Introduction
Detectives and data analysts have a lot in common. Both depend on facts and clues to make decisions. Both collect and look at the evidence. Both talk to people who know part of the story. And both might even follow some footprints to see where they lead. Whether you’re a detective or a data analyst, your job is all about following steps to collect and understand facts.
Analysts use data-driven decision-making and follow a step-by-step process. You have learned that there are six steps to this process:
Ask questions and define the problem.
Prepare data by collecting and storing the information.
Process data by cleaning and checking the information.
Analyze data to find patterns, relationships, and trends.
Share data with your audience.
Act on the data and use the analysis results.
Data + business knowledge = mystery solved
1) ASK
First up, the analysts needed to define what the project would look like and what would qualify as a successful result. So, to determine these things, you have to ask effective questions and collaborate with leaders and managers who are interested in the outcome of their people analysis.
These are the questions(examples) you may ask:
What do you think new employees need to learn to be successful in their first year on the job?
Have you gathered data from new employees before? If so, may we have access to the historical data?
Do you believe managers with higher retention rates offer new employees something extra or unique?
What do you suspect is a leading cause of dissatisfaction among new employees?
By what percentage would you like employee retention to increase in the next fiscal year?
Key Task You have to do in this Stage:
Identify The Business Talk.
What is the problem you are trying to solve?
Determine key stakeholders
What metrics will you use to measure your data to achieve your objective?
How can your insights help your client make decisions?
2) Prepare
Find or Obtain data appropriate for your analysis from any credible dataset or within that respected company.
In this case, the analysts chose to gather the data from an online survey of new employees.
These were the things they did to prepare:
They developed specific questions to ask about employee satisfaction with different business processes, such as hiring and onboarding, and their overall compensation.
They established rules for who would have access to the data collected — in this case, anyone outside the group wouldn’t have access to the raw data but could view summarized or aggregated data. For example, an individual’s compensation wouldn’t be available, but salary ranges for groups of individuals would be viewable.
They finalized what specific information would be gathered, and how best to present the data visually. The analysts brainstormed possible project- and data-related issues and how to avoid them.
Key Task You have to do in this Stage:
Download data and store it appropriately
Identify how it’s organized
Store and filter the data.
Determine the credibility of the data.
3) Process
Collecting and using data ethically is one of the responsibilities of data analysts. In order to maintain confidentiality and protect and store the data effectively.
these were the steps they took:
They restricted access to the data to a limited number of analysts.
They cleaned the data to make sure it was complete, correct, and relevant. Certain data was aggregated and summarized without revealing individual responses.
They uploaded raw data to an internal data warehouse for an additional layer of security.
Key Task You have to do in this Stage:
Check the data for errors.
What tools are you choosing and why?
Transform the data so you can work with it effectively.
How can you verify that your data is clean and ready to analyze?
Document the cleaning process.
4) Analyze
Then, the analysts did what they do best: analyze! From the completed surveys, the data analysts discovered that an employee’s experience with certain processes was a key indicator of overall job satisfaction.
These were their findings:
Employees who experienced a long and complicated hiring process were most likely to leave the company.
Employees who experienced an efficient and transparent evaluation and feedback process were most likely to remain with the company.
Key Task You have to do in this Stage:
Aggregate your data so it’s useful and accessible.
Organize and format your data.
Perform calculations.
Document your calculations to keep up with your analysis steps.
Identify trends and relationships.
5) Share
Data visualization is the graphical representation of data. But why should data analysts care about data visualization? Well, your audience won’t always have the ability to interpret or understand the complex information that you relay to them so your job is to inform them of your analysis in a way that is meaningful, engaging, and easy to understand. Part of why data visualization is so effective is because people’s eyes are drawn to colors, shapes, and patterns, which makes those visual elements perfect for telling a story that goes beyond just numbers.
This is how they shared their findings:
They shared the report with managers who met or exceeded the minimum number of direct reports with submitted responses to the survey.
They presented the results to the managers to make sure they had the full picture.
They asked the managers to personally deliver the results to their teams.
Key Task You have to do in this Stage:
Were you able to answer the business questions?
What story does your data tell?
Determine the best way to share your findings.
Create effective data visualizations.
6) Act
The last stage of the process for the team of analysts was to work with leaders within their company and decide how best to implement changes and take action based on the findings.
These were their recommendations:
Standardize the hiring and evaluation process for employees based on the most efficient and transparent practices.
Conduct the same survey annually and compare results with the previous year's results.
Key Task You have to do in this Stage:
- What is your final conclusion based on your analysis?
One of the many things that makes data analytics so exciting is that the problems are always different, the solutions need creativity, and the impact on others can be great — even life-changing or life-saving. As a data analyst, you can be part of these efforts.
Outgo and Resources for further Experiment.
If you Liked This Article and you have some *doubt* If you want a Brief Explanation then Consider Checking the Google Data Analytics Course on Coursera. I have used many reading Materials from this course to make this article so I thank Google for letting me use their resources for my research.
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