I have just decided that I am going to embark on a journey to take the Google Data Analyst Certificate which is a program hosted on Coursera. The reason I made this decision was because I want to work in the field of machine learning and AI and the first step to doing that sort of thing well is being able to work (at an advanced level) with data. Having just completed my BSc (Hons) in Artificial Intelligence I am already quite good at data analysis, but I feel the course provided by Google will consolidate my knowledge and fill any gaps that there may be in my skill set.

Google says that there are 6 steps to data analysis:

1. Ask
2. Prepare
3. Process
4. Analyse
5. Share
6. Act

In the course, Google uses a real-world example to explain these principles. The scenario is that an organisation was experiencing a high turnover rate among new hires for the company. Lot’s of employees were leaving the company within their first year of employment. The analysts working on finding out why this was were trying to answer the following question “How can the organisation improve the retention rate for new employees”.

Ask

The first thing that needs to happen is the analysts need to define what the project would look like and what a successful result would be. This is done by asking effective questions about the problem to the leaders and managers who are interested in the outcome of the project. Here are some of the questions that were asked.

• 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?

Prepare

The group working on this project set a timeline of three months and decided how they wanted to relay their progress to the interested parties. Another thing they did was identify what data they needed for the project. It was decided that they should send a questionnaire out to new employees.

• They developed a highly specific questionnaire that would ask new employees about employee satisfaction surrounding hiring, onboarding and overall compensation for working in that role.
• They established rules as to who (in the organisation) would have access to the collected data. Anyone in the group could have access to the raw data and anyone not in the group would have access to the reports (summarised or aggregated data).
• They finalised what specific information would need to be captured and how best to present that data visually. They brainstormed possible and data related issues and how to avoid them.

Process

The next step (once the survey had been created) was to send it out to new employees. An important point to note at this point was that the analysts needed to get permission from the employees to carry out the survey. The analyst also let the employees know how their data would be collected, stored, managed and protected. Collecting and using data ethically is one of the responsibilities of the data analyst.

These were the steps that they took at this point:

• 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 summarised without revealing individual responses.
• They uploaded the raw data to an internal data warehouse for an additional layer of security.

Analyse

The next step was to evaluate the responses from the employees. The data analysts discovered that an employee’s experience with a certain process was a key indicator of overall job satisfaction. This is what was found:

• Employees who experienced a long and complicated hiring process were most likely to leave the company.
• Conversely, employees who experienced efficient and transparent evaluation feedback process were more likely to stay.

The analysts knew to document exactly what they had found as it was important not to diminish trust in the survey process. This is important to ensure the data coming in is truthful and honest.

Share

This is how the analysts shared their findings:

• They presented their findings to the managers
• They asked the managers to share the results with their teams

This allowed the managers to communicate the results in the right context. As a result, they could have productive team conversations about the steps that would be needed to improve employee engagement.

Act

The last step of the process is to work with leaders in the company to decide on how best to implement the changes and take action on the findings. These were the recommendations:

• Standardise the hiring and evaluation process.
• Conduct the same survey annually and compare the results with those from the previous year.

A year later the same survey was sent out and as a result of the work done by the data analysts, the retention rate dramatically improved.