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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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Course Topics You Need to Know Before You Take Course on Excel

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Hey, you want to be master in Excel. There are 4 parts in this course. These contents cover all the functionalities you need to work with Excel.
Excel is one of the tools to be used in data analytics
Why I have given contents means these you must ask your tutor if present in the course or not. This list useful to start a career in analytics.

List of Excel Course Topics

Part-1 - Importing Data from other sources

  • Import or Export data from multiple data sources

Part-2 - Converting data Excel ready

  • Formatting the data understand by EXCEL.

Part-3 - Data Mining

  • Formulas you need for Data cleaning.

Part-4- Excel Data Analysis Tools

  • Data analysis using statistical methods, Charts and Pivot Tables

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