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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...

Beginner's Tutorial on SaS Visual Analytics

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SAS visual analytics is a completely new architecture from SAS. It has the capability to manage large amounts of data and bring it into memory to analyze it, explore it and publish reports.  Although the data amounts are massive — up to 1.1 billion rows of data, the SAS LASR Analytic Server, to use its full name, was designed to be intuitive to users without an advanced degree in computer science. A report from Simply hired. All about SAS analytics Server - The SAS Analytic Server begins with an eight-blade server with 96 processor cores, 768 gigabytes memory and 4.8 terabytes (TB) of disk storage.  The upper end of the reference configurations is 96 blades with 1,152 cores, 9.2 TB memory and 57.6 TB of disk storage, enough disk space to store the entire Library of Congress six times. Where to Learn SAS Visual Analytics Also read:    Modelling with SAS a detailed video course to get instant benefit  The real SAS Visual analytics benefi...

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, a...