Do I need a data science team?

One of the questions often addressed to me is whether an organization needs a data science team or not.

The way in which an organization will interact with data science depends a little bit on what kind of organization it is.

To some extent, it depends a lot on the size of the organization. So, when it is just a start up, when it is an early stage company, or just one person with a very small team, then we may not need to worry so much yet about how to do experimentation, how to do machine learning, how to do sort of prediction and downstream calculations. The first order of business is just making sure we keep our data in order. And the way to do that is to make sure we focus on infrastructure.

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The Data Science Process_Part 2 (Practice)

As already discussed the Stages in the knowledge discovery process are:

  • Opportunity Assessment & Business Understanding
  • Data Understanding & Data Acquisition
  • Data Cleaning and Transformation
  • Model Building
  • Policy Construction
  • Evaluation, Residuals and Metrics
  • Model Deployment, Monitoring, Model Updates

Let’s see these stages in more detail:  Continue reading

The Data Science Process_Part 1 (Theory)

Data Science is not new. In fact, it’s been around for many years.

Over that time, various groups of data professionals have defined and documented methodologies that are useful when we need to conduct a data science project. All these several attempts to make the process of discovering knowledge scientific, resulted to similar steps, therefore it is safe to state that there are some core principles that underlie the data science process.

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What is Data Science?

Data Science is the exploration and quantitative analysis of all available structured and unstructured data to develop understanding, extract knowledge, and formulate actionable results.

The term “data science” has existed for over thirty years and was used initially as a substitute for computer science by Peter Naur in 1960. In 1974, Naur published Concise Survey of Computer Methods, which freely used the term data science in its survey of the contemporary data processing methods that are used in a wide range of applications. In 1996, members of the International Federation of Classification Societies (IFCS) met in Kobe for their biennial conference. Here, for the first time, the term data science is included in the title of the conference (“Data Science, classification, and related methods”).

So what Data Science actually mean?

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