Many of the giants of the modern global economy are companies with a focus on technology. Due to the dominance of technology to give companies a competitive advantage, many businesses work to create their own software to provide superior customer service. Though this is a laudable goal, it can be easier said than done. With some businesses launching quite cumbersome systems, and others amazing technical assistance for customers worldwide. Like Shiply in shipping for instance, where you can control your own workload as a customer trucker, shipping or logistics company, and be your own boss.

To assist our readers in creating workable applications of their own, we’ve turned to the example set by Freight Hub Group and its TruckHub software. Under the guidance of CEO Luis Lopez, the third-party logistics company has helped highlight a method of software development that can be applied across many different industries.

Know your industry

This may seem apparent to some, but it can be surprising how many business owners attempt to implement technology into a new venture without fully understanding the industry in which they are working. This type of “leap before you look” approach can often be doomed to failure as early mistakes may steamroll into critical downfalls as time passes. Without a firm grasp of the unique challenges of a particular industry, a business leader may find themselves ill-equipped to articulate to developers exactly what issues need to be solved through the creation of a piece of technology.

The example of Freight Hub Group CEO Luis Lopez makes for an instructive example to show the type of legwork that can help you gain a more complete understanding of an industry. The shipping professional’s experience in his field dates back to his time in high school, where he was first introduced to the work through a part-time job. That first exposure to third-party logistics not only taught him many fundamentals that are still relevant in the field to this day, it also gave him an understanding of areas that could be improved upon. One such area that caught his eye was the lack of flexibility in the industry, and the opportunity to create a company that could be more agile in its ability to serve client needs.

Know your clients

That simple observation highlights a second important concept that can be critical for any business owner seeking to design technology to aid in their goals. It is absolutely critical to know and understand your clients. This idea goes beyond an understanding of the industry itself which, though important, is often focused on the nuts and bolts of delivering services. By contrast, knowing your clients hinges on understanding the pain points on their end and better understanding what might be done in order to more fully achieve their goals.

To continue drawing from the example of the third-party logistics company, the CEO’s understanding of a client’s need for flexibility was a direct inspiration for his push to create his TruckHub platform. One early way in which he saw this need manifest was through his observations of the handling and shipping of hazardous materials. Early in his career, he noticed that regulations and other burdens created a slow-moving environment for this type of transportation, causing unnecessary bottlenecks for clients. Through this observation, he worked to create a more streamlined hazardous material handling service that offered same-day pick-up to allow the company to better meet client needs.

Take feedback

No piece of software is created in a vacuum. Though a business owner or design team may come up with the original concept for a piece of technology in order to solve or alleviate a perceived problem, it is the users themselves who ultimately decide its worth. For this reason, keeping an open line of communication with users as to how to best serve their needs can make the difference between a successful product launch or a lackluster attempt.

The launch of TruckHub illustrates this concept perfectly. The application was the result of a long design process with input from a range of sources. Though Luis Lopez was instrumental in the initial conception of the software, he and his design team made the decision early on to solicit input from actual clients. This led to the design process being heavily guided by the desires of clients as the company sought to implement features that had been explicitly requested through user feedback. This has been one of the top factors leading to the successful launch of the TruckHub platform.

Feature selection

Ultimately, the design and implementation of a piece of software comes down to the prioritization of features. The decision to include or exclude certain features can be one of the most important parts of the design process and can contribute greatly to an application’s success. Though the above process of soliciting user feedback can be a great determiner of which features to focus on, it is generally left up to the individuals in charge of the software to make the final decisions regarding implementation.

To better understand this idea, let’s take a quick look at the features that have been implemented in the software created for Freight Hub Group. The TruckHub application is a tool used by clients to track the status and whereabouts of their goods throughout the transportation journey. It also allows dispatchers, drivers, and shippers to share contact information and rate quotes for business owners seeking to utilize the company’s transportation services. The use of GPS and real-time updates to achieve the software’s goals helps to illustrate how focused the platform is on streamlined client-driven features.

While technology is often at the heart of many of the largest and most successful companies in the modern economy, it can sometimes be tricky to implement on a case by case basis. Rather than act as a deterrent, however, this concept can serve as motivation for business owners to become better educated regarding the specifics of software design and implementation. Looking to the above overview of Freight Hub Group and how CEO Luis Lopez has led the design process for its TruckHub software can be informative. Look for additional resources through the company’s website to get a better idea of this process and to see how you can implement a similar process in your own pursuits.

