Big Data consulting and management

Every business that wants to utilize Big Data technology in its operations needs to implement a clear and predictable Big Data strategy to ensure the successful implementation of Big Data projects. IT Svit has 5+ years of expertise in Big Data consulting, implementation and management, and we can provide end-to-end solutions that will help you reach your business objectives.

Big Data strategy design and implementation

IT Svit was involved in web scraping and data mining projects for building innovative query engines; projects using Optical Character Recognition and Natural Language Processing for customer verification and CV parsing features; building systems for data processing on the fly. Our team has a thorough understanding of Big Data architecture and workflows, which enables us to provide top-notch Big Data strategy design & implementation services.

Managed Big Data solutions from IT Svit

We have the expertise and technology required to plan, build and run Big Data solutions at scale. We can help your team quickly gain the experience needed to run these systems or we can deliver them as managed services, so your team can concentrate on your core areas of expertise, while we cover the Big Data side of operations.

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Big Data became a buzzword some years ago, by the hype wave has since subsided quite a lot. “Analyzing everything” turned out to be not feasible, and business opportunities hidden within your data streams still remain hidden. However, the initial influx of interest to Big Data technology allowed us to highlight several areas where these practices and principles were able to make a huge impact and enable data-driven analytics to empower business decision-making processes.

Various Machine Learning and Artificial Intelligence algorithms can be applied to enable real-time financial analytics, process textual and visual data, manage smart cities and Industry 4.0 factories, personalize products and services at online marketplaces, etc. However, the correct implementation of these features is impossible without an in-depth understanding of what Big Data solutions can and cannot do, their architecture and workflows — and this is still terra incognita for many businesses.

This is why the UK business that wants to gain a competitive edge over the rest of the market players must implement and utilize Big Data analytics to the fullest extent. This is easier said than done, however, as the expertise required to build and run Big Data solutions is rare to come by, so many companies fall for the promises of pushy vendors and spend lots of time and resources building Big Data solutions that contribute little to the effectiveness of their operations.

IT Svit has ample hands-on experience with all stages and aspects of Big Data implementation, which allows us to provide trustworthy Big Data consulting and help our customers get the results they need. Here is how a feasible Big Data strategy must be formed.

There are 4 main characteristics of any Big Data process, dubbed “4 V’s”:

  • Volume. Big Data operates gigabytes, terabytes, and petabytes of files, which can span various data types. These huge data sets must be used to train the ML and AI models correctly, so they must be reliably gathered from a variety of sources and securely stored. This can be achieved by using Apache Hadoop to run a distributed network of clusters in multiple nodes to provide reliable data storage.
  • Velocity. As the incoming data is huge in size, there will be lots of files to be processed each minute. This means your Big Data solution must work at high velocity to be able to transform various files into a common format like JSON and store them in the database. This can be done through building distributed data analytics systems, where the incoming data is handled by the nearest node to minimize the processing time.
  • Variety. To build a holistic picture, your Big Data platform must operate the data from a variety of sources and work with multiple file types. It must also be able to filter out the noise and leave only the relevant input to ensure the resources are spent cost-efficiently. This is done by writing the appropriate Python scripts and training the needed Machine Learning model.
  • Value. This is the main Big Data parameter. Running the servers needed to store the data and process it at high velocity costs a lot of money. This means the results of such an analysis must justify the resources spent. Therefore, Big Data analytics is only working right if it delivers value to your business.

Therefore, the main goal of a Big Data consulting is determining the VALUE the planned solution can bring to your business. Depending on what you WANT to achieve IT Svit team selects what MUST be done and what Big Data tools will allow achieving this result best. IT Svit can develop a Big Data implementation strategy based on the input from your business stakeholders and create a clear roadmap to ensure the successful implementation of your Big Data project. If this is the result you want to achieve — contact our team right away!

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