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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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IT Skills you need to get top jobs in e-commerce

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Technology and digital marketing-related skills are in huge demand as e-commerce companies have got big-ticket investments.

IT Skills for e-comm jobs
IT Skills for e-comm jobs
Technologies in Demand

Domestic consumption of technology, especially in mobile telephony, is on the rise. The traditional IT services sector is likely to see a spurt in hiring as demand revives in Europe, along with expected economic turnaround at home.

Hot in Demand IT areas

According to Teamlease, this category will provide opportunities for a wide range of people:
  • beginning with IT infrastructure managers
  • mobile developers on IOS, Android, and Windows
  • languages like Python, Ruby on Rails, HTML, and CSS
  •  IT security
  • cloud computing professionals.
  • Experience developing applications using technologies such as Java, Node.js, HTML5, JavaScript, SpringBoot, Tomcat, and Selenium.

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