Big Data Landscape

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Data Landscape is the systematic assessment of creating, receiving, processing, and disseminating an organization's data. It is seen as a knowledge graph, a collection of interlinked descriptions on a particular knowledge domain, including entities of relationships, interfaces, and data flows. They can range from the data warehouse, relational databases, and scientific softwares to omic analysis tools with internal or public databases.

A big data environment is a dynamic environment, continuously fetching data from a greater pool of sources. It is so rigorous that it eventually becomes impossible for data handlers running the big data environment to rightly define the origin and content of all the data sets in the contains.

The three fundamental principles guiding big data are:

• 1. Collect a considerable amount of data for particular use case and aggregate them 
• 2. Identify and scrub sensitive data 
• 3. Always have an alternative method in case the scrubbed insights fail. 

Big data gives an organization the power to collect more and better marketing-related data about the users, which will help marketers understand better what the users want, what users use, and what channels are regularly used for commodity flow. With this data, it is now even easier to customize the content to target potential customers and drive sales.