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Data Engineer
Accelerate your Data Engineering career: Discover best practices, and learn the latest trends.
Data engineering is the process of discovering, designing, and building the data infrastructure to help data owners and data users use and analyze raw data from multiple sources and formats. This allows businesses to use the data to make critical business decisions. You can revisit the definition of data engineering here. If you want to dig a little deep we recommend taking a look at the four fundamentals of data engineering:
- Data discovery and lineage
- Data ingestion
- Data processing
- Data quality

Explore the different components of Data Engineering and stay up to date with the latest trends, technologies, troubleshooting techniques, and best practices.
Unleash the power of data by building an AI-powered modern data architecture

5 Data Engineering Trends You Must Master to Stay Competitive

Artificial Intelligence for the Data-Driven Intelligent Enterprise
Discover, understand, trust, and access relevant data to generate business value

What is Data Discovery and Why Does it Matter?

Setting Your Sights on Data Intelligence
Replicate and ingest data from applications, databases, streaming sources, and files using a simple, wizard-driven experience.

Cloud Mass Ingestion Data Sheet

Artificial Intelligence for the Data-Driven Intelligent Enterprise
Build, deploy, and operationalize low-code data pipelines at scale

5 Reasons to go Serverless to Achieve Your Cloud Data Integration Needs

Faster, More Cost-Effective Cloud Data Integration CDI-Free
Profile, cleanse, standardize, and enrich all data using an extensive set of prebuilt data quality rules.

Informatica Cloud Data Quality and Cloud Data Integration – Solution Brief

Data Quality in the Cloud Data Warehouse
Open, embeddable, and extensible headless data management for data engineers

Faster, More Cost-Effective Cloud Data Integration CDI-Free
Build, deploy and monitor your AI/ML models at scale

MLOps: How to Operationalize Machine Learning Models in 5 Steps

Informatica ModelServe: Put AI into Action