Companies nowadays feel the pressure to innovate and go digital. One of the biggest questions executives are facing is how to do all of these— migrate systems and processes and transition culture— especially in complex organizations employing thousands and servicing a lot of customers. In a given enterprise, there are many operational workloads that can be migrated to the cloud, and analytics migration is one of the most common ones.
Agility and scalability
Analytics processes are well-suited for migration because it can benefit from two important things that the cloud can provide: agility and scalability. Legacy systems simply cannot keep up with the workload demands and intensive computing power required by organizations of today. If your organization is working with big data, migrating to the cloud has become a necessity due to its many benefits. According to Teradata, 40 percent of big data practitioners used cloud services for analytics in 2015.
Many large tech organizations offer readily available cloud data management and analytics. The two leading platforms are Microsoft Azure and Amazon Web Services (AWS). When looking at your options for migrating analytics processes to the cloud, it is crucial to make the right choice among cloud providers and to work with a strategic technology partner that can help you develop the data architecture, roadmap and implementation plan for your organization’s needs.
The imperative to modernize business practices is driven by customer demands. Customers nowadays expect products and services to be available immediately. These demands necessitate companies to modernize their existing analytics processes in order to serve their customers and compete in the marketplace. Cloud data management and analytics platforms offer off-the-shelf algorithms, solution architecture blueprints and even source codes that enable organizations to quickly buy in order to optimize processes or upgrade to new analytic methods.
Like any complex process that involves multiple stakeholders, teams, and extended timelines, migration comes at a cost. However, while organizations allocate budget toward migration, it is a strategic investment because it can reduce the total cost of ownership. Additionally, by using cloud solutions, companies could shift their capital expense toward operational expense, giving them the flexibility to free up capital toward other initiatives.
Migrating analytics to the cloud is a worthwhile endeavor, but it is also complex. When considering migration, IT departments should assess existing processes and plan for potential dependencies and constraints. Additionally, they need to identify potential applications and examine the advantages of certain solutions, such as infrastructure-as-a-service and platform-as-a-service, that will complement a cloud strategy.
Understanding that migrating analytics to the cloud is a process with several steps, milestones, and key decision points. Migration happens gradually, never all at once.
While migrating analytics to the cloud is easy and common with cloud management platforms, risk can exist even in a successful migration. Developing a sound migration strategy in order to minimize risk and ensure successful business outcomes is the way to go. It can help organizations mitigate delays, interruptions and project failures. For example, partial migration may be more suitable for a data-intensive organization especially when opportunities for downtimes are limited.
In order to understand the complexity and manage risk, scope discussion and assessment of cloud readiness are important first steps to begin the process of cloud migration.
Putting it all together
Migrating analytics to the cloud enables companies to manage data where they can be deployed, optimized, and scaled with ease. Cloud platforms enable organizations to build new services and products. Over time, as services scale up and become more central to a company’s operations, the workload balance of an enterprise will naturally shift towards the cloud. Companies who want to lead their industries are already doing so.