- #DATA PROCESSING HOW TO#
- #DATA PROCESSING SOFTWARE#
The keyword here is “logical”, because it should happen before implementation decisions.
This is similar to the so-called Data Modeling that is applied to database and sometimes referred as “database logical design”.
The relationship of the datasets with other existing datasets in the organization. The expected data pattern of each field, including whether it can have missing values and a distinct list of values. The fields that determine the uniqueness of each record. The data type of each field, such as text, integer, float, list, etc,. The data fields in each of the datasets. The input data sets and reference data required. Whenever designing a data process, the first thing that should be done is to clearly define the input dataset(s), as well as the output dataset, including: Ensure data quality from the beginning.ĭesign Principle 1: Always Start with Design of Datasets and Data EntitiesĮvery data process has 3 minimal components: Input Data, Output Data and data transformations in between. Make the system more open and easy to operate. Make the data process easier to maintain (no matter which programming language or data preparation tool is used). In both areas, there are reusable solutions and best practices that have been proven to: My next article will be on common design principles for optimized performance. As inspired by Robert Martin’s book “Clean Architecture”, this article focuses on 4 top design principles for data processing and data engineering. However, in order to differentiate them from OOP, I would call them Design Principles for data science, which essentially means the same as Design Patterns for OOP, but at a somewhat higher level. Design patterns are formalized best practices that the programmer can use to solve common problems when designing an application or system.”įor data science, many people may have asked the same question: does data science programming have design patterns? I would say yes. #DATA PROCESSING HOW TO#
It is a description or template for how to solve a problem that can be used in many different situations. It is not a finished design that can be transformed directly into source or machine code.
#DATA PROCESSING SOFTWARE#
“A software design pattern is a general, reusable solution to a commonly occurring problem within a given context in software design. Below is the definition of Design Pattern from Wikipedia: The practice of Design Patterns is most popular in Object-Oriented Programming (OOP), which has been effectively explained and summarized in the classic book “Design Patterns: Elements of Reusable Object-Oriented Software” by Erich Gamma and Richard Helm.
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