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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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The 5 Skills You need to Start Data Analytics Career

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Data analytics is the job role hot in demand in each organization. Digital skills such as Mobile development, Full-stack development, Data Science, and Cloud computing are successful because they are very user-friendly to the end-users.


skills in-demand

Digital devices enabled digital technologies to cause to generate more data. You need different kinds of tools to analyze data in different formats.

You need the right tools. Else you cannot predict the user's mind. User search data is the source of big retail markets. Based on these search words, they start selling the products.

The motto behind data analytics is to get the benefit all stakeholders. Let us take cloud computing the main advantage is cost-effectiveness and scalability.

5 Skills you need for data analyst job

  1. R Programming
  2. SAS
  3. Excel
  4. Tableau
  5. QlikView

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