According to the latest statistical studies, the global big data market will grow to $103 billion by 2027, doubling the volume of 2018. It makes sense to expect big data analytics consulting with advanced tools to develop further.
At the same time, the cloud computing market will be growing by 18.79% annually as software as a service (SaaS) quickly becomes popular. The synergy created by the combination of cloud infrastructure and big data will be revolutionary. To understand why they are perfect for each other, we need to consider how they differ and how they are related.
Differences and Relationships
Large amounts of data are too big to be viewed or queried on a regular computer, and they grow rapidly over time. Traditional methods are not suitable for storage and processing, therefore, the need arises for specialized management software tools.
Cloud computing allows you to store large amounts of data, files and programs and provide access to them over the internet on demand. Hardware virtualization provides the required scalability, resiliency, and availability.
Due to flexibility and scalability, available resources can be used according to customer requirements. They will allow you to view and query large datasets much faster than on a standard computer. In other words, cloud computing can become a mechanism that remotely accepts and performs any kind of big data operations.
Distribution of Roles and Relationships
The SaaS model makes it easy to process data using a console that can accept specialized commands and parameters, or directly from the site’s user interface. This makes it mega popular, and practically uncontested.
On the other hand, big data is generated by large networked systems. This requires powerful resources that are not easy to manage. A wide variety of types and types of data requires new approaches, including the use of machine learning and artificial intelligence.
Data can be collected through a cloud computing platform. They can be received and processed in real time, edited and used for analytical studies. In addition, the power of the cloud dramatically reduces the time spent on big data analytics.
The perfect combination
Big data itself is a potential value. It takes a long time for ordinary computers to extract it. Connecting to clouds opens up new possibilities.
Cloud computing allows us to use modern infrastructure and only pay for the time and energy we use. They have the lowest entry barriers in terms of cost, complexity, payback time, and eliminate the risks inherent in local storage.
The main reason for collecting big data is that there are services that can receive and decrypt it in a matter of seconds. They go hand in hand and cannot exist without each other.
It is the perfect combination for the key benefits:
Agility. Setting up servers and a big data storage infrastructure is costly and time consuming. Cloud computing almost instantly provides any infrastructure with the necessary resources.
- Elasticity. The cloud platform is capable of dynamically expanding, providing room for new data.
- Efficient data processing. Cloud computing simplifies and makes the process of processing data of different types and forms available for all types and sizes of enterprises.
- Reduced costs. Maintaining a large data center can drain your budget. The cloud eliminates the need to invest heavily in hardware infrastructure support. In addition, we only pay for the space provided and the energy consumption.
- Low complexity. Cloud computing allows you to automate components and integrations, improving the performance of big data analytics.
Conclusion
The symbiosis of the best modern solutions gives a chance of growth for companies with great ideas but limited resources. They allow these companies to use data that was previously not possible to analyze.
Success awaits organizations that invest in converting hidden potential into real income. Click here to contact our team if you are looking for a smart solution to manage your big data.
