Data science is an evolving profession. Artificial intelligence is also changing at a remarkable pace. A number of new platforms and tools are being regularly rolled out to help data scientists do their jobs more effectively and easily.
Savvy data scientists and AI developers are keeping up with trends and learning the new technology that can help them work more efficiently. One of the biggest trends is the introduction of low code and no-code data platforms.
No-Code Platforms Are the Future of Data Science and AI
There is a significant shift in tools, processes, and skills being used in the enterprise. As a result, low-code/no-code next-gen technologies are starting to reach the enterprise. As enterprises increasingly look to outsource or bring in third-party providers, they are starting to embrace low-code/no-code tools.
There are a lot of great reasons to embrace no-code platforms. One of them is the fact that they make AI technology more available to businesses. This is a topic that Harvard Business Review author Jonathon Reilly discussed in an article back in November.
No-code platforms are also becoming more valuable for data scientists. One example is with Obviously AI. This is a company that boasts its commitment to providing data science solutions to companies without the need to create code. Dubbed a “No Code Startup for Data Scientists”, Obviously AI received $4.7 million in seed funding last summer, according to a report by TechCrunch. This underscores the tremendous demand for a codeless approach to data science.
In some cases, the new tools are replacing the on-premise enterprise solutions that have been custom-developed in the past, which creates valuable new features for data scientists. In other cases, especially where a third-party solution is brought into an organization on a more temporary basis, low-code/no-code platforms provide the perfect alternative to outsourcing.
These low-code/no-code tools can be used by experienced application experts as well as subject matter experts who have little to no programming knowledge, which makes them very popular with enterprises because no-code tools speed up development time and cost savings without the need for hiring expensive developer resources. Although most data scientists have at least moderate programming capabilities, most of them are not hardcore experts in the various languages they might need to be proficient in to develop applications from scratch. They also have better things to do than spend hours debugging code.
Here are five reasons why data scientists in many enterprises are turning to low-code/no-code platforms.
1. Overwhelmed development teams and talent shortage
At the most basic level, IT teams are becoming increasingly overwhelmed with so many applications, digital journeys, and tools being developed. Data scientists are no exception.
In many cases, there is a significant time lag between a request and when that request is fulfilled. This takes up a lot of the team’s time and creates frustration among various stakeholders. Given the growing number of data requests that organizations face, data scientists can’t contribute to this bottleneck.
In addition, having to hire expensive resources means that organizations are paying out significant sums for very niche skill sets. Not only does this contribute to the high cost of developing data science projects, but also directly impacts budget and timelines. Low-code/no-code tools have a much lower barrier to entry and expertise required, so can be used by experts as well as those with limited experience.
2. Demand for new apps is increasing exponentially
As more and more applications come online, demand for new applications is quickly outstripping the ability of development teams to produce them. A recent McKinsey report found that 40% of application development projects fail to meet the intended business goals.
The research also shows that Over 60% of the Enterprise Software projects are delivered late—with 16% being double the amount of time anticipated or more! Data scientists can help streamline their delivery by using the right platforms.
3. Enterprises recognize third-party solutions as a viable development platform
Enterprises are starting to recognize that giving non-technical employees no-code tools to accomplish certain tasks and processes reduces costs and also contributes to increased agility. Given the evolving nature and growing complexity of data science projects, this makes no-code tools a huge selling point.
This is especially true for many of the application development initiatives that enterprises embark upon each year, which require either small scale projects or outside expertise.
Delegating these tasks to citizen developments can be very cost effective and provide quick access to specific skill sets or domain knowledge.
4. Need for speed
Everyone wants to be “agile” these days, but the truth is that most organizations still tend to move at a rather sluggish pace compared with the rate of technology change. Even data scientists struggle to handle these projects efficiently.
Enterprises understand that their advantage in the market can be eroded quickly if they don’t embrace new technologies and innovate at a faster rate. They want their data scientists to have the best technology at their fingertips.
Low-code/no code platforms provide a quick route to market for new ideas or concepts, as well as the ability to build out proof-of-concept apps that can be used internally as demos before going through a full development cycle. Enterprise-grade no-code platforms also integrate well with existing enterprise technologies, including CRM systems.
5. Need for cost savings
Every IT department faces the same problem of diminishing budgets and increasing pressures to prove ROI for every initiative. Low-code/no code platforms are often relatively inexpensive, which means they are very affordable even if only used on a temporary basis to build out proof of concepts.
These platforms also have a low learning curve, so can be picked up by subject-matter experts with little or no formal development training. This reduces the need for expensive developer resources and speeds up development time.
In conclusion, enterprises are increasingly turning to low-code/no code platforms as an agile method of developing new applications that let them turn new ideas into working solutions, and then scale up to the production environment when ready.
The market for these platforms is growing quickly and there are lots of good options available at different price points.
One area of enterprise digital transformation that can be solved with no-code is customer data collection, such as forms and paperwork in insurance and banking. With EasySend’s no-code platform you can build forms that are integrated into your CRM and internal systems without having to wait months on the IT department, while ensuring that your customers get great digital experience at every step.
Codeless Platforms Are the Future of Data Science
More data scientists are relying on platforms that don’t require coding. This saves them time and helps process tasks much more efficiently.