So you’ve decided you want to learn more about data science. Perhaps you’re seeking a career transition into the field or maybe you just want to be able to better understand the data professionals with whom you work. Whatever the reason, your path can be greatly helped by a guide to resources and topics you can study to learn aspects of this interesting and fast-growing field. We’ve compiled the following overview along with a look at the work of Jonathan Cornelissen, the founder of DataCamp, to do just that. Read on to help find your own path forward in data science.

Professional background

Let’s first take a quick look at the work engaged in by Jonathan Cornelissen and the company he founded to help spread knowledge about his field. He first conceived of his company during his time pursuing his Ph.D. in Econometrics. Through his own studies, he encountered the difficulty of learning R without access to supporting resources. When he was teaching courses where his students were also required to learn the programming language, he witnessed the same difficulty in their efforts as well. He realized that the process could benefit from the advent of an educational platform designed to help in this area.

That idea would eventually lead to the creation of DataCamp, the educational service that has helped over 4 million learners improve their data skills to date. The platform showcases the capacity of such resources to help individuals grow their ability to work with data in a professional environment. Beyond simply teaching a programming language, the focus of the platform also allows students to improve data fluency and better understand the output of more experienced data scientists. In a world that is fast becoming more and more dependent on data, improving these skills can be a worthwhile endeavor for any modern professional.

Improving math skills

For those who are looking to actually transition into the world of data science, a firm foundation in mathematics is a must. Such a foundation allows data scientists to better understand their data and make useful extrapolations from it to help predict the future. Key areas of math that are important in this regard include linear algebra, probability, calculus, and statistics. It’s important to note that a foundation in this area doesn’t mean you need to be an expert, far from it. It does, however, require a degree of familiarization that will allow you to know what is required of you in a given circumstance.

In this regard, the advice that is generally given is to undertake an honest assessment of your math skills and formulate a plan for further knowledge based on that. Even if you’ve taken some related courses before, depending on how long it’s been since you were exposed to the material, you may want to revisit the topics as a refresher. This type of reintroduction can be accomplished through online courses, videos, or self-learning textbooks. Whatever route you choose, be sure to continuously relate the knowledge you’re gaining back to your end goal of becoming more proficient in data science. In other words, make sure you’re staying cognizant of how everything you’re learning will benefit you in the long run.

Explore a programming language

Beyond math, your journey into data science can be greatly helped along by a firm understanding of a relevant programming language. Most data scientists utilize either R or Python as their primary language, and will often use SQL as a supplemental language. Similarly to what Jonathan Cornelissen found in his own studies, you may be helped along on your journey by seeking out online or printed resources that can teach you one of these languages in practice.

However, understanding a programming language for data science goes beyond what is often used for, say, a software developer. Data scientists often make use of specialized toolsets within a programming language to help them accomplish their work and engage in analysis. For instance, popular libraries and visualization tools for Python include Pandas, Numpy, and Matplotlib. If you don’t already have a strong command of these or similar tools, then it can be a good idea to take steps to learn their usage. In this way, you’ll not only be proficient in the programming language of your choice, but also a number of additional tools relevant to data science.

Further learning

Once you’ve improved your abilities in math and programming, you’ll want to dive further into data-specific topics. One relevant field that’s garnering plenty of attention these days is machine learning. This subset of artificial intelligence uses data and neural networks to generate algorithms that can expand on their own and essentially “think” in new and different ways. The field rests on an algorithm’s ability to build upon itself as it’s fed increasing amounts of data. Beyond the connection to data science, the applications of this field are vast, including self-driving cars and more efficient online search methodologies.

For a broader suggestion of a path forward, it can be helpful to follow in the footsteps of Jonathan Cornelissen and actually set out to build a project of your own. In much the same way the entrepreneur saw a need for data learning resources, you can also identify projects of interest and engage in them in order to further your knowledge base. Such projects have the added benefit of demonstrating your newfound abilities to potential employers and might even help you get a job somewhere down the line. Regardless, they can be a great way to explore the field in a way that is interesting and engaging.

If you’re at the beginning of your data science journey, the field might appear overwhelming. While there is certainly plenty of work to be done by the self-learner in order to attain the same level of knowledge as someone with a formal education, the task is accomplishable with determination and hard work. Looking to resources such as the one created by Jonathan Cornelissen can help put you on the path to eventual success in this regard. The more you commit to growing your abilities in this area, the faster you may find a number of opportunities in the field of data science opening up to you.