As companies become more overwhelmed with data and eager to leverage it for better business performance, data science implementation steadily gains popularity. After all, who wouldn’t want to have access to real-time analytics, accurate sales forecasts, and other opportunities that this technology delivers?
However, before undertaking development, it’s important for business leaders to understand that there are several data science challenges that can arise along the way. Being armed with information on the difficulties you may face and how to solve them is crucial for the success of your project.
So, in today’s post, we will rely on the years we have spent delivering data science services to share some potential problems you ought to be prepared for. Let’s get started.
6 Common Challenges of Data Science Projects
No matter how many software development initiatives you’ve already worked on, every new one can throw curveballs at you and cause project delays. Naturally, leaders want to minimize the impact of these surprising difficulties, and for that, preparation is key.
Whether you already know what kind of a data science project you want to pursue or are just looking for a consultation on this subject, finding skilled specialists will be the first challenge you face.
You may come to realize that you don’t have the needed in-house resources for a successful completion of the initiative. So, you’ll start the hunt for data science experts but quickly recognize that they are either unavailable or lack domain-specific knowledge you require.
Depending on the project goal, it’s important for your IT team to not only have data scientists, developers, and business analysts but potentially Big Data architects and machine learning engineers as well. After all, if you’re building a large-scale solution or are revamping the entire IT infrastructure, you’ll need people who can deliver an excellent result.
Since skilled tech talent with domain-specific expertise is hard to come by these days, it might be a good idea to consider outsourcing development. That way, you’ll be able to skip the time-consuming efforts of recruitment and partner with a vendor that can advise you on the best course of action in your unique business case.
Of course, everything depends on the scale of your project and the capabilities of your existing team. However, if you run into the challenge of finding the right data science professionals, don’t exclude the possibility of outsourcing.
Watch our webinar to unveil the tricks of onboarding a tech partner and incorporating it into the process to foster your product delivery.
Get Help Avoiding Data Science Challenges
The corporate world is well on its way to completely embracing data science and business analytics, and the above-outlined roadblocks won’t stand in the way of adoption. Nonetheless, it’s always good to be prepared for any difficulties you may face within your IT project.
Velvetech’s team has ample expertise in delivering data science services and accounting for the challenges that a project within a specific industry may present. So, if you’re looking for help with your initiative, don’t hesitate to reach out to our team.
Our specialists will quickly get on board and recommend optimal ways of achieving your unique business goals. Together, we’ll swiftly deal with any issues that may arise during development or after deployment.