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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...

SAS Visual Analytics top features useful to your project

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You may already know that SAS is king in visual analytics. The real features that SAS provide you can learn here.I have collected some features on SAS analytics. 

SAS Visual Analytics is an easy to use, web-based product that leverages SAS high performance analytic technologies and empowers organizations to explore huge volumes of data very quickly in order to see patterns and trends, and to identify opportunities for further analysis. 

"SAS Visual Data Builder enables users to summarize data, join data, and enhance the predictive power of their data. Users can prepare data for exploration and mining quickly and easily."
The highly visual, drag and drop data interface of SAS Visual Analytics Explorer combined with the speed of the SAS LASR Analytic Server accelerates analytic computations and enables organizations to derive value from massive amounts of data. 

This creates an unprecedented ability to solve difficult problems, improve business performance, and mitigate risk rapidly and confidently. SAS Visual Analytics Designer enables users to quickly create reports or dashboards, which can be viewed on a mobile device or on the web.

Advantages

  • SAS Visual Analytics empowers business users, business analysts, and IT administrators to accomplish tasks from an integrated suite of applications that are accessed from a home page. 
  • The central entry point for SAS Visual Analytics enables users to perform a wide variety of tasks such as preparing data sources, exploring data, designing reports, as well as analyzing and interpreting data. Most importantly, reports can be displayed on a mobile device or in the SAS Visual Analytics Viewer.

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