Avoid cloud data chaos - Capitalize on your Snowflake investment

Ensure a smooth, governed and disruption-free migration with Quest's framework for before, during, and after the move.

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The Playbook Common Pitfalls FAQs

Common Pitfalls in Data Migrations

Dark Data – Poor Organization & Governance

Security and Compliance Risks

Lack of a Clear Use Case

Performance & Cost Challenges

Integration Issues

Dark Data – Poor Organization & Governance

Dark data can inflate migrations with irrelevant or outdated information, increasing costs, slowing performance, and hiding critical insights. Without strong data governance, organizations risk carrying over security vulnerabilities, compliance issues, and inefficiencies into the new system.

Failure to implement role-based access or encryption strategies can leave critical data exposed. Often sensitive data is stored without proper classification or access controls, increasing rick of breach or regulatory violations.

Rushing into modernized data structure without defining clear business objectives leads to wasted resources. Without a defined roadmap of how data will be used (e.g. analytics, AI, real-time decision-making), the data lake becomes an expensive dumping ground

Migrating vast amounts of data without optimization leads to inefficiencies – querying unstructured data at scale can slow analytics and inflate storage costs. Additionally, poor indexing, duplicate data and excessive redundancy can increase costs without adding value.

Legacy systems can struggle to interact with modern data lakes, creating silos instead of a unified ecosystem. Without standardizing before migration, compatibility issues arise and can require expensive post-migration fixes.

Frequently Asked Questions

I can migrate into the data lake without modelling. Why do I need a modelling solution?

Transitioning data from legacy systems into a modern data lake is complex and prone to errors. Our solution streamlines the migration process ensuring that data integrity, consistency, and security are maintained at every step. This saves time and avoids operational disruptions compared to a direct, unassisted move.

Why is real-time data replication essential for a data lake strategy?

Our platform ensures that your data lake is continuously updated through real-time data replication, bridging the gap between your operational systems and analytics environments. By seamlessly replicating data as it changes, our solution guarantees that every piece of information is available for immediate analysis, empowering agile decision-making.

Can I demonstrate clear return on investment and value to the business?

Investing in a data lake should drive tangible business outcomes. Our solution not only reduces costs by eliminating redundant data but also enhances decision-making speed and analytics capabilities. By tracking key performance metrics, we help you demonstrate the value and ROI of your data lake transformation, making it easier to justify your investment.

Can I track data quality, pipeline performance and system usage after migration?

A data lake is only as valuable as its accessibility and performance. Our solution provides built-in monitoring and management tools that track ingestion rates, query performance, and resource utilization. With continuous optimization monitoring, you’re never caught off guard by performance issues.