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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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Top Teradata Course details that you need to learn

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Teradata is most popular database among data warehousing projects. You will learn Teradata from any institute you want. My post intention is you just take a look on course contents you need to learn. Course Contents You Need to Look Before You Start Related: Top Data warehousing Interview Questions Introduction to Teradata Data warehousing concepts and SCD’s OLTP & OLAP Teradata Architecture & Physical Design Teradata Vs. Other RDBMS BYNETPEs AMPs Vprocs Clique Cluster Data Storage Data Distribution Data Access Teradata Space Management Fault Tolerance Data Protection Teradata Indexes and Performance Tuning and Optimization UPI – Unique Primary Index NUPI – Non Unique Primary Index USI – Unique Secondary Index NUSI – Non Unique Secondary Index PPI – Partition Primary Index MLPPI – Multilevel Partition Primary Index STJI – Single Table Join Index MTJI – Multi Table Join Index AJI – Aggregate Join Index Global Temporary Tables and Vola...
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