Development of Big Data solutions for your business

The hardest part of Big Data software development is that there are no “best-practices” and guidelines for it, as each of Big Data solutions is uniquely suited to perform a certain task. Thus said, while most of the Big Data applications are written using Python/Django, R language, Golang, JuPyteR Notebooks, D3.js, Apache Hadoop / Spark / Cassandra, etc — it is the Big Data application development expertise that matters, not the toolkit used for it. IT Svit has ample experience with delivering end-to-end Big Data development services for various cases!

Big Data software development for any industry

Big Data applications can be hugely beneficial for any industry, as they can either augment your customer’s experience or minimize your operational expenses. Thus said, designing and implementing such Big Data solutions requires both a software development expertise, as well as an in-depth DevOps expertise. IT Svit possesses both and we can lend this expertise to your assistance to help you provide more value to your customers while saving your budget!

Real-time data analytics to maximize your business performance

Big Data analytics can decrease your infrastructure expenses, help better personalize your services, enable some useful functionality for your products, etc. However, the most impactful Big Data application lies within the predictive analytics field, as it allows to significantly reduce the upkeep costs of your systems, and the money you save can be invested into growing your business.

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Big Data software development is quite different from the delivery of any other types of software. First of all, the expertise required to do this is quite scarce and highly-qualified specialists are very hard to come by on the job market. Most of them are happily employed with either cloud service providers like AWS, Google Cloud Platform or MS Azure — or with the leading Managed Services Providers like IT Svit.

Secondly, you need to build the system from scratch every time (though you use the same toolset, technology stack and best practices). Thirdly, even the readily available solutions developed by an IT outsourcing company like IT Svit for previous customers quite often cannot be adapted to the needs of the next Big Data solutions. Thus said, partnering with an experienced team still accounts for much when developing Big Data applications, and IT Svit is very experienced with Big Data development.

Big Data software use cases

The first point to look at when developing Big Data solutions is the purpose of their application. Obviously, the general point is to provide some kind of analytics in real-time for the structured and unstructured data your business gets access to. However, the goal of this analysis can differ quite a lot.

  1. Many E-commerce platforms with huge volumes of traffic like eBay or Amazon use Big Data analytics to better cater to the needs of their visitors, personalize their offerings and maximize sales.
  2. There are medical applications, able to discern the diseases based on blood cell analysis photos and begin the treatment much earlier, greatly increasing the chances of recovery.
  3. Rolls Royce Holdings has implemented a Big Data analytics solution to introduce an in-depth comparison of their turbine blade tests, which helped them identify potentially faulty ones much easier and saved the company hundreds of millions in potential risk.
  4. Transport for London has deployed a robust Big Data analytics solution that performs data processing from thousands of buses, ferries, cabs, and bridges, as well as millions of traffic lights and Oyster London Transport cards to provide safe transportation to 10+ millions of commuters in one of the most important megapolises worldwide.
  5. A fast-food chain of 500+ restaurants across 8 states in the US, Dickey’s Barbecue Pit, has implemented a proprietary Big Data analytics solution for processing data from all their Points of Sale, inventory tracking systems, loyalty program management systems, etc. This helped them optimize resource allocation, rapidly react to various business challenges and raised their margins quite noticeably.
  6. Carnival Cruises, the world’s largest cruise business with 100+ liners operating across the globe under 9 differing brands, has implemented a proprietary Big Data analytics solution. It helped the company personalize the pricing of various items in their inventory to make them more affordable to its customers based on their lifetime purchase history. Encouraging every customer to spend just 1 more dollar a day allowed Carnival Cruises to additionally earn more than $80,000,000 a year — quite a worthy investment, don’t you think?
  7. Telstra, one of the leaders of the telecom industry in Australia and neighboring regions, has implemented an integral Big Data solution to gather the machine-generated data from all of their infrastructure and optimize various aspects of their operations. In addition to improving the baseline income, this would allow them to improve the call handling in their customer support center, and even improve their delivery truck fleet schedule, becoming a more significant player in the local telecom services market.
  8. Xerox, global office appliances and accompanying services provider implemented a Big Data solution to find out the reasons for ever-increasing support representative turnover. Processing the structured and unstructured data from various sources helped the company understand the reason was the flawed approach to measuring the performance efficiency, which led to burnout of experienced professionals. As a result, the international giant changed its approach to corporate culture and efficiency measurement, which helped reduce employee turnover by 20% and saved the company millions long-term.
  9. The IBM Weather company uses a bespoke Big Data solution to analyze incoming data from more than 100,000 of sensor arrays, which total in more than 2.2 individual data entry points for IBM Watson, the technology giant’s AI engine. This allows The Weather company to forecast the weather conditions in real-time and provide on-point information to maintenance companies and businesses beforehand. As the losses from bad weather in the US total in more than 500,000,000 dollars annually, this information can be the difference between saving or losing the business in many cases.
  10. Avis Budget, one of the world’s leading car-sharing enterprises invested in building a Big Data application to analyze the entirety of public and inside data on their customers — from rental history to social media interactions. This would allow identifying highly loyal customers and provide additional discounts to them, as well as highlighting low-value troublemakers and denying them access to the service. Thus said, such a Big Data software helped greatly increase the revenues and decrease the expenses of this car-sharing network.

There are many more examples of Big Data algorithms applied as a part of the customer-facing systems or to improve the efficiency of infrastructure performance, but the general results are the same. Big Data solutions form an essential part of customer experience and ensure the cost-efficiency of your business IT operations due to leveraging predictive and prescriptive analytics.

The only issue here is that all of these companies are either industry leaders or global enterprises and can invest millions of dollars into building their Big Data analytics systems, you might say. The point is, the major part of this investment went into building and operating on-prem cloud data centers, as well as into developing proprietary Big Data management tools. The only reason for that is the confidence of global enterprises that to do something well, you should do it yourself. It was a sound point in the 20th century… but not in 21st, really.

Big Data solution development best practices from IT Svit

The rest of the market players can do just well by using public cloud resources and open-source Big Data tools like Python/Django, R language, Go language, JuPyteR Notebooks, Cassandra DB, MongoDB, Apache Hadoop/Spark/Storm, various OCR (Optical Character Recognition) models, Deep Learning algorithms, etc. The real challenge is finding a trustworthy partner with sufficient experience to determine the best way to design and implement custom Big Data solutions using the most cost-efficient tools available.

IT Svit is such a partner, as we have 5+ years of expertise in Big Data software development and implementation in various industries. Most importantly, we are a Managed Services Provider, meaning we have an in-depth understanding and expertise with all the stages of software delivery, from website design and development to DevOps services, Big Data analytics implementation, Machine Learning model training, blockchain development – you name it.

Thus said, instead of building a team from scratch and reinventing the wheel while developing Big Data software, many businesses go for IT outsourcing and get instant access to in-depth expertise, polished workflows, and ready solutions for most common challenges. This helps greatly reduce the project costs, shorten the time-to-market for new product and ensure its stable and cost-efficient operations. If this is what you need — IT Svit is ready to help!

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