Enterprise Cloud Data Migration: Stick to Approved Data Ingestion Patterns or Pivot to Disruptive Innovative Solutions?

By Kamal Atreja (Head of Delivery and Leader in Enterprise Cloud Data Migration and AI Adoption at Ubique Digital)

With the evolving needs for data ingestion on the cloud and analysing the same for analytics purposes, it has become increasingly important to understand whether we should stick to a defined process for data ingestion or adopt a disruptive solution to meet the urgency of moving petabytes of enterprise applications data for analytics and AI use cases.

Although many enterprises are working towards building innovative solutions for data movement using cloud SaaS ETL services or custom data migration solutions to move data to a cloud data warehouse for analytics purposes, we are still a long way from seamless on-premise data movement to the cloud.

With the strong demand for data analytics, machine learning, and generative AI solutions consistently knocking on enterprise doors and bringing new innovations to market, there is a significant shift required for enterprises to move data to cloud-based solutions quickly. This enables enterprises to consume and process vast amounts of data to create solutions that can sustain and thrive in the global environment using AI.

When the urgency of data movement hits enterprise leaders, they face a critical decision:

• Stick to existing solutions within the organization or approved design patterns to move data slowly and steadily to the cloud, or
• Bring in a disruptive solution to set up the data warehouse in a shorter time frame.

With data being generated from all sources in structured, unstructured, streaming, and batch formats from applications, social media, websites, IoT devices, influencers, news, and global innovations, the way forward seems to be a hybrid approach. Streamlining internal processes with consulting capabilities to innovate the existing process using disruptive new technologies appears to be the best way forward.

Whether the data movement needs to follow homogeneous or heterogeneous ingestion patterns, all security processes, data encryption, or data pseudonymization for data at rest or in transit at the enterprise level must be addressed in accordance with the organization's compliance policy.

This makes it imperative that if we stick to the data ingestion approved design patterns with a defined process within the organization, the speed at which organizations move data will slow over time due to several key reasons:

1. Shortage of Right Cloud Skills: The global shortage of the right cloud skills impacts organizations' ability to not only migrate data but also address the shortfall of relevant staff.
2. Emergence of New Toolsets and Technologies: New and improved tools and technologies available to strengthen the existing data migration setup within organizations' processes.
3. Lengthy Approval Processes: In large organizations, the processes and approval times can significantly slow down actual data ingestion and AI adoption.

At this stage, opting for a disruptive new technology that has proven its worth in recent years seems like the way forward. This approach updates existing design patterns and involves consulting organizations constantly leading innovations to streamline existing processes.

This strategy not only adapts to existing processes but also evolves with the organization's needs and data movement over time, bringing ease to data movement, data democratization, and the setup of an analytical warehouse for the cloud data ocean.

Contact us at Ubique Digital if you would like to discuss solutions for your enterprise in cloud data migration/security/management.

Ubique Digital is a boutique digital transformation consultancy with headquarters in London, UK.