Layers of Big Data

Six Layers of Big Data:

1: First, the Data Ingestion layer takes in all kinds of data including: structured data; unstructured data; data from devices, sensors, logs, click streams, and applications; and data from both cloud and on premises sources.

2: Next, the Processing and Persistence layer is performed by cloud based systems such as Hadoop and Spark.

3: The Orchestration layer handles transformation and cleansing.

4: The Data Discovery layer is the critical next step, because it solves the silo problem, and it does that using a mixture of data modeling, data preparation, data curation, and data virtualization. Data virtualization creates a combined, virtual view of the data across two or more silos, which can be accessed by consumers in real-time as if the disparate silos were part of the same dataset.

5: The Data Management and Intelligence layer provides security and governance across the other five layers.

6: Finally, the Data Access layer delivers the data directly to analysts or to applications, tools, and dashboards.