Data Visualization
The fifth step is visualizing the data. Nothing is more compelling than a visualization. The data now transformed has to be made into a visual (chart, graph). The reason for making data visualizations is that there might be people, mostly stakeholders that are non-technical. Visualizations are made for a simple understanding of complex data. Tableau and Looker are the two popular tools used for compelling data visualizations. Tableau is a simple drag and drop tool that helps in creating compelling visualizations. Looker is a data viz tool that directly connects to the database and creates visualizations. Tableau and Looker are both equally used by data analysts for creating a visualization. R and Python have some packages that provide beautiful data visualizations. R has a package named ggplot which has a variety of data visualizations. A presentation is given based on the data findings. Sharing the insights with the team members and stakeholders will help in making better decisions. It helps in making more informed decisions and it leads to better outcomes.
Six Steps of Data Analysis Process
Data analysis is the methodical exploration and interpretation of data, underpins decision-making in today’s dynamic landscape. As the demand for skilled Data Analysts grows, understanding the six key steps in this process becomes imperative. From defining problems to presenting insights, each step plays a vital role in transforming raw data into actionable knowledge.
In this article let’s delve into the six essential steps of data analysis, emphasizing the significance of each phase in extracting meaningful conclusions.