Lesson 4 - Introduction to Explores and Creating a Tile – Support

Welcome to Lesson 4 of your Safety Intelligence Self-Guided Onboarding Program!

If you do not have Safety Intelligence and are interested in adding it, please contact your Customer Success Manager or shared email: csoffice@ecoonline.com

Learning Objective

By the end of this lesson, you will have learned:

What is an Explore?
Data Fields - Dimensions, Measures & Custom Fields
Navigating the 'Explore' interface in-depth
How to create a new tile in your dashboard
Enhancing your Data Pane By Hiding Fields and Utilizing Row Limits

What is an 'Explore'?

As a new user, particularly if you are unfamiliar with business intelligence (BI) tools, it's crucial to start with a foundational understanding of one of the core features of Safety Intelligence (SI) - Explores. This section will provide a concise overview of what an Explore is, before you dive into creating your own tile.

An Explore in SI is your gateway to exploration and analysis of your health and safety program data within eCompliance. It is a feature that allows you to delve into your organization's data in a structured and intuitive way, without needing any technical background in data analysis or database querying.

Each Explore we have created for you in SI, has been curated to allow for deep dive analysis into specific modules and functionality that exists within eCompliance. For example, we have created several 'forms-related' explores that allow for different types of analysis on any forms that have been created in eCompliance. In some of the forms-related explores, you'll be able to do some high level analysis on fields such as 'Type of Incident' or 'Date of Inspection', whereas we have other forms-related explores that will allow you to focus in on more specific data, such as 'Question Name' or 'Answer Date'. For more information on the Explores available in SI.

In the upcoming section, how to use the data fields available in each Explore, how to navigate the Explore interface, and finally you will learn how to begin creating a tile in your own dashboard.

Data Fields - Dimensions, Measures, and Custom Fields

In this section, we will cover the three main types of data fields that you can work with in SI. This is crucial to understand as these are the building blocks of any visualization. The three types are: Dimensions, Measures, and Custom Fields. Each plays a unique role in shaping your data visualizations and insights.

Dimensions

Dimensions are the descriptive aspects of your data. They help you slice and dice your data to see it from different perspectives. Think of dimensions as the 'who', 'what', 'where', and 'when' in your data. Dimensions matter because they allow you to categorize your data into segments for details analysis. They are essential for filtering and grouping your data in visualizations.

For example, take the following pie chart. We can see that it is grouped based on the Dimension Form Type. In this case, the total number of forms have been "sliced" so-to-speak, but the type of form dimension they fall into - you can also think of dimensions as categories.

Now without changing anything about what data is being queried, but simply by selecting a different type of dimension - Form Status - we can see that the number of forms that fall into each dimension (or category) has now changed. However the total number of forms does not. This is the essence of what a Dimension is, in Safety Intelligence.

Measures

Measures are the quantitative elements of your data. These are the number you'll add up, or perhaps average out, to quantify something about your dimensions. Measures are important because they give you the ability to perform calculations on your data. They're what you use to evaluate compliance, track changes over time, and identify trends.

Continuing with the example of the pie charts above, while the categories themselves changed, the measure did not - the measure being Form Count. You can even select multiple measures when aggregating by certain dimensions. In the example below, we can see that the measure of Form Count and Action Item Count have been selected to provide a value of each at every Site Name (which is the Dimension in this case).

Custom Fields

Custom fields are fields you create within an Explore to tailor your data analysis further. While this is a slightly more advanced SI concept, we will go over the three general types of custom fields:

Custom Dimensions - These might combine existing dimensions in new ways, like concatenating two separate dimensions like first and last name fields to create a full name dimension for example.
Custom Measures - These could include existing measures that have been customized with a filter. For example, we could take the Form Count measure and create a custom filtered measure that will only provide us with the count of forms that are of the Inspection type.
Table Calculations - These are calculations that operate on the data present in your visualization, offering immediate, visible insights based on existing fields. For example, we might select two measure fields: Documents Required Count and Documents Acknowledged Count. We could then create a table calculation to get the percentage of documents that have been acknowledged by creating a calculation that divides the Document Acknowledged Count / Documents Required Count.

Custom fields empower you with the flexibility to analyze your data precisely how you need to. They unlock a deeper level of insight by allowing you to manipulate and explore your data beyond the default fields.

Dimensions, measures, and custom fields are the foundation of data analysis in SI. Understanding these elements is key to creating meaningful and insightful visualizations. As you begin to experiment with creating your first visualization, keep these definitions in mind to select the appropriate fields for you analysis needs.

