IT and Data Education Predictions: Democratizing Tech Skills

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data educationIn five to ten years, said Johan den Haan, the CTO in charge of R&D and Cloud Operations at Mendix, the number of computer scientists and data professionals using 3gl programming languages (Java, BASIC, C+) “will not” grow that much. Instead, this limited number of them will focus on creating the engines and compilers, and these will be used by people with more soft skills and fewer tech skills.

This is made possible by the evolution of low-code development platforms and accessible dashboards. In describing Mendix’s beginnings and how they are aiding in the such transformation, Johan said:

“We started Mendix because we saw that a lot of software projects kept failing, for several reasons. It took way too much time, and there were communication problems between business and IT. This has been a problem for a long time. So, we’ve been working on creating tools to make higher level visual models, to define software, and then automatically generate working software.”

Such advancements assure a common language between the IT/data professionals and less experienced people, with more of a business background. “Both work to create these visual models, and collaborate on these models,” said Johan. “Essentially having a common language to express their ideas. And that’s why we created the software.” The Mendix platform allows developers to create software upwards of ten times faster than with traditional programming languages, which then makes local collaboration that much more powerful.

They have eliminated the whole communications problem by removing the gap between the two worlds of business and IT, and this is a growing trend within the entire industry and is being demonstrated in educational programs as well.

The Democratization of Tech Skills

According to Johan den Haan, “the supply of tech talent will not meet the demand in 2018, forcing an increase in the democratization of tech skills.” The pace of software and technology development is increasing exponentially, at rates never seen before. He said that schools “simply cannot churn out qualified developers fast enough to meet the demand for individuals with deep technical skills.” This is true in 2018, but also moving well into the future.

This is forcing organizations to look at their software development teams, mid- and long-range plans, along with other possibilities, to better meet the demands of the industry.

“There is a growing faction of low-code resources available,” he said. “These will help to democratize tech skills and empower enterprises to transition digital transformation from the tech to transforming their business.”

Low-Code Development Platforms and Broadening the Development Range

Low-code development platforms (LCDPs) originated from a combination of fourth-generation programming languages and the rapid application development tools, which were used in the 1990s and 2000s. LCDPs are based on principles used in automatic code generation, model-driven design, and visual programming. LCDPs have promoted new approaches for the idea of end-user development, and Mendix has been paying attention. Johan stated:

“What you now see, is that we are in the era of the Internet of Things, and of Machine Learning. We are basically mechanizing the brains of humans. People don’t have to make all the decisions anymore, or do all the analytics. With Machine Learning, we enable computers to see, to hear, to read, and that’s a whole new input channel that is now coming alive. And this leads to an enormous amount of data.”


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A low-code development platform supports the easy creation of application software. It does this by using graphical user interfaces and their configurations, instead of traditional computer programming. These platforms can produce operational applications, or use minimal coding, to extend an applications functionality. LCDPs minimize the amount of hand-coding that is needed, and allows for a faster delivery of the applications. A major benefit of this platform is the broader range of people who can work on the app’s development. Additionally, LCDPs lower the cost of training, setup, and deployment.

Mendix is a member of the Cloud Foundry initiative and makes use of the Open Source Platform to deliver enterprise-class scalability. The Mendix R&D team actively contributes to the Cloud Foundry project, benefiting the entire Cloud community as a whole. They are part of a business ecosystem, called Pivotal Partnership as well. The Pivotal Partnership is a part of their business strategy, and includes integrating the Cloud Foundry’s Platform-as-a-Service (PaaS) framework with its fast “app platform-as-a-service.”

The Mendix Cloud platform is based on its abilities to integrate with Amazon Web Services, Machine Learning, IBM Watson, IoT, and other Cloud elements in building applications. Their focus is providing developers with the ability to create Smart Apps. According to Johan, “Mendix is based on visual models for creating web and mobile apps – we use our own modelling languages known as DSLs, or domain specific languages, which makes things easy for users.”

Their platform allows for “scaling, health management, and high availability,” while also being a part of the Open Source Movement. Mendix seeks to be a prominent voice addressing the growing need of preparing organizations to meet the IT and Data Education demands of the future.

Data Education and Machine Learning Predictions

Officially Mendix’s mission is “to empower IT and Business teams to collaborate like never before, while experiencing unmatched speed and control.” Mendix’s primary focus is to provide comprehensive tools, and the best practices, for an application’s “entire” lifecycle. This includes testing, deploying, and iterating.

During the interview, Johan den Haan made some predictions about the future of Machine Learning, Data Science, and Data Education:

“The next platform is already coming up, which will be much more disruptive in a lot of industries. Machine Learning is not something that happens automatically. Machine Learning is not generic intelligence, it’s a very specifically trained algorithm, that’s helping us to do something. For a computer to see, it needs to be trained, and that requires a lot of trained professionals.”

If and organizations cannot train enough people to do software development, or Data Analytics, in the traditional way, then they need to change the way they develop software, said Johan. More people need to be easily enabled to deliver the technology that enterprises need. “I think that’s exactly what you’ll see more and more of.” With a technology such as low-code, organizations are democratizing software development.

“Machine Learning is now mechanizing, or automating, interns. You can hire an intern for a very specific task, train the intern to do so, and that’s basically the level of work that Machine Learning will be able to take over, in the relatively short term, but then you can scale it to millions.”

Tech schools are now putting less emphasis on coding, and more on innovation, he said. “I don’t believe everyone should be taught to program. We should make sure people can be more productive in creating software.” He remarked that he sees education programs across the spectrum, combining soft skills and business skills with education in Data Science, programming, and other technical areas.

“Despite widespread acceptance that social, mobile, analytics, and Cloud should have a place in every company’s future, it’s wise to demonstrate how the business value of digital solutions can and will be managed and measured. As the role of IT departments evolves, so too should their capabilities to manage and measure value.”

To help close this skills gap, Mendix has invested in creating a University Program. University professors can use Mendix for free to teach their students cutting-edge approaches to application development so they can enter the workforce with the skills demanded by top employers. Currently 36 universities from around the world are using Mendix as part of their curriculum.

Such predictions are being seen throughout the Data Management industry. The future of IT and Data education is one where universities and other technical schools still appropriately educate professionals to work in the industry, while organizations also become more proactive with training their existing employees in the skills necessary for success in the new data-driven world.


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