What Data Models Need to Change When Migrating to Looker?

As enterprises embrace modern BI platforms, migrating from legacy systems like IBM Cognos to Google Looker has become a key step in transforming their analytics ecosystem. While the benefits—such as faster reporting, cost reduction, and centralized data management—are clear, one critical aspect that determines migration success is the data model transformation. At Squareshift, our certified Looker experts help businesses redesign their data models to fully leverage Looker’s semantic layer and self-service capabilities.

Understanding Data Model Transformation in Looker

Unlike Cognos, which relies on pre-aggregated reports and static metadata models, Looker uses a semantic modeling layer called LookML. This allows organizations to define reusable logic for metrics, joins, and data relationships directly in code.

When migrating, companies need to revisit their:

  • Data structures – Flatten overly complex hierarchies and ensure compatibility with SQL-based data warehouses.
  • Relationships and joins – Redefine joins and aggregations for efficiency in LookML.
  • Metrics and dimensions – Translate existing KPIs into LookML parameters that support drill-down analysis.
  • User access models – Redesign permissions using Looker’s role-based access controls to enhance governance and security.

Key Data Model Changes When Migrating to Looker

From Metadata Layers to LookML Models

Cognos’ Framework Manager models need to be rebuilt in LookML, where logic is modular, transparent, and version-controlled. This makes updates easier and reduces report maintenance time by up to 40%.

Centralized Logic for Consistency

In Looker, measures and dimensions are defined once and reused across dashboards. This ensures a single source of truth, improving data accuracy and reducing manual data preparation by 30–50%.

Optimized SQL for Cloud Data Warehouses

Since Looker connects directly to databases like BigQuery, Snowflake, or Redshift, optimizing SQL logic for these platforms enhances query performance by up to 2x compared to traditional OLAP models.

Data Governance Enhancements

By integrating Looker’s version control and Git-based workflows, teams gain stronger governance and traceability across data assets—reducing compliance risks and unauthorized data modifications.

Why Enterprises Choose Squareshift

At Squareshift, we bring proven migration experience and a strong track record of helping enterprises transition to Looker seamlessly. Our looker certified experts guide clients through every stage—from model assessment and redesign to validation and user enablement.

  • Recognized by industry analysts for our cloud analytics expertise.
  • Trusted by global clients across retail, finance, and manufacturing sectors.
  • Documented looker success stories—including a leading U.S. insurer that achieved 60% faster dashboard refresh times and 35% lower infrastructure costs after partnering with us.

The Squareshift Migration Advantage

Our migration approach emphasizes:

  • Comprehensive model audits to map Cognos entities to LookML structures.
  • Iterative testing for accurate metric translation.
  • Automated migration tools to reduce manual effort and human error.
  • Post-migration enablement, ensuring teams adopt Looker efficiently.

Driving the Future of Data-Driven Decisions

Migrating to Looker isn’t just about shifting tools—it’s about empowering data-driven decision-making with scalability and speed. With Squareshift’s expertise, enterprises gain cleaner data models, faster insights, and sustainable analytics growth.

Whether you’re modernizing your BI stack or planning a large-scale data transformation, Squareshift’s certified Looker experts can help you architect, migrate, and optimize your analytics for the cloud era.

Ready to accelerate your Cognos to Looker migration?

Partner with Squareshift—your trusted ally in intelligent data transformation.

Location: United States

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