File organisation guidelines Every data analyst’s goal is to conduct efficient data analysis. One way to increase the efficiency of your analyses is to streamline processes that help save time and energy in the long run. Meaningful, logical, and consistent file names help data analysts organise their data and automate their analysis process. When you use consistent guidelines to describe…
Maximise databases in data analytics Databases enable analysts to manipulate, store, and process data. This helps them search through data a lot more efficiently to get the best insights. Relational databases A relational database is a database that contains a series of tables that can be connected to form relationships. Basically, they allow data analysts to organise and link data…
Data Responsibility Rundown Key Learnings: Specific Topics Covered: Data anonymization What is data anonymization? We have been learning about the importance of privacy in data analytics. Now, it is time to talk about data anonymization and what types of data should be anonymized. Personally identifiable information, or PII, is information that can be used by itself or with other data to…
Select the right data Following are some data-collection considerations to keep in mind for your analysis: How the data will be collected Decide if you will collect the data using your own resources or receive (and possibly purchase it) from another party. Data that you collect yourself is called first-party data. Data sources If you don’t collect the data using…
A massive amount of data is generated every single day. In this part of the course, you will discover how this data is generated and how analysts decide which data to use for analysis. You’ll also learn about structured and unstructured data, data types, and data formats as you start thinking about how to prepare your data for analysis. Learning…
Content collected from Google Data Analytics course Feel free to download a .pdf version of this reading below: These best practices include guidelines for entering SQL queries, developing documentation, and examples that demonstrate these practices. This is a great resource to have handy when you are using SQL yourself; you can just go straight to the relevant section to review…
Working with stakeholders Your data analysis project should answer the business task and create opportunities for data-driven decision-making. That’s why it is so important to focus on project stakeholders. As a data analyst, it is your responsibility to understand and manage your stakeholders’ expectations while keeping the project goals front and centre. You might remember that stakeholders are people who…
Spreadsheets are a key data analytics tool. Here, we will learn both why and how data analysts use spreadsheets in their work. We will also investigate how structured thinking helps analysts understand problems and come up with solutions. Learning Objectives Spreadsheets and the data life cycle To better understand the benefits of using spreadsheets in data analytics, let’s explore how…
In analytics, data drives decision-making, and this is your opportunity to explore data of all kinds and its impact on all sorts of business decisions. We will also learn how to effectively share your data through reports and dashboards. Learning Objectives Data trials and triumphs Introduction A data analytics professional’s job is to provide the data necessary to inform key…
Why You Should Take This Course This course is the second in the Google Data Analytics Certificate program. It builds on the foundation you learned in the first course and dives deeper into the world of data analysis. Here are some reasons why you should take this course: In addition to the above, this course will also help you to:…