How does Docker Assist Big Data analyst (Nov 9th - Nov 15th 2020)

 As we dive deeper into the semester we start to learn more tools that will assist us with open-source networks. For this particular week, I looked into how docker will assist someone in a bigdata concentration like myself. While doing my research I found out that docker allows us to put data or large files into containers. Which will allow us to deliver and respond much quicker to the customer with the use of docker. This is enabled not only the customer but the data scientist to have a more organized platform for information to be transferred. This is valuable because instead of having to go through multiple platforms to transfer information instead of with the use of docker you are able to use one platform to put the information into a container which will then transfer it to the client. With the power of docker, it allows big data scientist to be self-sufficient and build effective models which can be tested and modified on multiple occasions without having to change the main structure of the data. The use of docker allows us to have the developer systems and production environment to be constant and be monitored under the same platforms, while prior to docker we were unable to do such a thing because the environments would always switch up and not be uniform. Some tremendous features that docker allows us to have are the ability to multi-task between two separate nodes. The assistance of docker allows us to create multiple Hadoop clusters and nodes in order to run multiple databases and processors without overloading your computer. Another great benefit is the superior security, and speed given to us with the use of docker in the spectrum of using virtual machines.  Another benefit to docker in the big data ecosystem is it allows us the user or data scientist to develop microservices which can be independent modular services that can be opened up from any computer in order to work on the project while on the go. the main benefit is the ability to have an easier application and scalability of data. Docker will also allow us to be able to build a multi-cloud distribution system. In other words, this allows us to extract big data files without having to use powerful data processing systems and the needless requirements of installing complex and large analytics tools. Finally, more systems should incorporate docker into their platforms because it allows us to package the information as applications, dependencies to be deployed as one single package.