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How Low-Code Is Bridging the Gap Between Data Scientists and Businesses

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Read more about author Nahla Davies.

Coding is a foreign language for many high-level and C-suite executives who lead corporations today. However, it’s hard to find anyone who doesn’t understand the importance of technology and how our future will hinge on mastering it.

Although many computer scientists argue in favor of low-code software for data scientists, there is an argument to be heard regarding the benefits of low-code for business operations. Data Science is, at heart, the practice of working with others to handle large swathes of information. Hard skills and soft skills govern the best use of data, yet in many corporations, business executives have little to no interaction with data scientists.

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This article will discuss how low-code can unite companies as they seek to work together to serve a common purpose. Low-code software can be a meeting ground for data scientists and C-suite managers, uniting vision with purpose and execution.

Illustrating the Data Story

Data scientists can look at mounds of data, helping them detect patterns that provide vital insights into a company’s future. The data can also help pinpoint potential strategies for enhancing revenue. It’s at this moment that others in an organization understand the importance of Data Science and how it can guide future decisions.

Of course, these breakthroughs don’t occur every day. In fact, many data scientists feel like they need to justify their positions because those in power need to see consistent results from data analysis. Much of a data scientist’s most important work is explaining what they do and backing findings up with data that can illustrate their cause. Other data projects can become delayed or suffer from a lack of funding because the purpose isn’t very clear to someone who doesn’t work with data.

It is helpful when companies better understand which problems data can resolve, resulting in more realistic and achievable goals for their teams. When business leaders are empowered to understand basic Data Science, it brings the two factions closer to understanding each other and working together to their full capacities. Low-code software empowers even the technologically illiterate employee, who doesn’t quite understand what removing a virus in a MacBook Pro means, to play an integral role in the Data Science journey. 

With low-code, benefits extend beyond increasing efficiency for data scientists. Low-code software can help bring business leaders to the 21st century by helping them understand and work with data themselves. Furthermore, even the most complicated technologies such as machine learning can be more transparent for all.

Understanding the Data Journey

When departments have a better understanding of how data science works, outcomes improve. Sales teams, for example, understand the sales enablement framework and current deadlines better than anyone else. They can be empowered to use data to propel highly targeted prospecting efforts and better monitor their progress towards a specific goal. Knowledge of data enables sales leaders to ask bespoke questions from data scientists to maximize how organizations use data.

When C-suite executives like CEOs, VPs, and business operations managers understand data, it can improve focus on the right type of data. And when they understand how data is gathered, teams can work across the board to drive results. Risk mitigation, innovation, budget needs, and potential cost savings can all be illuminated by business leaders that understand data. Empowering citizen data scientists to contribute to the overall data effort can result in a huge return on investment. 

Delving into the Data

By involving more people in the data journey, organizations provide new and relevant skills to their employees of all levels. Data capture rates can dramatically increase, along with more eyes capable of detecting patterns that will make a tangible difference in the operation of a business.

As it turns out, it’s not just computer scientists who can derive insights from data. Data Literacy is an easily learned skill and can improve outcomes throughout the entire organization. Although very few can do the job of a data scientist (which can get quite complex in certain areas), it can democratize and increase access to data that can better inform decisions being made across all company levels.

The future of business involves artificial intelligence, machine learning, predictive analytics, visualization, and data exploration. These are all high-level areas of expertise that necessitate hiring an experienced data scientist. However, the very lowest level of Data Science – the simple collection and recording of relevant data – is something that everyone throughout an organization can do.

The more an organization can help with wrangling relevant data, the more time data scientists have for focusing on the more complex areas. This can be a key competitive advantage in a landscape where having better technology can make or break a company’s success. 

Conclusion

Our future is likely to be dominated by big data. The proper gathering and analysis of data has been shown to superpower marketing campaigns, provide priceless insight into business operations, and is now even boosting the growth of smart buildings and smart cities. It’s clear that there is no way to avoid being part of this data-powered process, even if it is only a passive role. 

Using low-code software to educate and train citizen data scientists, even those unfamiliar with high-tech concepts, can help them find better solutions and optimize their work. This key difference can help power organizations and hand them a competitive advantage as we head into an increasingly digital and data-driven world. 

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