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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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How to use Blockchain on Cloud

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Blockchain applications are growing in the financial world. Security is the main motto behind blockchain applications. You cannot tamper a record once created. What is a platform   A platform is a place where you can develop applications. Top Blockchain Cloud Platforms The development needs to create a project and deploy it into production. So that the real use can feel by users at their end. Ok... Let us come to three popular cloud platforms that are highly used in Blockchain applications: HyperLedger IBM BlueMix Microsoft Azure #1. HyperLedger The Hyperledger project is led by Executive Director Brian Behlendorf, who has decades of experience dating back to the original Linux Foundation and Apache Foundation, as well as being a CTO of the World Economic Forum. So it's not surprising that Hyperledger has been well received. You can learn hyper Ledger here. Many of the top business and industry leaders have joined the project, including Accenture, Cisco, Fujitsu ...
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