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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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Talent Analytics on employees to measure real worth

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Human resource managers are currently embracing talent analytics like never before. Companies are evaluating and analysing raw data to derive valuable insights which are helping them to hire the right talent, retain them as well as help them learn and grow internally.
talent analytics

Data to do analytics

Talent analytics companies take into account all the data, rather than limited samples, so a full-fledged picture emerges. 

It looks for patterns in the data and discovers critical connections that might otherwise go unnoticed. Such data can be related to employees' pre-employment assessments to background checks to social media profiles.

How data will gather

They also gather data on the characteristics of their most successful employees. When big data is tapped this way, HR managers no longer need to depend on intuitions of interviewers and hiring managers or rely on obsolete hiring tools of yesteryears. 

Organisations are also leveraging big data to hire and promote top performers who will enable companies to meet with their dynamically changing business needs.

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