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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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SAP HANA Top new Applications

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The SAP HANA analytics from German software vendor SAP AG is betting heavily on a new generation of analytic computing it calls HANA.  In this post you will know the new features that are added in HANA. To maintain its position as the world's largest business-application vendor. So, learning HANA is really good and make sure these HANA course contents you need to have in your training. SAP HANA Applications HANA, which is already installed at more than 200 customer locations, processes data in real-time by storing it in live memory rather than in a separate data warehouse, enabling customers to make business decisions faster. >> Liquor distributor Charmer Sunbelt Group finished installing a HANA system , and it says it has helped managers react to logistical problems as they occur. Getting shipments out is essential for Charmer because customers can refuse them if they are late. >> According to Chief Information Officer Paul Fipps, HANA h...
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