Top 5 Cloud Myths that can derail your migration plan

Big Data Visualization
As data gravity shifts from on-premise to the Cloud, BI also needs to move for strategic advantage. Though the drivers for Cloud BI may be different for each organization, here are some common cloud myths that can derail your migration plan in the long run.

Myth: BI in Cloud will save costs

One of the biggest myth about Cloud BI is that it helps in saving costs for every business. However, the truth is that your ability to save costs in the cloud will depend upon the size and nature of your workload.

Cost savings in the cloud are determined by the extent of fluctuations in workloads and vary for different enterprises based on the amount of processing they do on a daily, weekly, and monthly basis. If you are using the same resources 80% of the time, then instead of saving costs you will be spending more in the cloud.

To ensure cost savings, you need to first understand how cloud will help you in saving costs and then evaluate your migration based on your specific business needs. Instead of using a lift and shift approach, you should use tools and technologies that are designed take advantage of the flexibility of the cloud. You can achieve your long-term cost savings goals by building an auto-scaling analytical model that can handle business workloads in the cloud with high elasticity and optimal resource utilization.

Myth: If you move to cloud, you’ll be locked-in to a specific vendor

A common reason why organizations are skeptical about moving their BI to the Cloud is that they feel that once they choose a vendor, they will get locked-in to that vendor. Business teams find it difficult to trust vendors, especially with their sensitive data, and IT teams anticipate long-term portability issues. It is assumed that moving to another vendor in future would cause too much pain.

From business intelligence perspective, if you choose all services from a specific vendor or choose products that are built using a set of vendor-specific services, portability will be reduced. In that case, you’ll be locked-in to the vendor and moving to another would cost a great deal of time and money.

However, you can dispel this myth by choosing your services intelligently and building an analytical environment using tools and technologies that are vendor-neutral and work with all cloud vendors and configurations.

Myth: Its either no Cloud or all Cloud

It is not always possible to move everything to the cloud. For large organizations with huge existing on-premise infrastructures, complete migrations are complicated and expensive. In a real scenario, organizations have to deal with multiple data sources including on-premise Hadoop environment, cloud storage such as Amazon S3 or Google Cloud Storage, distributed streaming platforms or other modern platforms, and even some of their legacy applications. This makes an all-cloud approach almost impossible but that does not mean that you cannot move to the cloud.

If you have a huge existing infrastructure, you can either follow an incremental approach or choose a hybrid implementation. You can build a modern BI architecture that enables cross-platform integration. A modern BI platform supports multiple data sources and provides the flexibility to move incrementally. It allows connectivity to your existing applications and enables easy consumption of data across the enterprise through a unified interface.

Myth: Cloud makes your business agile

Organizations often embrace the Cloud hoping that it will make their business agile by providing the scalability and performance they need to achieve the desired business outcomes. However, it is important to understand that there is a difference between being cloud-enabled and enabling cloud computing. Simply moving applications to the cloud does not automatically make them more efficient or meaningful to the business. Cloud by itself does not make your business agile.

The key here is not to think about Cloud as adopting a modern technology, but instead, implementing cloud services from an outcome perspective. Pulling massive volumes of data and feeding into your traditional BI tool would sometimes require the same amount of effort, irrespective of whether it is in the cloud or not. If you want to use the cloud for ad-hoc analysis and exploration of Big Data, you need to use a modern BI platform in the cloud that can pre-aggregate data at massive scale and deliver quick insights that translate into business outcomes.

Myth: Rip and Replace approach is essential

It’s a common myth that once data moves to the Cloud, existing BI applications and processes would not be able to work in the new environment. They would either need to be replaced by new ones or re-engineered to achieve the desired performance in the Cloud. This leads to a considerable amount of training and migration effort. Besides this, business users are reluctant to change the BI tools they are comfortable using.

You need a way to move to the cloud without going through the time-consuming and expensive effort of rewriting your BI applications or SQL queries. This can be resolved by building a modern BI architecture in the Cloud that leverages its flexibility and elasticity for analytics, while at the same time enables your existing BI tools and applications to connect to the Cloud. This would ensure that transition is transparent to business users and they are not impacted by the move.

Solution: Building a Modern BI Architecture in the Cloud

With the availability of multiple cloud options, it is important to keep your end goals in mind while planning your cloud strategy. We, at Kyvos, help you build a modern BI Architecture for the cloud that offers a radically better way to do analytics in the cloud with high elasticity and superior performance.

Our breakthrough technology helps you build a high-performing BI Consumption layer in the Cloud that allows your existing BI tools to access massive volumes of data with high performance and unlimited scalability. You can use your existing BI tools like Tableau, Excel, Power BI, Business Objects, Spotfire, Cognos, QlikView, Qlik Sense, or even your custom tools, for Cloud Big Data analytics.

Built for the cloud, Kyvos leverages native cloud elasticity to scale up and down as needed to optimize resource utilization and reduce costs. You can monitor your cloud resource consumption and quickly grow or shrink to meet your organization’s needs. Kyvos supports all major cloud service providers including Amazon Web Services and Microsoft Azure, and provides a seamless way for you to move BI and analytics processing from on-premise to cloud deployments.

If you want to learn more about our cloud platform and how it helps you build a long-term cloud strategy, request a demo now.

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