Do you need support for Big Data analytics? IT Svit can help!
Every business that aims to run its infrastructure efficiently thinks of using Big Data analytics for optimizing the IT operations. Big Data technologies can be largely applied to two main effects: they can provide more value to your customers by empowering your products and services through real-time data processing tools like Apache Hadoop or Apache Spark — or implement open-source Machine Learning models to monitor your cloud infrastructure and provide predictive analytics to optimize your IT operations.
Thus said, getting access to decent expertise with Big Data analytics is quite complicated for a startup. Most of skilled data scientists work for either huge enterprise business, for cloud computing providers like Amazon Web Services or Google Cloud Platform or for Managed Service providers like IT Svit. Below we explain the reasons behind each approach.
When data scientists decide to work for a large enterprise, they aim for the fat paycheck. They often have to deal with legacy infrastructure, outdated tools, workflows, products and services, they work on projects that take years to accomplish — but they have a stable income and the possibility to master new Big Data technologies while working on their projects. Unfortunately, many of these data scientists stop growing professionally and become too comfortable with their currently used technology stack. The rest of Big Data analysts employed with enterprise businesses outgrow their routine with time and often leave for a cloud service provider or an IT outsourcing company. Why so?
Big Data analysts working for cloud platforms have ample opportunities to master the latest technology and best practices in Big Data analytics and systems, which is definitely good. however, AWS specialists master AWS products and services like Amazon ERM, Amazon Kinesis, etc. Should they want to learn Google Cloud products or MS Azure services — they need to do it on their own time. Besides, most of the customer requests regarding Big Data support are quite similar, so the cloud employment results in even more routine. This is why most of the data scientists that work for the cloud platforms ultimately leave for the IT outsourcing field. And for a good reason.
Working for an IT services provider like IT Svit, Big Data analysts have a wide variety of projects to choose from. They can investigate the latest cloud-specific and open-source tools and learn the best practices of building resilient Big Data platforms. As most of the projects are startups, the Big Data analysts don’t work with the legacy systems. They receive carte-blanche and are able to design and implement elegant, resilient and cost-efficient Big Data solutions. As all the projects are rather short, data scientists can finish them and reach the set business goals before they are overwhelmed with the routine. Thus said, both the IT services providers and the startups have a win-win situation, as the customers gain instant access to top-notch talents with decent hands-on expertise, while the data scientists have a variety of projects to choose from and can improve their skills very quickly.
Cloud infrastructure for Big Data analytics
The main challenge on the way to deploying and running an efficient Big Data platform is the lack of DevOps skills and understanding of the cloud infrastructure management best practices and workflows. Thus said, without a decent DevOps expertise and technology stack, it is quite hard to design and deploy an infrastructure capable of dealing with petabytes of data storage and processing it in real-time to provide feasible business intelligence insights.
Thus said, the challenge is not in hiring a decent DevOps engineer (which is quite a challenging tasks by itself). The challenge lies in hiring the DevOps engineer with ample experience in building the cloud infrastructure required to run a Big Data platform — as incorrect system configuration can lead to quite significant losses. Most startups prefer to work with cloud platforms to minimize this risk, but they go straight to another pitfall — vendor lock-in, as if your Big Data analytics solution is built around Amazon Kinesis, you cannot move to another platform without having to rebuild everything from scratch.
This is why many businesses prefer to future-proof their IT operations by hiring Managed Services Providers like IT Svit to deliver cloud infrastructure for Big Data analytics. We have ample DevOps and data processing expertise, so our data scientists can design a bespoke Big Data solution uniquely fit to meet the project requirements — and our DevOps engineers can deploy a cost-efficient cloud infrastructure required to make it work.
Thus said, whether you already have data analytics solution and require support for an update in Big Data workflows, or are just planning to implement a bespoke Big Data platform — IT Svit can help! We can train and deploy a Machine Learning model to help run your cloud infrastructure cost-efficiently — or we can develop and implement data processing features for your products and services, to drive more value to your customers. Should you need support for Big Data processes — contact us right away, we would be glad to assist!
