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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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Excel Analytics: The complete best explained Free Tutorials

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Can you do analytics—either kind—using Excel? Sure. Excel has a large array of tools that bear directly on analytics, including various mathematical and statistical functions that calculate logarithms, regression statistics, matrix multiplication and inversion, and many of the other tools needed for different kinds of analytics. But not all the tools are native to Excel. 

 For example, some situations call for you to use logistic regression: a technique that can work much better than ordinary least-squares regression when you have an outcome variable that takes on a very limited range of values, perhaps only two. Odds ratios are the workhorses of logistic regression, but although Excel offers a generous supply of least-squares functions, it doesn’t offer a maximum likelihood odds ratio function. 

The below list makes you strong in Excel analytics

  1. Microsoft Excel 2010 Data Analysis With Functions
  2. Analytics with Excel - Book
  3. Cloud data analytics from Excel
  4. Quantitative Analysis with Excel
  5. Data Analysis Using SQL and Excel
  6. Excel Analytics 

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