Google Data Analytics Professional Certificate - Course 1 : Foundations: Data, Data, Everywhere - week 3

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Week 3 - Follow the data life cycle

The life cycle of data is plan, capture, manage, analyze, archive and destroy.

Planning

During planning, a business decides what kind of data it needs, how it will be managed throughout its life cycle, who will be responsible for it, and the optimal outcomes.

Capture

This is where data is collected from a variety of different sources and brought into the organization. With so much data being created everyday, the ways to collect it are truly endless.
when you maintain a database of customer information, ensuring data integrity, credibility, and privacy are all important concerns.

Manage

How we care for our data, how and where itโ€™s stored, the tools used to keep it safe and secure, and the actions taken to make sure that itโ€™s maintained properly.

Analyze

In this phase, the data is used to solve problems, make great decisions, and support business goals.

Archive

Archiving means storing data in a place where itโ€™s still available, but may not be used again.

Destroy

To destroy it, the company would use a secure data erasure software. If there were any paper files, they would be shredded too. This is important for protecting a companyโ€™s private information, as well as private data about its customers.

Recap

  1. Plan: Decide what kind of data is needed, how it will be managed, and who will be responsible for it.
  2. Capture: Collect or bring in data from a variety of different sources.
  3. Manage: Care for and maintain the data. This includes determining how and where it is stored and the tools used to do so.
  4. Analyze: Use the data to solve problems, make decisions, and support business goals.
  5. Archive: Keep relevant data stored for long-term and future reference.
  6. Destroy: Remove data from storage and delete any shared copies of the data.

Caution: data analysis life cycle (Ask, Prepare, Process, Analyze, Share, and Act)

Week 3 - Outlinning the data analysis process

ask, prepare, process, analyze, share, and act.

Ask

We define the problem to be solved and we make sure that we fully understand stakeholder expectations.
Stakeholders hold a stake in the project. They are people who have invested time and resources into a project and are interested in the outcome.

  1. First, defining a problem means you look at the current state and identify how itโ€™s different from the ideal state. Usually thereโ€™s an obstacle we need to get rid of or something wrong that needs to be fixed.

  2. Another important part of the ask phase is understanding stakeholder expectations. The first step here is to determine who the stakeholders are. That may include your manager, an executive sponsor, or your sales partners. There can be lots of stakeholders. But what they all have in common is that they help make decisions, influence actions and strategies, and have specific goals they want to meet. They also care about the project and thatโ€™s why itโ€™s so important to understand their expectations.

Communicating with your stakeholders is key in making sure you stay engaged and on track throughout the project. So as a data analyst, developing strong communication strategies is very important.

This part of the ask phase helps you keep focused on the problem itself, not just its symptoms. As you learned earlier, the five whys are extremely helpful here.

Prepare

This is where data analysts collect and store data theyโ€™ll use for the upcoming analysis process. Youโ€™ll learn more about the different types of data and how to identify which kinds of data are most useful for solving a particular problem.

Itโ€™s so important that your data and results are objective and unbiased. In other words, any decisions made from your analysis should always be based on facts and be fair and impartial.

Process

Here, data analysts find and eliminate any errors and inaccuracies that can get in the way of results. This usually means cleaning data, transforming it into a more useful format, combining two or more datasets to make information more complete and removing outliers, which are any data points that could skew the information.

Analyze

Analyzing the data youโ€™ve collected involves using tools to transform and organize that information so that you can draw useful conclusions, make predictions, and drive informed decision-making.

Share

In the share phase, visualization is a data analystโ€™s best friend. So this course will highlight why visualization is essential to getting others to understand what your data is telling you. With the right visuals, facts and figures become so much easier to see and complex concepts become easier to understand.

Act

This is the exciting moment when the business takes all of the insights you, the data analyst, have provided and puts them to work in order to solve the original business problem and will be acting on what youโ€™ve learned throughout this program.

data-analysis-process-6-phase

Week 3 - Data analysis toolbox

Appendix

Glossary: Terms and definitions

Reference

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