5 Key Advantages Of Cloud-based Data Analytics Platforms

We are witnessing unprecedented acceleration towards digitalization as organizations look to recover from the economic impact caused by the global health crisis. To go with practises such as remote working, video conferencing and online retailing, adoption of cloud services by global enterprises is a significant initiative in the post-pandemic world.

According to research and analyst firm Gartner, end-user spending on public cloud services is set to reach USD 304.9 billion in 2021, growing at a compound annual growth rate (CAGR) of 18.4 percent since last year. It is also worth mentioning that a vast majority of organizations using cloud services plan to increase their spending on cloud (further!) to overcome the disruption of the global health crisis.

The rise in cloud spending is likely to be sustained for a few years, Gartner says, with organizations increasing their investments in remote-working technologies, mobility, collaboration and more.

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In return, what advantages are organizations aiming to gain from spending on cloud engineering services, which include analytics, business intelligence, databases, networking, software, et cetera? Let us find out.

Centralized data access

When data is siloed across your content management systems, marketing automation, ERPs and numerous other systems, it’s challenging to get a comprehensive view of your business and decision-making is harder too.

Cloud-based data analytics platforms help organizations by integrating all the data into a single point of access for every user to make business decisions.

Among the key advantages of having centralized data access is you can eliminate duplicate entries of data, provide executives and decision-makers with the right data at the right time, reduce the time spent to identify which gathered data is right, and enhance data intelligence capabilities of the organization.

Security and governance

Governance may be challenging but security is built into cloud analytics platforms, helping you configure user permissions to make sure everyone in your organization has access to the data they need while also ensuring accountability and transparency.

With the increasing volume of customer data being collected and used in 2021, organizations must ensure that privacy and governance requirements are met.

Today’s customers want to know what details of them are being collected and where they are stored. It is possible they will lose faith in an organization if their personal details are widely accessible.

Gartner predicts that, until 2025, 90 percent of organizations which fail to control public cloud use will inadvertently share sensitive data, which also means identity and access management (IAM) will be a key challenge for individual and machine users in 2021 and beyond.


Instead of purchasing new hardware as data requirements change, cloud analytics platforms provide organizations with the option to turn on or turn off their services as required. For example, you can scale up your services quickly if you have a spike in data and, when the activity is normal, scale back down.

The ability to scale up or scale down cloud resources helps organizations to significantly reduce the risk that comes with rapid growth. Most applications can be managed cost-effectively on the cloud and be easily migrated using lift-and-shift strategies.

This flexibility further helps organizations to provide innovative products and services and not be constrained by infrastructure that does not suit their current requirements.

Data sharing and availability

The best cloud-based analytics platforms and solutions provide business users easy access to data, enabling them to analyze and explore in every possible context.

From laptops to smartphones, cloud analytics services also give users a comprehensive, unified experience irrespective of the device, including being able to analyze and share data and applications anywhere.

Cost savings

According to a McKinsey study, legacy systems account for 74 percent of a company’s IT expenses while affecting agility too.

With cloud services, no upfront costs are involved as the cloud service provider fulfills all infrastructure needs. Less power consumption and the lack of need for in-house expertise for server and software maintenance result in even more cost savings with cloud platforms.

Cloud service providers also have multiple data centers and offer resilience with data replication, which is particularly useful during a system crash or natural disasters such as flooding.

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In addition, updates and upgrades happen automatically on cloud-based data analytics platforms. This saves organizations significant costs as they don’t have to worry about ongoing maintenance which is typically part of on-premise servers.


From providing centralized data access to reducing costs, cloud-based analytics solutions are helping companies get maximum value from their data. As the volume of data grows exponentially, cloud is very much the future of data analytics as it provides agility and fosters company-wide use of analytics for data-driven business decisions.

Author: Suhith Kumar
Suhith Kumar is a digital marketer working with Indium Software. Suhith writes and is an active participant in conversations on technology. When he’s not writing, he’s exploring the latest developments in the tech world.