Data Profiling?-?Aamir?P
Hello everyone! Today, we’ll see about Data Profiling.
Data profiling is the process of examining and analyzing the data. This is an essential step in data management, data integration, data warehousing, etc. This concept is so important because you understand the characteristics, quality and structure of data.
Discovering the structure of the data includes types of data, number of columns and relationships between datasets or tables. We can also assess the quality of data by detecting missing values, duplicates, etc. By detecting this, we can examine the completeness, accuracy, integrity, etc. of data. So, we can flag the inconsistencies in data and also detect its patterns.
With data profiling, you can understand the dependencies or relationships of data. This is a crucial part because it supports data modelling and database design.
Profiling supports the transformation and cleaning of data. With profiling, it's easy to document the data by providing insights. This is valuable in data governance and data lineage tracking.
The Data Profiling tools are:-
Statistical Analysis:
This is where mean, median, histograms and many more come in to understand the data.
Data Sampling:
Here, we analyse the subset of the data.
Data Exploration:
Explore the data manually to gain insights.
Data Relationships:
Discover the relationships based on primary and foreign keys.
Data Visualization:
Create charts or graphs to represent the data visually.
Data Quality Rules:
Apply rules to identify issues.
Data profiling is an iterative process and is not limited to a one-time analysis. It is valuable for decision-making.
So, that’s it for the day! Thanks for your time in reading my article. Tell me your feedback or views in the comments section.
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