Tag - Hadoop Data Lake

Why Kappa Architecture for processing of streaming data. Have competence to superseding Lambda Architecture?

Data is quickly becoming the new currency of the digital economy, but it is useless if it can’t be processed. The processing of data is essential for subsequent decision-making or executable actions either by the human brain or various devices/applications etc. There are two primary ways of processing data namely batch processing and stream processing. Typically batch processing has been adopted for very large data sets and projects where there is a necessity for deeper data analysis, on the...

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Data Absorption (Ingestion)

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Distributed Incubator

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Data Ingestion phase for migrating enterprise data into Hadoop Data Lake

The Big Data solutions helps to achieve valuable information to iron out the accurate strategic business decision. Exponential growth of digitalization, social media, telecommunication etc. are fueling enormous data generation everywhere. Prior to process of huge volume of data, we should have efficient data storage mechanism in a distributed manner to hold any form of data starting from structured to unstructured. Hadoop distributed file systems (HDFS) can be leveraged efficiently as data lake by installing on multi node cluster....

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Basic concept of Data Lake

The left side info graphics represents the basic concept of Data Lake where we can use the approach of ELT (Extraction, loading and then transformation) against traditional ETL (Extraction, Transformation and then loading) process. ETL process implies to traditional data warehousing system where structured data format follows (row and column). By leveraging HDFS (Hadoop Distributed File System), we can develop data lake to store any format data in order to process and analysis. Directly data can be loaded in the Lake...

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