Big Data Consulting Services

Big Data analytics was a buzzword around 5 years ago, now it is the reality we leave in. The technology allowed us to move from traditional data warehousing and business analytics systems to real-time data-driven decision-making. Machine Learning models can now be applied to financial analysis, managing Industry 4.0 factories, transportation systems, energy sector, smart cities and in many other areas. However, most of the businesses still consider Big Data to be a magic stick and don’t know how to apply it correctly.

Big Data is the umbrella term for the toolkit, set of workflows and cloud solutions required to provide real-time data analysis for huge volumes of structured and/or unstructured information generated by your company’s cloud infrastructure, software ecosystem, product usage, social media interactions, etc. Various Big Data solutions can be implemented as features for your products and services, as well as modules of your cloud infrastructure. But how does it work?

Big Data has four distinctive characteristics, so-called “ 4 V’s of Big Data”:

1. Volume. Big Data is called that way because it operates with huge quantities of data. All your business systems produce tons of system logs, and large data sets are needed to train Machine Learning models. Thus said, Big Data solutions require dozens of Gigabytes of disk space.
2. Velocity. All these huge arrays of data must be processed quickly, preferably in real-time. This ensures that the results of data analysis are still relevant by the time they are obtained. Thus said, your data analysis systems must be distributed, so the data is processed at the closes node to where it was obtained, and they must be highly scalable, to ensure they can deal with any volume of information that comes through.
3. Variety. The incoming data flow can be composed of a huge range of information in various file formats, and the system should be able to determine the important parameters, filter out the unneeded details and process the relevant data to bring value for your business.
4. Value. Yes, it is the most important of the parameters, as Big Data solutions are costly, so they should provide some tangible benefits for your business, and “analyzing everything just in case” is by far not the best approach. Your application can be built around Big Data, it can be used in one of the product’s features or can work as a part of the cloud infrastructure to optimize your operations — but Big Data must deliver some value in any case.

Thus said, determining the value Big Data analysis must deliver to your business is crucial for the success of such a project. Therefore, many businesses come to realize they are not using their cloud computing resources with the utmost efficiency and want to implement Big Data analytics but do not know the required expertise in-house. Many more have already tried to implement data mining and Machine Learning into their workflows, but find themselves in need to reinvent the wheel all the time to be able to cope with information variety, velocity or volume.

This is when Big Data analytics consulting companies like IT Svit come into play. As we have in-depth experience with designing, implementing and running Big Data analysis at scale, we are able to provide data consulting services at scale and assist our customers with every aspect of their Big Data management.

Regardless of the domain your business operates in, and the similarities between your company and the rest of the market, each business DNA is unique, and your business is not an exception. While everybody runs pretty much the same infrastructure nowadays, the way you use (or don’t use your Big Data) determines the way you stand out among the rest of the market players.

Financial services companies can use Big Data to assess the credit history of their customers and prevent fraud. The medical industry uses Big Data to identify diseases much earlier than a doctor could do it, based on the complex of parameters, from prob results to MRT scans. The energy industry uses Big Data solutions to monitor a wide range of environmental parameters and maximize the efficiency of their facilities. Industrial companies apply Machine Learning models in a wide range of cases, from quickly processing the results of various component tests and speed up the time-to-market for new products, to optimizing the efficiency of operating their transportation fleet. Fast-food chains deploy Big Data analysis to assess their stockpiles in real-time and launch short-term localized events to increase revenues or minimize losses, etc.

In addition, every business that wishes to remain competitive must reduce the expenses on running its cloud infrastructure and minimize the risks of downtimes. Data-driven predictive analytics helps achieve this result, as the model identifies the normal operational patterns and triggers smart response scenarios, should some anomaly occur.

Naturally, these results can be achieved only if the business clearly understands what results are needed, how they can be achieved and what challenges can arise in the process. A detailed Big Data consulting strategy from IT Svit will help your company highlight the desired results and determine the most cost-efficient ways to achieve them. IT Svit enables your company to use your Big Data most efficiently!

With 5+ years of experience in providing Big Data services and 6+ years of DevOps expertise, IT Svit can develop, deploy and run an end-to-end solution that will solve the business challenge you face. We can also reconfigure the existing Big Data solutions to improve their maximum performance and reduce operational expenses, whether they are cloud-based and vendor-specific or custom modules. We work with businesses of all sizes an deliver the expected results quickly, on-time and under budget. Should you want IT Svit to help you with Big Data consulting — contact us, we are always ready to help you!