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In association with Hexaware-Technologies
  1. Leadership
November 19, 2021updated 22 Nov 2021 5:17pm

How enterprises must find a data migration strategy to fit transformation needs

Hexaware’s Vaidya J.R. on how the complexity of data and analytics workloads can be streamlined to deliver digital transformation, combining automation with human expertise.

By lead monitor

Clouds have formed over enterprises across the globe. They are not necessarily the dark, ominous harbingers of impending storms, however; rather the promise of a brighter future.

And they are certainly getting bigger. Vaidya J.R., SVP and global head of business intelligence and analytics at Hexaware, points out that, by 2025, forecasts suggest 200 zettabytes of data will be stored globally on the cloud.

data migration

Hexaware’s Amaze for Data and AI platform provides a comprehensive road map from traditional data warehouses to the cloud. (Photo by piranka/iStock)

The transformation of static on-premise IT architectures for data storage and analysis to dynamic, multi-cloud and hybrid architectures is well underway. Accelerated by the unique conditions and requirements of the past 18 months or so, it is now being performed at unprecedented speed and scale.

“The rise of cloud-based workloads and large-scale adoption of SaaS platforms have made cloud the new normal,” says Vaidya. “It’s also believed that 50% of all this data will be on the public cloud. If not already executing, every enterprise in the world is thinking of strategies to move to the cloud. It is inevitable.

“In turn, the centre of gravity for data and analytics has shifted,” he continues. “By 2023, 75% of data and analytics workloads will be on a cloud platform. The real task is for enterprises to ensure they get the digital fabric right.”

Amaze on the move

Hexaware’s Amaze for Data and AI platform provides a comprehensive road map from traditional data warehouses to the cloud. Its automated approach begins with gathering and analysing all internal and external strands of that digital fabric, ingesting it into a data lake, cleaning it up and transporting it seamlessly to the cloud – regardless of which service provider a company chooses to work with.

Automation removes 80% of the effort normally required to prepare data for an analytics cycle, pool it and prepare it for migration. The platform promises a 60% saving in cost, time and effort. Furthermore, having been launched only in May of last year, Amaze for Data & AI continues to evolve, recognising the unique data requirements and challenges faced by various verticals.

“People are looking for trusted partners to help them to move to cloud, so the platform is rapidly evolving with every single large engagement,” says Vaidya. “We are creating our own differentiation, using our expertise and the knowledge of the industry. We are building differentiated industry-specific data models that can drastically reduce time to market when enterprises go digital.”

“These are very specific data models for industry, like capital markets, healthcare or insurance, and we’re coming out with domain-driven data architectures. Not just in the data models, data pipelines and integrations, but also around how we infuse AI and machine learning.”

Simplicity through automation

Complexity is the bane of cloud transformation processes. “When businesses are reluctant to move from on-site storage, it is often because they do not understand the complex data landscape within their own organisations, or they lack the capabilities and bandwidth to properly untangle it.”.

“It has often evolved over many years to the point where businesses have a spaghetti of systems in place,” says Vaidya “They do not have control over what is working for them and do not see what the landscape looks like. So, we have developed an assessment toolkit that really can figure out the complexity of an organisation’s data landscape.”

“Sixty per cent automation is possible with Amaze for Data and AI,” he adds. “We can build across the three layers of data store, data pipeline and visualisation, no matter how many data warehouses are involved. We have worked with customers who have huge number of data warehouses.”

The platform accelerates digital transformation initiatives by enabling organisations to build the capability to glean insights ahead of their competition from the data that they have access to, both within the enterprise itself and in the public domain.

Now, in the aftermath of the pandemic, there is a need to make such a transformation more urgently than ever before.

Digital transformation has become job number one,” agrees Vaidya. “More and more of my clients are asking me for a quick MVP – a minimum viable product. And then multiple releases follow. They want to hit the market right now. There is a blurring of the lines between business and IT strategies, which are really becoming synonymous.”

“With the pandemic, we’re seeing touchless and immersive customer experiences becoming the norm,” he adds. “And now all of these are enabled big time through the technologies that enable digital leapfrogging, for which resilience on the cloud is key. Everybody is seeing that the recovery from this pandemic is through digital.”

A guiding hand

With haste come mistakes, so as companies look to better leverage cloud, there is a risk that they will not execute the transformation correctly. With Amaze for Data and AI and the industry expertise of Hexaware behind it, those risks can be mitigated, says Vaidya.

“People are beginning to understand that it is not just technology change that’s required; it’s a cultural one,” says Vaidya. “It means changing people’s skillsets and transforming the way they collaborate. Clients want highly personalised, customised and connected services. They want convenient products and services that are being leveraged with utmost customer-centricity, automation and straight-through processing.”

“They want decisions made based on data to be facilitated in near real time or real time,” he adds. “That is what the platform delivers for them, simply and quickly.”

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