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Informatica Power Center

⬢ NIVÅ 2Verktyg
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3 månader
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Informatica Power Center is the leading enterprise ETL (extract, transform, load) platform used by 5000+ companies. You design data pipelines: extract from SAP/Oracle/Salesforce, transform (join, aggregate, enrich), load to data warehouse. Mastery takes 5-7 weeks of mapping design, workflow optimization, and performance tuning. Senior Informatica architects earn 20-30% premium because they reduce manual ETL dev by 70% and pipeline failures by 50%. It's rare: requires both SQL knowledge AND visual ETL thinking.

Vad är Informatica Power Center

Informatica Power Center is an enterprise data integration platform (ETL) used by 5000+ Fortune 500 companies. It extracts data from source systems (SAP, Oracle, Salesforce, databases), transforms it (joins, aggregates, enriches), and loads it into data warehouses (Snowflake, Redshift, Teradata). It's a visual tool: you draw pipelines (source → transformation → target) without writing code. Under the hood, it generates SQL and distributes execution across parallel threads.

🔧 VERKTYG & EKOSYSTEM
Informatica Power CenterInformatica DesignerInformatica Workflow ManagerInformatica RepositorySource systems (SAP, Oracle, Salesforce)Data warehouses (Snowflake, Redshift, Teradata)SQLScheduling tools (Control-M)

💰 Lön per region

OmrådeNybörjareMidErfaren
USA$72k$118k$180k
UK£44k£72k£110k
EU€50k€80k€125k
CANADAC$70kC$115kC$175k

❓ Vanliga frågor

How does Informatica compare to modern tools like dbt?
Informatica is enterprise ETL: handles low-level integration (SAP connectors, CDC, error handling). dbt is SQL-focused transformation (great for cloud warehouses). Use Informatica if integrating from legacy systems (SAP, Oracle); use dbt if data is already in a cloud warehouse. Many companies use both: Informatica for landing, dbt for transformation.
What's a mapping in Informatica?
A mapping is a blueprint for transforming data. It defines: source (table/file), transformations (expressions, lookups, joins), target (warehouse table). Mappings are reusable building blocks. Workflows orchestrate mappings (run mapping1, then mapping2 if mapping1 succeeds).
How do I optimize a slow Informatica pipeline?
1) Partition data: process 1M rows in 4 parallel streams, not serial. 2) Reduce lookups: cache lookups instead of querying for every row. 3) Push predicates down: filter at source (SQL WHERE clause), not in Informatica. 4) Tune DTM (Data Transformation Manager) process: increase memory, threads. 5) Profile data first (what bottlenecks?).
What's the difference between mappings and workflows?
Mapping = transformation logic (source → transform → target). Workflow = orchestration (run mapping A, then mapping B if A succeeds, else send alert). Workflow is the 'engine'; mapping is the 'task'.
How do I handle data quality issues in Informatica?
Use rejection filters: if a row fails validation, send to a 'bad data' table, not the target. Log the error. Later, investigate and reprocess. Keep good/bad data separate for auditing.
Can Informatica handle real-time streaming?
Power Center is batch ETL (daily, hourly loads). Informatica Streaming (separate product) handles real-time Kafka/Pub-Sub streams. For real-time, use Informatica Streaming or Apache Kafka + Spark/Flink instead.

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