Denodo Platform 9 Certified Developer Professional study plan
Denodo Platform 9 Certified Developer Professional · Give each week a clear focus.
8 weeks · About 7 hours per week
Virtual DataPort: Derived Views, Joins, Unions, and Query Optimization
Map every derived view type (selection, projection, join, union, aggregation, flatten, intersect, minus) to a concrete scenario and build a working view for each in a local Virtual DataPort instance
Create at least three join types (inner, left outer, full outer) across two base views and inspect the generated execution plan to identify where the join is pushed down versus executed in Denodo
Rewrite one slow join as a materialized-style derived view and compare query traces before and after to quantify the improvement
Explain in writing when a union versus an intersect or minus view is the correct modeling choice, with one example each
Your checkpoint
A documented notebook of 8+ derived views with annotated query traces showing at least one pushdown optimization decision per join
Virtual DataPort: Derived Views, Joins, Unions, and Query Optimization & Caching, Query Acceleration, and Performance Tuning
Apply the main query optimization levers (join order, join type selection, aggregation pushdown, subquery delegation, cost-based optimization hints) to a deliberately inefficient query and record each change's effect
Configure and validate a cache module on a derived view, including cache mode, invalidation schedule, and TTL, then prove the cache is hit using query statistics
Identify and fix at least two anti-patterns such as unnecessary DISTINCT, non-delegable functions in WHERE clauses, or cross joins that block pushdown
Build a baseline performance test with three representative queries and capture elapsed time and rows processed
Your checkpoint
A before/after optimization report for one end-to-end scenario, with a table of the five changes made and their measured impact
Virtual DataPort: Data Sources, Base Views, and Connection Management
Create base views over at least four source types (relational JDBC, delimited file, JSON/REST, and one additional such as XML or Excel) and configure each data source's connection pooling
Configure schema refresh and incremental metadata update for one base view, then trigger a change at the source and verify the view updates without breaking downstream views
Set up a JDBC data source with correct connection pool sizing, validation query, and timeout settings, and explain the effect of each parameter
Diagnose and resolve two deliberate connection failures (bad credentials, unreachable host) using Virtual DataPort logs
Your checkpoint
A working multi-source Virtual DataPort environment with four base views, documented connection settings, and a troubleshooting log of two resolved failures
Data Security: Authentication, Authorization, and Data Masking & Data Modeling and Governance: Associations, Tags, and Metadata
Configure two authentication mechanisms (local database and LDAP or another external provider) and assign users to roles with least-privilege grants
Implement row-level and column-level security on a derived view using a policy that filters by session user, then verify with two different logged-in users
Apply data masking to at least three sensitive columns, choosing between masking and encryption based on whether the consumer needs the original value
Create associations between related views and apply tags and descriptions so that the metadata is discoverable through search
Your checkpoint
A security and governance configuration sheet showing each role, its grants, the masking rule per column, the associations created, and evidence from two user sessions
Data Services and APIs: REST, SOAP, OData, and GraphQL Publishing
Publish one derived view as a REST web service and one as an OData service, then call each successfully with a client tool and capture the request and response
Publish a SOAP web service and a GraphQL endpoint over the same or a related view, and compare the payload shape and filtering capability across the four protocols
Configure at least two service-level controls such as pagination, result limits, output format, or authentication on the published interfaces
Document when each protocol is the right choice for a consuming application
Your checkpoint
A published API catalog covering REST, SOAP, OData, and GraphQL with sample requests, sample responses, and a one-paragraph selection guide
Caching, Query Acceleration, and Performance Tuning & Denodo Scheduler: Jobs, Data Movement, and Incremental Loads
Create a Scheduler job that performs a full load into a target and a second job that performs an incremental load using a timestamp or sequence watermark
Run the incremental job twice with intervening source changes and verify that only new or changed rows are transferred
Configure job scheduling, error handling, and notification, then force a failure to confirm the alert path works
Tune one slow job by adjusting parallelism or batch size and measure the change
Your checkpoint
Two working Scheduler jobs (full and incremental) with execution logs proving correct incremental behavior across two runs
Denodo Design Studio and Solution Manager: Development Lifecycle and Deployment
Export a project from Design Studio, import it into a second environment through Solution Manager, and resolve any dependency or revision conflicts that arise
Create a tagged revision or snapshot before a change, apply the change, and demonstrate rollback to the prior state
Use the elements and dependency view to identify everything affected by modifying one base view before making the change
Write a short promotion checklist covering what must be verified before moving a revision to production
Your checkpoint
A completed promotion run from development to a second environment with revision history, a rollback demonstration, and the promotion checklist
Denodo Platform Architecture, Installation, and Administration & Caching, Query Acceleration, and Performance Tuning & Data Security: Authentication, Authorization, and Data Masking
Describe the role of the main platform components (Virtual DataPort server, administration tool, Scheduler, Solution Manager, cache and embedded databases) and how they communicate
Review server configuration and diagnostic tooling, including log levels, monitoring queries, and health checks, and use them to investigate one simulated issue
Re-run the week 2 performance baseline and the week 4 security checks to confirm nothing regressed
Take two timed practice assessments weighted toward domains 2, 4, and 6, and review every missed item by returning to the underlying concept
Your checkpoint
A consolidated final review pack containing the architecture summary, regression results from the performance and security re-checks, and a list of weak areas with remediation notes
Milestones
Week 2: You can build a multi-source join, explain where pushdown occurred from the execution plan, and show a measured speedup from at least one optimization or cache change
Week 4: Two users with different roles see different rows and masked columns from the same view, and the associations and tags you created are findable through metadata search
Week 6: All four API protocols return valid responses from your published views, and a Scheduler incremental job transfers only changed rows on its second run
Week 8: A project has been promoted through Solution Manager with a demonstrated rollback, the performance and security baselines still pass, and practice scores show domain 2 and domain 4 above 75 percent