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Before data on any platform will become an asset to any organization, it has to pass through processing stage to ensure quality and availability. Afterward, that data has to be available to users (both human and system users). The availability of quality data in any organization is the guarantee of the value that data science (in general) will be to that organization.
We are using the airline on-time performance dataset (flights data csv) to demonstrate these principles and techniques in this hadoop project and we will proceed to answer the below questions -
We will also transform the data access model into time series and demonstrate how clients can access data in our big data infrastructure using a simple tool like the Excel spreadsheet.
In this hive project, you will design a data warehouse for e-commerce environments.
In this big data project, we will continue from a previous hive project "Data engineering on Yelp Datasets using Hadoop tools" and do the entire data processing using spark.
In this hadoop project, we are going to be continuing the series on data engineering by discussing and implementing various ways to solve the hadoop small file problem.