In this digital age, companies are collecting massive amounts of data from multiple sources, such as customer loyalty cards or email marketing. When properly processed and analysed, Big Data can offer businesses valuable insight into their operational efficiency, customer preferences and more.
However, as Gartner notes, those information assets need ‘cost-effective, innovative forms of information processing for enhanced insight and decision making’. The cloud is an excellent candidate for this because it has the tools and mechanisms to process, analyse and store such voluminous data sets.
The value of Big Data lies in its sheer volume, which enables companies to derive more accurate and holistic insights from it through detailed analysis. However, these data sets can come in the terabytes, petabytes or more, which poses a challenge for current on-premise IT infrastructures as storage is often limited by the number of servers.
The cloud’s capacity to flexibly scale on demand eliminates these limitations and allows businesses to expand their storage as they require, which can be as little as a few gigabytes to thousands of terabytes and beyond. It is also more efficient cost-wise because businesses are only paying for the storage they use at any one time.
The sheer magnitude of Big Data requires immense computing power to analyse and process it in a timely fashion, which the cloud is capable of providing. A cloud network’s ability to simultaneously integrate sizable datasets derived from numerous sources fosters efficient real-time analysis of Big Data, which can be smoothly performed from a singular reference point.
We have also supported clients that were facing challenges coping not just with data volume, but also data type. With more unstructured data being generated in today’s world than ever before, having the infrastructure to standardise it for efficient analysis is crucial, especially in the world of sports analytics.
Previously, numerous key metrics were being laboriously captured, recorded and ranked manually. We successfully automated the process via our cloud-based solution with artificial intelligence-enabled Azure services. This provided an automatic input of all unstructured data generated by the client and led to more seamless data analysis, as well as enabling better predictive player rankings.
Flexible, cost-efficient budgeting
On-premise management of Big Data often incurs high costs due to the necessary capital expenditure on massive-scale infrastructure resources, which must be constantly upgraded, maintained and expanded as they handle more data. This also increases operational costs such as electricity usage, hiring of IT staff and so on.
Outsourcing Big Data management to the cloud is more cost-effective as it transfers many of these infrastructure maintenance and analytics costs to the cloud provider. They will be responsible for maintaining and upgrading the cloud environment, covering everything from cloud storage and processing to cybersecurity and cloud backup. Additionally, the pay-as-you-go model common with clouds allows for more flexibility in the business’s budget.
Preparing for a data-driven future
Big Data is a constantly growing phenomenon, and cloud technology will help businesses best capitalise on the advantages it offers. As the world becomes more digitised, even small to medium enterprises can expect an overwhelming force of data generated.
Journal studies have described the concurrent use of cloud and Big Data as a “match made in heaven” due to the compatibility of the immense storage and computing power of the cloud with the voluminous nature of Big Data. With near-infinite scalability, sheer computing power and better cost efficiency, businesses can leverage the cloud to cement their competitive positions and remain agile in a data-driven world.
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