019?

What is Python Being Used for in 2019?

Python is everywhere. Google, YouTube, Spotify, Reddit, Instagram, Netflix, Uber, Dropbox, Pinterest, Lyft, the list of dominant names in the tech industry that use Python is endless. Python is the fastest growing major language in the world edging out Java according to StackOverflow. Python is also the second most loved language by developers just behind Rust and has been the third most popular language on GitHub for years. ​ Python is a highly versatile language that can be used for a plethora of applications. As tech continues to rapidly evolve and change, Python is being used for different applications. Here is what Python is being used for in 2019; Data Analysis and Data Science Data analysis and data science are the most popular application of Python for 2019. Data driven decision making is increasing in popularity in large multinationals as well as SMEs. Data driven decision making enables companies to work smarter, increasing efficiency and profitability. This isn’t a new trend; data science has been on the rise for the last few years with data science being the highest paid field (within tech) to enter in 2016 according to Glassdoor. In terms of frameworks and libraries, developers are favouring NumPy, TensorFlow, Scikit-Learn and Keras for data analysis and science in 2019. Similarly, employers are actively seeking Python developers with NumPy and Tensor Flow experience/knowledge. This can be seen by the number of job specs citing these frameworks on LinkedIn, Indeed, Angel List and StackOverflow. Web-Development Web-development is the second most popular application for Python in 2019. Instagram use Python in combination with Django (Python framework). Spotify use Python for about 80% of their backend services and Facebook uses Python for image processing. 2019 trends for Python show that developers are favouring Django, CherryPy, Flask and Pyramid when using Python for web development. Similarly, employers are actively seeking out Python developers with Django experience. DevOps Next on the list for Python is DevOps. Python is a great fit for DevOps due to its’ flexibility and accessibility. Python enables a DevOps team to build web applications, data visualizations, and to improve their workflow with custom utilities. Python developers with DevOps and Django experience are hot on the market for 2019. Machine Learning An upcoming entry to the list is machine learning. Machine learning is a prominent topic in the AI sphere with AI hailing the media spotlight recently. Python and machine learning go hand in hand due to the abundance of libraries and frameworks suitable for machine learning such as NumPy, SciPy, Scikit-learn, TensorFlow and Pandas. As previously mentioned, employers are actively seeking Python developers with experience of these libraries and frameworks. If you’re a python developer looking to ensure your tech stack is up to date, these are the skills that employers are actively seeking in 2019 (not including the libraries and frameworks mentioned earlier); AWS API Agile Docker Linux Cloud Computing Machine Learning JavaScript Java Git SQL React Flask Of course, the necessity of these skills depends on how you use Python. If you’re a machine learning engineer, you don’t need to have a lot of Django experience, and so on. If you are a developer considering learning Python, we highly recommend you do. Data science and machine learning are exploding with demand for developers increasing year on year within these domains. Python is easier than other major languages to learn and has a huge community that provides support to struggling developers. Lastly, python developers are among the highest paid developers, especially in machine learning and data analysis roles.

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Most in Demand Tech Jobs in 2019

