cloud transformation

Cloud migration is a key part of a company’s cloud transformation strategy. While cloud migration is simply the movement of data, applications, and systems from on-premise to the cloud, cloud transformation encompasses developing an end-to-end strategy to enrich an organisation across all functions and departments – using cloud technologies to meet business objectives.  

Let’s understand the difference between cloud migration and cloud transformation with a case study.  

Recently, Deloitte released a report highlighting the cloud transformation initiatives undertaken by various companies across the globe. Amongst them was the journey of a UK-based global automotive manufacturer.  

Famous for building iconic British vehicles, the car manufacturer had assembly plants all over the world, and its objective for cloud transformation was to increase its market share and become more insights-driven across functions.  

The company turned to AWS and a cloud transformation services company to implement these objectives. Here’s what they did.  

  • As a first step, the automotive manufacturer documented how data was stored in the organisation currently – it was siloed, some needed manual updates, and there was a lack of adequate transparency and security. They tackled it by building a data lake architecture and later building a comprehensive technology stack within AWS, which would provide traditional data warehousing, advanced AI analytics, and business intelligence solutions. This helped the automotive manufacturer connect data assets across functions and plan sales, inventory, and marketing more cohesively in one process.  
  • It equipped its workforce with the required skills to adapt to the cloud and develop the capabilities to aid in their digital transformation journey. 

The result? The global car manufacturer had access to data from a single source, which led to informed, enhanced decision-making capabilities, and sustained growth in the market. This is a classic example of a cloud transformation journey. 

A cloud transformation strategy involves; 

  • Coming up with the business case (determining the objective of moving data to the cloud) 
  • Determining a suitable cloud deployment model and strategy 
  • Embedding analytics into the entire organisation 
  • Enhancing security across each set of data and assets, ensuring that it is compliant with industry standards 
  • Optimising processes, performance and operations to reduce cloud spending and promote growth and innovation 

Let’s look at each of these strategies in more detail. 

Step 1: Determine the Objective Behind Cloud Transformation 

It’s important for businesses to assess their current stand in the industry – how they are performing in comparison to competitors, what is the current state of operations, and what are the gaps that need to be filled. This will help them identify what needs work, and how the cloud can help achieve that.  

For example, the Deloitte report highlights another case study of an Australian academic institution, the University of Newcastle, which wanted to adopt a cloud-first strategy to achieve one major objective; it wanted to compete and differentiate itself in the higher education sector. With this goal in place, the company implemented a cloud strategy that enabled it to introduce system changes much faster than earlier, accelerate research through instant access to a host of academic resources, and improve security and disaster recovery. 

Step 2: Identify a Suitable Cloud Deployment Model 

We have spoken about cloud deployment models in our earlier blogs. The three types of cloud deployment models are; 

  • Public 
  • Private 
  • Hybrid 

Public clouds act as third-party vendors that provide cloud space for businesses on a subscription basis. Public clouds are used by multiple businesses, and they’re ideal for businesses that have fluctuating needs and are in the growth phase, or for businesses that are still in the testing phase. 

Private clouds are exclusive to an organisation, and they’re placed in the organisation’s physical data centers. Even if they are hosted by third-party vendors, they run on a private network, and the hardware and software are exclusively maintained by the organisation. 

A hybrid cloud is one where businesses have data and applications moving between both public and private cloud environments. Typically, businesses that have their data on the hybrid cloud choose to store sensitive data that has strict regulatory norms, in the private cloud, and testing apps and related data in the public cloud. 

Depending on the business requirements, and the regulations, organisations can choose from the three cloud deployment models. 

Step 3: Establish a Cloud Migration Strategy  

Normally, during cloud migration, organisations hire experts and train an internal team to manage the entire process from the get-go. And, they move data and applications in parts after assessing the current state of their infrastructure and systems. During migration, organisations can choose from the following approaches to move to the cloud;  

  • Lift & Shift, in which they can migrate their data and assets to an Infrastructure-as-a-service model. This process requires minimal changes and is the easiest way to migrate data to the cloud. 
  • Re-factor and rebuild approach, where, during migration, their business applications have to be rebuilt or modernised to configure with the cloud provider’s platform.  
  • Replace approach or moving to the Software-as-a-service model – Where you have to replace your applications or functionalities to suit the SaaS platform. 

Step 4: Build a Cloud Analytics Framework 

Every day, businesses generate tons of data from across functions like sales, finance, customer service, marketing, and IT. When they store all this data on an on-premise data center, it becomes expensive to collate, scale and analyse.  

Storing all this data on the cloud and embedding analytics tools to draw insights from a single source of truth gives immense benefits for organisations; it helps in generating timely and relevant insights, quickens decision-making, and aids in market growth. 

As a Merit Expert adds, “These days most enterprises are choosing to move their BI workloads to the cloud. While they may choose to retain their legacy data residing in an Oracle or SAP ERP in the on-premise database, they are looking to drive efficiencies into the BI process by migrating analytics, etc. to the cloud. But the key here is to look at the whole process holistically taking into account data management, governance, security, etc. It is just not a cloud migration effort; Rather it requires a complete cloud transformation program that is spearheaded by both business and technology teams. The role of a cloud strategy and cloud transformation service provider, therefore, becomes extremely important.”  

Step 5: Enhance Cloud Security 

Third-party cloud servers like AWS, Microsoft Azure and Google Cloud come with in-built security systems in place. Having said that, it is always best to assess the state of security in existing data centers, identify gaps, and look at how it needs to be enhanced when data and applications are moved to the cloud.  

A cloud security strategy includes determining identity and access management processes, having a cybersecurity strategy in place to minimise risk and exposure to highly sensitive data, software development lifecycle (SDLC) consulting to detect threats and vulnerabilities, and ensuring data is compliant with the regulatory standards set in the industry. 

In conclusion, cloud migration is part of cloud transformation. The latter is a holistic process involved in identifying why a business needs to migrate, laying down a detailed approach to how the migration needs to take place, and maintaining the cloud data centers in a manner that encourages ease, reliability, growth, and innovation for businesses. 

Merit’s Expertise in End-to-End Cloud Transformation Solutions 

Merit works with a broad range of clients and industry sectors, designing and building bespoke applications and data platforms combining software engineering, AI/ML, and data analytics.  

We migrate legacy systems with re-architecture and by refactoring them to contemporary technologies on modern cloud ecosystems. Our software engineers build resilient and scalable solutions with cloud services ranging from simple internal software systems to large-scale enterprise applications.  

Our agile approach drives every stage of the customer journey; from planning to design development and implementation, delivering impactful and cost-effective digital transformations.  

To know more, visit: 

Related Case Studies

  • 01 /

    Enhancing News Relevance Classification Using NLP

    A leading global B2B sports intelligence company that delivers a competitive advantage to businesses in the sporting industry providing commercial strategies and business-critical data had a specific challenge.

  • 02 /

    Optimised End-to-End Test Coverage and Test Automations

    A global B2B digital business information and analytics company needed optimum test automation and best practices for all stages of the software delivery