LEARNING MACHINE: From Data Science to Data Quality: When an Algorithm Includes a Company's Performance in the Digital Age (Artificial Intelligence Book 2) by Mazziotti Tommaso

Author:Mazziotti, Tommaso [Mazziotti, Tommaso]
Language: eng
Format: epub, pdf
Published: 2020-08-02T00:00:00+00:00

Chapter 6 — Data Science Lifecycle and Technologies

Data Science Lifecycle

The data analyst is going to spend some time explaining what is going on because they are able to process the history that the data went through. On the other hand, the scientist of data is not only going to do exploratory analysis in order to figure out what insights are there, but they get the benefit of using some of the more advanced algorithms in machine learning in order to figure out how likely an event is going to happen in the future.

The data scientist is going to have a fun job at this. They are going to specifically take the time to look at the data from a lot of different angles, and some of these angles may be brand new, and ones that no one had considered in the past.

So, to keep it simple, data science is going to be used to help us make some predictions and decisions through a lot of different methods. And one of these methods is going to be through machine learning.

The Lifecycle of Data Science

Knowing what this is and how it works is going to make a big difference in the amount of success that you are able to get with this field, and it will help you to get the best results possible out of the process. Some of the steps that come with the data science lifecycle include:

Discovery

The first step that we need to explore is going to be the discovery. Before you begin any kind of project in this field, you will need to know the different properties, the requirements, the specifications, and the required budget. Otherwise, it is hard to know where you need to get started. Once you have a bit of this information in place, you will be able to do an assessment of the people, time, data, support, and technology to figure out if the project is something that you will be able to do. If you are short on any of those aspects, then it may be time to evaluate whether or not you would be able to do without them or get them before you start.

For this stage, you are going to need to take some time to do some research. You need to have a full understanding of the project you would like to do, and you need to know if you have the right resources to get all of it done. And if it is needed and the project is something that is necessary and you want to do it but without the right resources, you need to figure out what you can do to change this around.

Another thing that you are going to need to focus on when you are working in this stage is that you will need to frame the business problem that you want to fix and make better, while also formalizing that initiation hypothesis that you would like to be able to test.

Data Preparation

When you are done with the steps above, it is time to move on to the second stage.

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