Most in Demand Tech Jobs in 2019

Technology is moving at such a rapid pace that we are at a point where jobs that didn’t exist a few years ago such as data science are now some of the highest paid and most recruited for positions. Emerging technologies continue to be the catalyst for increasing demand as there are clear shortages of suitable talent for roles that simply didn’t exist before the technology emerged. Here are three of the most in demand tech roles across the EU for 2019. Cybersecurity Professionals European firms are poised to hire a large number of cyber-security professionals in the next 12 months to fight the increasing threat posed by hackers. A survey conducted by the International Information System Security Certification Consortium (ISC)² conveyed that up to 38% of European firms are set to increase their cyber-security teams by up to 15% in a bid to protect company information from potential cyber-attacks. The survey also relayed the massive talent shortage of cyber-security professionals within the EU that is projected to rise to 350,000 by 2022. This has led to a significant rise in salary and remuneration packages being offered to cyber-security professionals. Full Stack Developers We have seen a lot of companies seeking to remove the traditional departmental gap between backend and frontend developers by moving towards more agile and scrum methodologies. Full stack developers are able to seamlessly integrate the software layers and are aptly suited to work on cross-functional teams. Furthermore, start-ups actively seek out full stack developers due to their wide range of skills, they understand the full cycle of software development and can be a one man band in the early stages of a start-up. As a result, demand for full stack developers is increasing year on year with Indeed statistics portraying a 607% increase in the UK and a 207% increase in the US between 2015-2018. ​Data Scientists Data science is a vibrant field to be in at the moment. It carries a lot of dynamism in terms of the skillsets that candidates need to be successful, as well as the impacts that good data science can have on an organisation. In 2017, a report by the European Commission signified that the number of data professionals will increase year on year by approximately 14.1% by 2020. As data science is a relatively new field, there is a clear talent shortage with the European Commission estimating that 769,00 data science positions will go unfilled by 2020. Data science is a lucrative career being the highest paid profession on Glassdoor (in the US) for 4 years running with a median salary of $95,459. European counterparts such as the Netherlands and the UK offer a median salary of €69,000 and €65,000 respectively. Switzerland offers the highest salary in the EU with a median salary of €115,000. Machine learning and AI are two other areas within data science that are ones to watch. These innovative activities are very new but hold substantial future potential as they can be effectively implemented to improve business processes and products in a wide variety of industries. From predictive analytics to self-driving cars in the automation industry, this technology is going to influence the majority of industries in the future. Machine learning is one of the fastest growing jobs on LinkedIn with data showing that there are now 9.8 times more machine learning engineers than there was five years ago. The roles here presented are just a fraction of the growing roles within IT. Other prevalent jobs that are on the rise include; Web Application Developer Computer Systems Analyst Data Analyst & Data Administrator Mobile App Developer Market Research Analyst Blockchain Specialist UX & UI Developer

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C++ Trends & Demand for Developers

C++ Trends & Demand for Developers

C is a middle level programming language developed by Dennis Ritchie during the 1970’s in his time at AT&T Bell Labs. He was seeking to redesign the UNIX operating system designed by Ken Thompson two years prior to enable the system to be used on multiple computers. The new language C offered both high-level functionality and the detailed features required to program an operating system. The inception of C++ began in 1979 when Bjarne Stroustrup was working on his Ph.D. thesis. Bjarne was fascinated by object-orientated approach and began working on C with classes; he started to create a new language that had the features of C and the object-orientated paradigm. C++ was first coined in 1983 and was officially released in October of 1985. C++ was officially standardised in 1998 and has continually evolved with major revisions taking place in 2003, 2011, 2014 and 2017. C++ is often mislabelled as an object-orientated language, it is actually a concept independent programming language. From a developer’s perspective, C++ is a notoriously complex language to master for a variety of reasons. For one, you have to come up with your own strategy, structure, and methodology when you use C++, there is no hints that tell you how to write your code. Whereas other languages are purposely deigned to be easy and quick to learn, C++ is the total opposite. C++ is powerful, fast and effective providing excellent concurrency support. C++ is great for applications where high performance and low latency are priority. It supports a wide range of applications from 3D graphics in games to real-time mathematical solutions for finance. Its versatile nature has led to C++ spreading to a multitude of different industries from transportation to manufacturing to game development. C++ is a staple language in the software development sphere maintaining its popularity and demand for year after year. In today’s climate, new technologies, frameworks and languages are consistently emerging, often disrupting the market causing the popularity of other languages to dissipate. C++ seems to hold its own with developers wanting to learn the language and employers looking for developers with C++ in their tech stack. TIOBE Index ranked C++ as the third most popular language of 2018, just behind Java and C. C++ has maintained this third-place spot since 2002. PYPL, a survey that looks at how often language tutorials are searched for on Google has C++ ranked in sixth place signifying that developers are actively upskilling their C++ skills. This is further substantiated by GitHub’s “Language Wanted” rankings, languages that developers have not learned yet but wish to in the future. C++ was ranked in 6th place again with 10% of GitHub’s community stating they intend to learn the language. Demand for C++ professionals is constant as it is used in so many different industries. One method of calculating demand for C++ professionals to analyse job data citing C++ as a requirement. C++ came in fourth in terms of IT jobs citing the language as a requirement, just behind JavaScript on Indeed, the world’s largest search engine for jobs. We have seen demand increase for C++ professionals for roles such a game software engineer, system software developer and embedded engineer. There have been warnings that C++ will inevitably fade out of existence as technology and other languages continue to emerge. C++’s ability to run legacy code may no longer hold value in the future. However, we have seen employers favouring C++ as programmers can be more productive using a basic language that fits so many applications. The future is yet to be written for C++ but demand for and popularity of the language has stagnated since 2013 without any indications of this trend improving going forward.

