Data Visualization and ETL Steps For Visualizing the Datawebogen
Data visualization is the presentation of data in graphical format which can be used for decision making, Data analysis and communication. It is one of the steps in data analysis or data science with a goal to communicate information clearly and efficiently to users. Data Visualization is the necessary ingredient in bringing the power of Big Data to the Mainstream.
People can easily consume the data if it is properly visualized. We can’t say the best sales in a year by seeing its record. But we can easily find the best sales in a year by seeing visualizations.
Data visualization is a series of processes which starts with acquiring the data and defining how user can interact with data effectively. The steps that are involved are:
- Acquire – obtaining data from a file or any source over network
- Parse – transform the data into required data format
- Filter – remove data unnecessary for visualization
- Mine – apply methods from data mining as a way to place the data in mathematical context
- Represent – selecting a basic model to represent the data (line, bar, scatter etc.)
- Refine- visualize the basic model in a clean way
- Interact- define the methods through which user can consume the data effectively
We can define all the above steps in simple as ETL concept which stands for Extract, Transform and Load. These three separate functions combined into a single programming tool for changing data into actionable insights.
- Extract: Retrieving the structure or unstructured data from data sources.
- Transformation: Transformation is the process of converting the extracted data into understandable format using rules or lookup table or combining the data with other data.
- Loading: Loading is used to writing data into target database.