What Would It Take to Move Analytics to the Cloud?

Digital transformation efforts are in full swing across organizations that are looking to drive positive outcomes and ensure long-term sustainability. Coping with the ever-changing business environment has compelled every business leader to adopt digital technologies and embrace the capabilities of the cloud.

While many organizations have begun moving apps and data to the cloud, they are still not completely open to the idea of moving analytics to the cloud. Possibly, because they don’t really know how or where to begin!

Read on to uncover why you should move analytics to the cloud and what it takes to do so, successfully!

Why move analytics to the cloud

As cloud computing becomes mainstream, there is a lot of migration happening across various business streams. While data and apps are most commonly migrated to the cloud, the benefits organizations can experience by moving analytics to the cloud are now too many to ignore.

Here’s why you should consider moving analytics to the cloud:

• Scalability: One of the biggest drivers for moving analytics to the cloud is the promise of immense scalability. Unlike on-premises tools and systems that are limited by their storage and computing capabilities, the cloud offers unlimited scalability. So, no matter how large your current data sets are, or how much bigger they are likely to get in the future, you can analyze all of them with the same speed, accuracy, and efficiency in the cloud.
• Anywhere access: With the cloud, analytics is no longer restricted to the IT or data science teams. Almost every person in the organization can get access to analytics tools and capabilities and use the insights to power their decisions. In addition, self-service analytics capabilities driven by ready tools and solution-sets provided by the cloud vendors mean employees can also quickly feed analytics tools with different data sets and quickly uncover actionable insights for the best outcomes.
• Faster insights: The cloud also helps in eliminating slow, time-consuming, and resource-intensive analytics processes and methodologies that organizations have had to contend with all these years. Moving analytics to the cloud means employees no longer have to wait for weeks before they can get access to critical reports or depend on the IT team to resolve analytics-related issues. Faster and easier access to insights means they can be extremely responsive to trends and quickly identify opportunities to grow the business.

What it takes

The global cloud analytics market size is expected to grow to $65.4 billion by 2025, at a CAGR of 23%, suggesting rapid adoption among enterprises convinced of the utility. Increasing data volumes, the ubiquitous trend towards becoming a cloud-first organization, and the many cost and efficiency benefits of cloud-based analytics solutions are all contributing to this massive growth. 

If you want to accelerate cloud adoption for your data analytics projects and get faster, more accessible, and more deeply scalable analytics, adopting the cloud makes eminent sense. That said, you need to be aware of the risks and opportunities and embrace certain best practices to become extremely agile, flexible, and responsive. 

Successful cloud analytics requires strong data governance, extensive data access and tools, and an analytics-first culture in place. Here’s what it takes to successfully move analytics to the cloud:

• A detailed assessment of the organization’s cloud strategy: Before you begin the task of moving analytics to the cloud, you need to understand your organization’s cloud strategy and determine how you can align analytics with it. This includes the type of cloud you select, the provider you partner with, the services you opt for, the tools you use, and more. A detailed understanding can eliminate the chance of ad-hoc decisions, minimize unnecessary costs, reduce security vulnerabilities, and curtail overall dissatisfaction with the cloud.
• Deep understanding of how analytics fits into the strategy: Since analytics depends primarily on data, it is important to evaluate how analytics will fit into the cloud data landscape. This includes the analytics model you choose, the security policies and governance you build, and the obstacles you may run into that can delay migration. Conducting a comprehensive assessment of the current state of your analytics platform and the business processes that rely on analytics can help in identifying any code or functionality that may prove challenging to migrate and data volumes and formats that need to be assessed or changed to accelerate migration.
• A carefully planned, phase-wise approach: Instead of taking a Big Bang approach to migration, determine which data or analytics tools you need to migrate first, based on their priority. Taking a careful, phase-wise approach can ensure a smooth and seamless move to the cloud, while also learning from the challenges you face along the way. Since conventional migrations take weeks or even months, the phased approach can help you quickly find out which tools, processes, and ideas work and which don’t, so you can plan for alternatives while also prioritizing future projects.
• Efforts towards data prioritization: Data is at the heart of your analytics projects; but not all the data you have is relevant, updated, or required. If you want your cloud analytics efforts to deliver maximum results, you need to take out time to evaluate and prioritize your data. Do not give in to the temptation of moving all your data to the cloud. That will increase the effort, time, and cost of the migration and could potentially stall the initiative. Instead, look at each data set in detail and determine if it makes sense to move it to the cloud. Such screening will not only improve the speed with which your analytics tools generate results; it will also deliver the best and most accurate insights.
• The right migration framework: Any migration to the cloud doesn’t happen at the same time or in the same way. Since a lot depends on your current maturity, your business drivers, and your budget and timelines, you need to consider the various analytics applications and assess which kind of migration will be most suitable: rehost, refactor, re-architect, revise, or rebuild. Carefully weigh the pros and cons of each approach and choose one based on the urgency, budget, opportunities, and dependencies.

If your business experiences instability due to the emergence of new market forces, the pressure of digital transformation, and the impact of globalization, you need to prepare yourself to face volatile conditions in the business landscape. Moving analytics to the cloud is a great way to overcome challenges across blurred industry boundaries, evolving regulations, and fluctuating trends. By doing so, you can not only accelerate transformation but also gain a stronger foothold in today’s highly competitive market.

Contact us today and allow us to make this complex migration quick, smooth, and cost-effective for you!