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Concepts

Data Analysis

Data analysis refers to the process of examining, transforming and arranging a given data set in specific ways in order to study its individual parts and extract useful information. [data-analytics] is an overarching science or discipline that encompasses the complete management of data.

Stages of data analysis

1. Understand the data model

  • It is the duty of the data analyst to understand the way how the data is stored and also of what it consists
  • Data usually is segregated in multiple tables, so a deep level of understanding of how they connect one to another is necessary

2. Manipulate the data

  • Data manipulation can be done either with SQL or using other programming languages such as Java, Python, etc.
  • It can involve both aggregating / joining existing models but also creating new ones to facilitate easier interrogation
  • Some type of [etl] process may be involved if data is distributed on multiple [database]. The data analyst might not be involved in the actual implementation of the process, but would work with the framework to ensure that the data is available for interrogation
  • It may also involve some [data-cleansing] to make sure the data are complete and accurate.

3. Presenting insights from the data

  • Data analyses have as output key insights from the data that can be easily consumed and are self-explanatory
  • The key insights can be displayed in reporting and dashboard with [data-visualization] tools.
  • The insights from the data can be served to other systems that will use the output of the analysis for further integration/investigation such as ML models, advanced reporting systems, E-mail send-outs etc.