Automate your Data Migration and Modernization Journey with Tech Mahindra's Sprinter

Data deluge. This phrase has found a permanent place in the business lexicon. And there is no denying that we live in the data deluge era. But what does the data deluge really look like? To give you an understanding, we have generated and stored 120 zettabytes of data till 2023¹. By 2025, this figure is about to reach 180 zettabytes. That is more than the number of stars in the visible universe. 

Data deluge presents a significant challenge for many businesses. Managing, storing, and utilizing the vast volume of data is a mammoth task. It becomes even more challenging when you consider the enormous historical data that needs to be managed. An enterprise's historical data comprises critical insights and context that can help in future marketing or investment decision-making. It can also account for past customer interaction records to ensure a seamless customer experience. So, keeping track of their origin (metadata lineage) and dependencies is essential. Since these data have been moving in and out of different organizational tools for years, it is common to lose track. 

While Metadata-driven historical and incremental data migration to the cloud can solve these challenges, these projects often have low success rates. 

According to a Moor Insights & Strategy whitepaper². only a mere 46% of migration projects were delivered on time, and even less than 36% were completed within the stipulated budget. The reason? In the same study, 45% of executives cited a poor understanding of critical technologies as a major challenge. Other roadblocks include a lack of vertical and horizontal scalability as well as analytics and AI/ML adoption. Slow, never-ending modernization, high data analytics investment, and maintenance costs pose additional challenges.

Key Considerations of Data Migration

How do we ensure that your data migration project is a success? There are certain factors that we need to keep in mind. Here is a breakdown of the critical considerations of any data migration project and how you should approach them:

Race to the Cloud with Sprinter

From our experience, we know that just offering a guidebook will not help unlock all the benefits of cloud data migration. Hence, Sprinter was designed to harness the best practices and tools to automate migration activities and fast-track the migration journey to the Microsoft Intelligent Data Platform. Tech Mahindra’s Sprinter supports activities like discovery, schema migration, SQL migration, data migration, and data validation, which drastically reduces overall effort and increases the efficiency and accuracy of any Cloud data migration. Sprinter's multi-featured modular architecture can be used separately or in tandem for “data migration to cloud” journeys.

Sprinter, is part of Tech Mahindra's D.A.H.L.I.A Platform (Data Analytics Hub for Large Scale Insights Acceleration), which has multiple Gen AI embedded Data Analytics solution accelerators across data value chain, right from Data Ingestion to Consumption layer that helps to expedite Organization’s journey towards Data Driven Ingestion

Sprinter’s Search & Discovery feature helps assess the workload and inventory of the on-premises Data Platform. It leverages industry best practices and checklists to discover and prioritize use cases. With Sprinter, you can also set up data governance, data security, and performance benchmarks. Similarly, the Sprinter Price Estimator tool lets you estimate the cost of building a data warehouse in the Microsoft Azure cloud.

Once you finalize the migration strategy, you can use the Sprinter Schema Migrator to migrate schema from the source database to the cloud database. The SQL Migrator, powered by GenAI, simplifies cloud migration of SQL, DMLs, stored procedures, and ETL scripts. At the same time, the Data Migrator uses Microsoft Azure Data Factory to manage the historical and incremental data load.

But that's not all. Leverage the Sprinter Data Validator to validate and verify migrated data and Sprinter Auto DQ to detect data anomalies using AI/ML algorithms. The Sprinter Monitoring and Tracking module monitors warehouse usage, user audit, and user query metrics and delivers insight through Microsoft Power BI.

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Together, We Can Simplify Your Data Journey

Data migration is a necessary yet tricky process. It can even be the playing field for legacy brands competing with cloud-native companies. To help the incumbents stay abreast of the ongoing technological revolution and plant their feet firmly in the cloud, Tech Mahindra has partnered with Microsoft. As the future is data-driven and cloud-native, seamless migration is a core part. Together, we are pushing the envelope for a digitalized future and ensuring the smooth digitalization of enterprises. Contact us to learn how Sprinter can launch you to the Cloud.