Remote work isn't the future. It's a current reality, with nearly 75% of U.S. workers working remotely at least some of the time, according to Owl Labs' State of Remote Work 2019 Report. Data scientists and other data professionals are no exception to the rule and are able to bring their work home with them if and when the need, or desire, arises. However, a switch to remote work isn't as straightforward as simply taking a work laptop home.
As the COVID-19 pandemic continues to spread, remote working is on the rise. The current situation continues to evolve, and those who are able to work from home are looking for ways to work effectively and efficiently. All personas (marketers, salespeople, HR, etc.) are running into troubles along the way and are navigating the best way to maintain a virtual workforce. However, data professionals like data scientists are facing acute problems when it comes to computing power and ensuring that data is secure and compliant.
Serverless computing, the cloud, and data experts
The move away from on-premises infrastructure has helped many companies enable data work anywhere one has access to the cloud—in other words, anywhere with internet access. Data scientists, when looking to solve business problems such as fraud detection, dynamic pricing, recommendation systems, and much more, look for data science and machine learning platform, which offer cloud solutions which would allow for this flexibility. One G2 reviewer wrote that the tool they were using is "extremely easy and efficient for building models in the cloud without having to worry about infrastructure."
However, not all data experts have the luxury of working in the cloud for a number of reasons, including data security and issues related to latency. In cases such as health care, strict regulations such as HIPAA, require that data be secure. Although it is possible to ensure this security in the cloud, it can be more difficult and complicated to do so. For cases such as financial services, in which time is money, every second counts when it comes to performing computations. Therefore, on-premises solutions can be vital for some professionals, such as those in the health care industry and government sector, where privacy compliance is particularly strict and sometimes vital.
Challenges data professionals face working from home
On-premises solutions come with their own challenges in terms of remote data access, but these challenges are not insurmountable. By using virtual desktop infrastructure (VDI), workers can access the data they need, giving them the ability to query it, analyze it, and derive insights from it. However, privacy considerations can be challenging, with VPNs getting overloaded by too many people accessing them at once.
A particularly difficult scenario arises when there are faults or concerns with the on-premises hardware, as cases arise in which one needs to be onsite to reset it. Some companies have resorted to RFID tags on the hardware for maintenance purposes.
Communication, especially in the distributed time in which we are living, is also a key concern for data professionals. Although some data tools like data science and machine learning platforms and machine learning data catalogs include collaboration and communication tools, features and functionality vary. In some cases, companies which handle particularly sensitive data are looking to introduce new collaboration tools but are finding it challenging to find a solution that meets the standards of their legal teams.
Moving forward with remote working
Remote working comes with its challenges for data professionals, but it is increasingly enhanced and enabled by cloud solutions. With the proper privacy procedures in place, compliant communication tools, and competent compute from their computers, businesses can better support their workforce and help employees work safely and efficiently.
