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Many companies generate massive amounts of structured, unstructured, and semi-structured data. But they lack the time and resources to build on-premise data systems, develop an analytics toolset stack, and hire an in-house team of data scientists. As a result, the data often goes unused. This is where big data as a service (BDaaS) comes in handy.
Organizations can instead hire the data management systems and toolsets of an outside provider. In doing so, they can save on organizational resources and still process, manage, and evaluate their large data sets to derive insights and gain a competitive business edge. Read on to learn more about big data as a service (BDaaS).
Big data as a service is an umbrella term that’s used to refer to different services related to the management of big data functions. It offers a combined structure of the following cloud-based big data solutions to companies:
By leveraging BDaas, enterprises can better handle, analyze, and manage massive data sets. And as a result, gain insights that may be useful in enhancing business operations.
Owing to their tailored nature, big data systems are never easy to build, deploy, and manage. But switching to cloud computing and managed services makes things easier. That’s because the user company doesn’t need to handle any of the hands-work that they would need to do if the data platform was on-premise.
Data processing workloads in many business environments vary from time to time. Because BDaaS is scalable, organizations can easily scale up big data systems based on their processing needs. They can also scale them down after the tasks wind up.
On top of all that, big data as a service users enjoy the added flexibility of adding or removing data technologies, toolsets, and platforms as dictated by existing business requirements. Of course, this would ave been impossible if the big data architectures had been deployed on premises.
Big data as a service is cloud-based, which translates to huge cost savings. That’s because it eliminates the need for organizations to invest in new hardware and software. Moreover, enterprises don’t have to employ in-house staff with big data management expertise.
Cloud data security remains a key concern for many organizations. The Cloud Security Report of 2022[1] reveals that 27% of organizations have encountered a security breach in their public cloud infrastructure in the last year. And the major contributors to cloud breaches include:
In light of these possible threats, BDaaS cloud vendors invest in failsafe security protections that guarantee the safety of their client’s data.
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There are several Big data as a service vendors on the market, and it’s important for you to know how to choose the right one[2]. Here are some important questions that you should ask before working with a specific big data as a service (BDaaS) provider:
You want to work with a BDaaS provider that offers no start-up cost for a specific period of time. The free trial period should provide tangible results before you start spending money on the service.
Big data projects often grow beyond their preliminary vision. If your data processing needs increase, will the provider allow you to scale up your big data storage and processing systems at an affordable price?
Big data as a service is designed to analyze huge, cluttered, and unstructured datasets. So if your data needs are small scale, then this service may not be ideal for your business.
The top big data as a service providers offer real-time insights on current happenings. This allows you to take needful action based on the valuable insights provided instead of learning from what happened last week.
Most BDaaS providers will give you the choice of both strategies, with technical personnel working behind the scenes to ensure everything flows smoothly. Of course, the consultancy service package may cost you an extra penny depending on the level of support included.
With big data as a service, you’ll have to move your datasets to a third-party cloud provider. Of course, this raises the issue of security. That’s why you should first understand the provider’s security policies and practices for safeguarding your business data. You’ll also need to weigh up the pros and cons of leveraging public cloud deployments or a system that allows private clouds.
Big Data has become the norm in recent years, with companies generating large amounts of data every day. Instead of building an on-premises big data framework, you can outsource your big data needs to big data as a service provider. It is an economical solution that reduces complexity and allows easy scalability.
[1] Checkpoint.com. What is Cloud Security. URL: https://www.checkpoint.com/cyber-hub/cloud-security/what-is-cloud-security/the-biggest-cloud-security-challenges-in-2022/. Accessed September 28, 2022
[2] Bernardmarr.com. BDaas, how o Choose the Best Provider. URL: https://bernardmarr.com/big-data-as-a-service-how-to-choose-the-best-provider/. Accessed September 28, 2022
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