Google Data Studio is a free tool from Google that allows anyone to create beautiful dashboards using their data. The tool has become very popular since its launch in 2016.
Data visualization tools allow us to explore our data in new ways. They provide insights into trends, patterns, and relationships. These visualizations can also be easily shared through social media platforms like Facebook or Twitter.
Google Data Studio is a powerful tool that makes sharing insights across teams and organizations easier. In addition, it provides a way to visualize data without having to write code.
A data model describes the structure of your data and how it relates to one another. You use a data model to describe the entities, attributes, relationships, hierarchies, and constraints that make up your data.
Metrics and Dimensions
Metrics are measurements used to analyze your data. For example, revenue, number of transactions, and average transaction size are metrics. These benchmark provide insight into the performance of your application. They tell us things like “how much money did we make?” and “how many customers do we have?”.
Dimensions are properties of your data.It may be customer name, address, city, state, zip code, and phone number are all dimensions.
You can think of a relationship as a connection between two objects. For example, a customer can purchase products from our store. In this case, the customer object relates to the product object because the customer bought something. This type of relationship is called a one-to-one relationship. You can also have a relationship with no direct link between the objects. For example, you could sell a house to someone. In this case, neither the buyer nor seller owns the property directly; instead, both parties acknowledge the place indirectly via a third party. This type of relationship, called a one-to-zero-or-more relationship, is common in real estate.
Data sources and connectors
Connectors allow you to connect data from one system to another. They can help you build dashboards, reports, and visualizations. You can use them to pull information directly from databases, spreadsheets, and files. Connectors can also be used to import data from external APIs—that’s where the name comes from.
Many free connectors are available, including those from Microsoft, Salesforce, Tableau, and others. Some connectors are explicitly built for specific tools like Excel, Power BI, and Qlikview. Others are designed to work across multiple applications.
Data Studio partners offer custom connectors that integrate with their products. For example, Salesforce provides connectors for SalesforceIQ, Salesforce Marketing Cloud, Salesforce Service Cloud, and Salesforce Analytics Cloud. These connectors provide access to data from these apps within Data Studio.
How the data sources fetch your data
Data sources are the lifeblood of data analysis. They provide the information needed to build reports, dashboards, and visualizations. Data sources are where we pull our data from, whether it’s a spreadsheet, database, API, or some other type of resource.
Most of the data sources maintain a live connection to their data, meaning they update it every few seconds. This allows us to quickly see what’s happening in real-time. However, there are times when we want to see historical data, like how many people viewed a particular blog post over the course of several days. In those cases, we need to cache the data in memory.
To do this, ensure that the data isn’t being updated while pulling it. If we don’t, we risk getting stale data. Fortunately, most data sources offer methods to check if the data is up to date, such as checking the HTTP status code.
If the data is outdated, we can either wait for the data source to refresh itself or manually force it to refresh. We can also choose to use a file upload data provider, which downloads the entire dataset into memory.
How to connect to MySQL
A Data Studio data source connects to a database. This article will elaborate how to set up a connection to a MySQL server.
JDBC 4.0 supports the following versions of Microsoft SQL Server:
– MS SQL 2000 SP3
– MS SQL 2005 SP1
– MS SQL 2008 SP1
– MS SQL 2008 R2 SP1
– MS SQL 2012 SP1
– MS SQL 2008 R2 SP2
Configure the data source
The Data Source panel allows you to configure how data sources are aggregated into reports. You can choose to aggregate data by day, week, month, quarter, or fiscal year. If you want to see data across multiple periods, such as daily, weekly, monthly, quarterly, or yearly, select “Multiple Periods.” This option lets you view data over a while, such as one month, six months, or 12 months.
You can also change the aggregation type from Sum to Average, Count, Minimum, Maximum, or Median. To do this, select the dropdown menu next to the aggregation type field and choose the desired value.
For aggregating data by day or week, select the checkbox next to each date range. For example, if you see sales by day, select Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday, and press Apply.
To add another date range, repeat the process.
Control who sees the data
Data credentials are used to restrict access to sensitive information. For example, you might use data credentials to limit access to a database containing customer records. You could set up multiple types of credentials, each one granting different access levels.
Viewer’s credentials require every viewer to enter their credentials when viewing the data. This credential lets people view the data without entering any additional information. If the owner wants to give everyone access to the data, they set up the data credentials to grant “owner” privileges.
The owner’s credentials allow anyone to view the data without requiring them to enter any additional credentials. The data owner can decide how much access to give out based on their needs.
Companies must ensure that the information they collect is accurate, complete, and up-to-date. If there is no longer a requirement to keep specific data, such as credit card numbers, companies must delete it within 30 days.
Hugo is another Data Studio fan that specializes in reports and dashboards. He runs is own business from home and uses Google Data Studio in his reporting for his clients