Are you still stuck with an on-premise setup? Migrating to a cloud-based infrastructure is no longer just an option; it's imperative for organizations that aim to modernize their operations. By 2026, end-user cloud spending is estimated to grow at about 50%, with a 20% yearly growth, according to Gartner, with over $675 billion in 2024 alone. This massive data shift has led companies to prioritize data migration and quality. According to SAP, $3.1 trillion is lost annually in the US due to poor data quality - a figure no organization can afford.
Why Migrate to Cloud-Based Infrastructure
The benefits of a cloud-based infrastructure are unparalleled: scalability, enhanced security, and cost-efficiency. According to Flexera's 2024 State of the Cloud Report, 89% of all enterprises now adopt a multi-cloud strategy, with 88% prioritizing cost optimization. The ability to scale operations on-demand is a game-changer for businesses across all verticals.
- Cost efficiency: All major cloud providers have a pay-as-you-go cloud computing model. This drastically reduces the hardware and maintenance costs of running physical servers.
- Enhanced security: Cloud platforms are built to inherently have top-notch security such as encryption, identity management, and regulatory compliance (GDPR, HIPAA), which safeguards sensitive information
- Scalability: All clouds are designed to be scalable on-demand, which means that you do not have to worry about unexpected spikes in cloud computing demands
However, a poorly executed data shift can lead to significant data quality issues. As reported by Forrester Research, 7% of data practitioners reported losing $25 million due to data quality issues, with a majority losing over $5 million. This is mostly because organizations experience data quality degradation post-data migration, mostly due to a lack of data quality assurance protocols.
The Importance of Data Observability in Cloud Migration
Quality assurance in data migrations is not just about avoiding error - it is about ensuring that data remains accurate, consistent, and complete throughout the entire cloud migration process. One of the key innovations driving cloud migration strategies is Data Observability. With observability tools like Acceldata, businesses can monitor every aspect of their data pipelines in real time, ensuring that data quality issues are detected and resolved before they impact operations.
- Real-time visibility: Platforms like Acceldata offer organizations real-time insights into data flow and pipeline performance, which helps detect issues before they escalate into significant problems
- Data governance: Businesses can enforce data governance rules during the Data Shift, ensuring that the data complies with internal and external regulatory standards
- Quality assurance: Besides making sure that the data is present, it is critical to implement best-in-class Data Quality Management standards
Acceldata has been instrumental in helping companies reduce their time-to-market by enabling faster and more reliable data migration. A Global Retail Giant used Acceldata's data observability features to monitor its complex data migration, which led to a 30% faster migration while maintaining zero data loss.
Key Strategies to Maintain Data Quality During Cloud Migration
When migrating to the cloud, maintaining data quality is paramount. Following are the Cloud Migration Strategies to implement to have a seamless Data Migration:
Pre-migration assessment
Start with a thorough audit of your existing data systems. This can help you identify potential data quality issues beforehand, which can help mitigate issues down the road.
- Data profiling: Profile your data before migration, which can help with an in-depth analysis of the data landscape, uncovering hidden issues that can impact migration
- Stakeholder engagement: Involve all key stakeholders early in the process to help ensure that the migration strategy aligns with the business objectives
Phased migration approach
Take your time to lift and shift. The approach that balances results and efficiency is moving the data in phases, which minimizes the risk of large-scale errors and allows for real-time quality checks. The role of Data Observability must be considered.
- Mitigate risks: A phased approach ensures migration errors are confined to smaller datasets, making troubleshooting and correcting problems easier.
- Rollback options: By migrating in phases, you can easily roll back to previous versions if any critical issues arise
Real-time monitoring, automation, and testing
Automation to monitor data pipelines in real time is key to reducing human error. Using Acceldata's Automation tool, T-Mobile verified over 45 billion rows for data quality, with a 20% reduction in storage consumption by eliminating 9PB of stagnant data.
- Machine learning for error detection: Machine Learning on Data Observability Platforms can be used to detect anomalies
- Data validation automation: Data Validation tests can be automated to ensure that the data remains accurate through the migration, which reduces reliance on manual processes
- User acceptance testing: Involve the end-users in the testing phase to ensure that the migrated data meets their needs and works in their systems
- Performance monitoring: Post-migration, Acceldata provides continuous performance monitoring to ensure that the new infrastructure is performing as expected
Ensure a Seamless Data Shift with Acceldata
Acceldata, a leader in data observability, has become an essential partner in managing complex migrations. They ensure that companies optimize their pipelines while maintaining a high standard of data quality. One notable Global Information Provider partnered with Acceldata to work on their data quality on a multi-petabyte database. This was done by checking over 500 billion rows with over 200+ rules for data checks to achieve a 96% reduction in data quality issue resolution time.
Migrating to cloud-based infrastructure is essential for modern businesses. However, it must be done with a focus on quality assurance to prevent costly errors and data inconsistencies. Acceldata provides the tools to ensure a seamless data shift, offering real-time visibility, automation, and comprehensive testing solutions. Acceldata's proven track record in finance, retail, healthcare, and telecommunications enables businesses to achieve successful migrations with minimal disruption and maximum data integrity. Ready to delve deeper into an All-in-One Enterprise Data Observability Platform - Request a Demo with Acceldata today!
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