IT Svit develops Big Data platforms for UK businesses

One of the biggest challenges of Big Data development is that it resembles building a LEGO castle without instruction. Big Data architects have a huge variety of building blocks — programming languages, frameworks, databases and data visualization tools. However, there never is a detailed step-by-step instruction on how to build a perfect Big Data solution that fits your project perfectly. The only guarantee of success is using in-depth expertise and best practices of Big Data platform design. IT Svit provides this expertise and helps UK businesses achieve their Big Data project goals.

We develop any Big Data software for your project

Big Data software can perform various functions within your workflows, from product personalization or enabling certain functions to the optimization of your cloud infrastructure in order to minimize the OPEX and TCO. However, planning, building and managing these solutions requires a thorough knowledge of Data Science and architecture, as well as DevOps Best practices. IT Svit team can provide both components to help your business implement Big Data solutions and gain a competitive edge.

Big Data analytics delivered in real-time

Using Big Data analytics enables OPEX reduction, allows augmenting your product with additional features and ensures delivering more value to your end-users. The most important of Big Data benefits, however, is the ability to employ Machine Learning models for predictive analytics and dramatically reduce the Total Cost of Ownership. IT Svit helps build such systems and save your business lots of money, which can be reinvested into further growth, instead of wasted on inefficient infrastructure operations.

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The main difference between building a web application and a Big Data solution is that there are no standard approaches to designing a Big Data platform. It all boils down to selecting the most appropriate programming languages like Python, R, Golang; frameworks like Django, Flask, etc.; tools like Apache stack – Cassandra, Spark, Hadoop, etc.; NoSQL and SQL databases like MongoDB, Redis, etc. When you know what you want your Big Data system to do, you can figure out what components it must include.

However, composing such a system requires a thorough understanding of data science best practices, as well as the cloud infrastructure workflows required to reliably run these systems. Obtaining access to such expertise can be quite difficult, as most of the specialists or teams capable of doing this are employed by cloud service providers like GCP or AWS, or work for global corporations and Big Data consulting agencies.

Thus said, some years ago every business was limited by these two choices — opting for Big Data services from cloud vendors or trying to hire Big Data architects in-house. Both of these options can be quite costly and outside the budget of a startup or small-to-medium business. This hindered Big Data adoption across the globe, making it a tool for helping market leaders to secure their positions, rather than a tool for smaller businesses to compete successfully.

Nevertheless, the boom of the IT outsourcing industry made Big Data analytics accessible for every company, regardless of the budget or business niche. Experienced BigData teams working in tandem with DevOps engineers can both design the data workflows and implement the cloud systems required to support them. Managed Services Providers like IT Svit can build such Big Data solutions from scratch, using the experience obtained during previous successfully completed projects. We know how to implement Big Data solutions for various use cases and know how to make them cost-efficient.

Best practices of Big Data development

There are two major areas of application for Big Data analytics: improving your customer experience or optimizing your infrastructure expenses. Both require using cloud infrastructure to store huge data sets and large volumes of computing power to process them and train the ML models using Deep Neural Networks and other Artificial Intelligence algorithms.

Once an appropriate Machine Learning model is correctly trained, it can be used to personalize your product offers, help authenticate your customers using OCR (Optical Character Recognition) algorithms, process a variety of data using Natural language Processing features or discover patterns of parameter changes across a variety of data sources, etc. These functions can be applied in a huge range of operations, depending on your business niche.

The other main field of application for Big Data analytics systems involves the minimization of cloud infrastructure expenses. Deploying the ML model to monitor the infrastructure operations helps quickly identify disturbances in normal operational patterns, inform the relevant specialists and minimize the potential impact of the incident. This helps minimize the expenses on incorrect resource allocation, and the cost of potential downtime.

IT Svit helps design, build, deploy and manage both types of Big Data solutions — for product/feature improvement and for IT infrastructure optimization. Based on IT Svit rich experience with Big Data and best practices of Big Data development, our team helps UK companies reach their business objectives. We use the ready solutions to help minimize the time-to-market for your product features and TCO for your IT operations. If you are interested in these kinds of services — reach out and IT Svit will gladly help you with Big Data development!

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