This article deals with data analysis and provides a basic example of creating a dashboard using Looker or Data Studio. We start by defining data, which is simply a collection of facts. For instance, the annual sales of a shopping company can be considered data. Facts can also be regarded as measurements, and they can be qualitative or quantitative. Data analysis involves the collection, transformation, and organization of data to draw conclusions, make predictions, and drive decision-making. Therefore, a data analyst is someone who collects, transforms, and organizes data to facilitate informed decision-making. For those unfamiliar with the term, decision-making refers to using facts to guide business strategy.
The data analysis process comprises six phases:
- Ask: The analyst must ask the right and effective questions, define the problem, use structured thinking, and communicate with others.
- Prepare: In this phase, the analyst understands how the data is generated and collected. Data is cleaned by removing duplicates, replacing null values, and ensuring the data is unbiased and credible.
- Process: The analyst creates and transforms data, maintains data integrity, tests data, and cleans data.
- Analyze: Analysts use tools to format and transform data. They identify patterns, draw conclusions, and make predictions and recommendations.
- Share: Analysts create effective visuals to bring data to life. They communicate with team members and stakeholders, ensuring everyone understands the findings.
- Act: Insights are applied, decisions are made, and problems are solved.
Curiosity: a desire to know more about something, and ask the right questions
Understanding context: understanding where information fits into the “big picture”
Having a technical mindset: breaking big things into smaller steps
Data design: thinking about how to organize data and information
Data strategy: thinking about the people, processes, and tools used in data analysis
We present here a basic example of a dashboard in which, we use data from Kaggle related to movies and series, and we extract insights. We will not be going through the 6 phases of a data analysis process, but we will be presenting a method for sharing findings. Please comment on this post to let us know what important parameter has been overlooked in the shared figures.
First, we remove duplicates and select the Director and Languages columns with non-null values. The code for this is provided below. The table containing this information is named "Netflix" in my SQL workspace on BigQuery.
The graphs below are obtained from Google Data Studio 👍👍👍👍
Based on the data, it seems that the majority of movies on Netflix are in English. Comedy is the most popular genre, and Steven Spielberg is the director with the highest number of movies available on Netflix.
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