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Automation - The Impact on Human Jobs

Automation - The Impact on Human Jobs

The robots are coming. Automation is a polarizing topic as despite the benefits and opportunities that new automation technologies offer, the impact on human jobs is a real concern. Regular reports warn that the automation apocalypse is coming within the next decade with studies from Oxford and McKinsey predicting that automation will eliminate 30 – 60% of all workplace tasks. These tasks which are carried out by human workers account for a significant portion of employment in some industries. Not all jobs are created equally, and some are more likely to be automated out of existence in the near future. To truly understand the reality of the threat that automation poses, we must examine examples of jobs that are at a high risk of automation. The long-standing staple of the taxi driver is likely to be a profession of the past. The taxi industry has already been turned on its head in a few short years with the introduction of apps such as Uber and Lyft. The human element of ordering a taxi has already been automated out of existence, is the driver next? Autonomous vehicles are no longer science fiction with major automotive brands heavily investing in autonomous technology. As the technology continues to advance and proliferate throughout society, it’s likely the lone taxi driver will simply be replaced by technology. The ‘Future of Employment’ have ranked taxi driver as one of the ‘least safe’ jobs with an 89% chance of being automated. On a similar note, truck/delivery drivers are likely to be a thing of the past alongside taxi drivers. We have already seen the first warning signs with Tesla’s fully electric autonomous semi-truck entering the market. Imagine; you order an item through a well-known online retailers’ website. All payment is made securely through the website, you provide your delivery address while ordering, but instead of your order being collected from a warehouse by an outsourced delivery partner, which is often the case at the moment, a dedicated robot tracks the order from the warehouse/ It is then loaded into a self-driving vehicle/drone and delivered safely to you, with no human interaction whatsoever. Amazon have already trialled this new tech using drones to offer same-day delivery on small Amazon purchases. US Netflix series Black Mirror provides many insights into the future of our society and how technology influences it. Take episode three of season four, Crocodile. In this episode, an autonomous pizza truck delivers a pizza while cooking it in-transit. It sounds like science fiction yet in Silicon Valley, a company called Zume is pioneering the concept of a ‘robot pizza truck’. An order is placed through the Zume app, the self-driving truck begins its journey to the destination address, and by the time it has arrived at the delivery address, the robot chef will have a freshly baked pizza ready for delivery. Household brand PizzaHut came out in 2018 saying it was teaming up with Toyota to bring the robot pizza truck concept to life. The ‘Future of Employment’ has ranked fast food cook at an 81% risk of being automated. The pizza truck will automate both fast food cook and delivery driver out of existence. As well as the food, e-commerce and driving industries, another area which faces potential extinction in the coming years is that of customer service. Customer service spans across a range of roles, yet a significant portion of these roles are on the way out. UI chatbots continue to proliferate throughout many large organisations removing the need for customer support agents. As this technology continues to improve and become a more cost and time efficient method of customer support, why would companies choose humans? Evidently, automation poses a higher risk to some industries more than others. Jobs that are highly routine with a high proportion of repetitive tasks are most at risk of being automated in the near future. However, this does not mean the job in its entirety will disappear, automation will change how we work. The reinvention and re-engineering of jobs is the key story, not job losses. For example, automating the last kilometre of truck deliveries is an inconceivable task at the movement, the journey still requires a qualified human driver. Customer service agents can upskill and work in other areas of the business such as sales or account management. Technology and automation have always changed how we work throughout history without causing an unemployment apocalypse. Automation will no doubt change how we work but the threat it poses can be mitigated by continuous upskilling and reskilling. Jobs will change, it important that we change as well.