Explain all three steps involved to deploy a Big Data Solution?

Data ingestion, or the extraction of data from diverse sources, is the initial step in the deployment of a big data solution. A CRM like Salesforce, an ERP like SAP, an RDBMS like MySQL, or any other log files, documents, social media feeds, etc., could be the data source. Either batch jobs or real-time streams can be used to ingest the data. The obtained information is then kept in HDFS.

Data Storage: The Second Step in Deploying a Big Data Solution

The next step after data input is to store the extracted data. Either a NoSQL database or HDFS will be used to store the data (i.e. HBase). HBase is better for random read/write access, while HDFS storage is better for sequential access.

Data processing is the last stage of deploying a big data solution. One of the processing frameworks, such as Spark, MapReduce, Pig, etc.