Navigating the Explore Interface

1. Explore Name

This is where you will see the name of the explore you are currently accessing

2. Search Box

The 'Find a Field' search box is a feature that allows you to quickly locate and add specific fields to your analysis, even within explores that are connected to many data fields. Just type a field name, or a keyword for a field name, and it will dynamically filter the fields below to the related fields.

To illustrate - you can see that in the example below, searching on 'Date' will provide all available Date-fields within a given explore, allowing you to easily narrow in on the specific date you are looking for:

3. Field Picker

This can be found on the left side of the Explore interface. This area lists all the available fields - both dimensions and measures - that you can use for your analysis. Simply click on a field to add it to your data set.

Info button - Within the field picker is where your Dimensions and Measures all live. When hovering next to each field, you will see a circle icon with an "i" in the middle - this is the Info button. Clicking this button reveals details about the specific field, including its definition. This information is useful if you are unsure of what data the specific field is referring to.

4. Filters Pane

This section of the Explore interface is also known as the 'Filters Pane'. This is where filters are set up and edited. Both dimensions and measures can be filtered on to help you with narrowing down your result set. There are three types of filters - Basic Filters, Advanced Matches, and Custom Filters.

Basic Filters - These filters are added by clicking on the filter icon next to any field in the Field Picker of the Explore:

- The filter icon can be identified by the upside-down triangle icon next to any given dimension or measure - in blue in the above example image. It will appear only upon hovering your mouse over the right-hand side of the field.
- Once the filter button has been selected, you will see the filter field appear on the right of your Explore in the Filters Pane.

Advanced Matches Filter - advanced matches filters offer a refined level of data filtering that allows for more specific and complex queries. These are particularly useful when the standard filter conditions are not sufficient to meet your analytical needs. To get the advanced filter, click the upside-down triangle next to a dimension or measure (see Basic Filters) to ensure the filter is selected. In the filter drop-down look for the "matches (advanced)" option as in the example below:

- To apply an advanced filter, you will need to input your desired criteria in to the text box that appears when the filter type is selected. For more information on advanced filtering please see the linked documentation from Looker HERE.

Custom Filters - custom filters take advanced filtering to the next level to allow users to build unique filter expressions based on a combination of fields, operations and functions.
- To utilize custom filters, select the Custom Filter checkbox in the upper right-hand corner of the filters pane. Clicking this will open the below custom filter area as it appears below:

While this is a more advanced SI feature, you can find more details regarding assistance regarding syntax HERE.

5. Visualization Pane

This section of the explore is also known as the visualization pane. This part of the explore is where you are able to visualize your data transformed into insights.

Key features of the visualization pane include:

Dynamic Visuals - As you select different data fields in the field picker, this pane dynamically updates to display your data in the chosen visualization format, be it charts, graphs, tables, or any of the other options available.

Customization at your fingertips - With plenty of intuitive tools for customizations, you can easily adjust the visual aspects of your data representation through the "Edit" menu. Depending on which visualization you select, the menu options will change. Options generally will include customization around colours, labels, chart types, scale etc. making your data easy to understand. Here's an example of the Edit menu for the line graph visualization:

Interactive Exploration - Many of the visualizations offer interactive features. Hover over bars and graphs to get values at-a-glance, click visualization values to drill down further, or adjust on the fly to see different dimensions of your data.

Example of an at-a-glance interactive visualization that provides values of each bar by simply hovering over it

6. Data Pane

The final key area of the explore interface is the data pane. This is an essential component for users, as it provides a direct view into the raw values and details that fuel your visualizations. Key features of the data pane include:

Comprehensive data overview - See a detailed row-by-row display of your query results, offering a granular look at the specific data points behind your visualizations.

Real-time data interaction - Interact directly with your data here through sorting, grouping, filtering, and drilling down into deeper levels of detail.
- To interact further with any of the fields in your data pane, click the cog icon next in your desired field name and a menu will appear with more options to view your data in different ways:

- - Remove - This option allows you to remove a field from your visualization directly from the data pane, having the same function as de-selecting a field from your field-picker. This will not remove it entirely from the explore if you have a filter for the field selected as well. You will need to remove both items separately - once from the data pane, and from the filters pane as well.
  - Filter - Selecting the filter option will function the same as clicking the upside-down triangle icon next to any given dimension or measure (see Part 4 - Filters Pane of this section). When selected, it will populate the filters pane with the filter option for the selected field.
  - Pivot - Selecting pivot will pivot any dimension in the data pane. Depending on the type of visualization selected, this will be reflected in the visualization.
- - Group - The group feature allows you to group values from a given dimension into custom groups. Grouping is a tool that allows you to categorize and consolidate your data based on selected fields. Best used to help with simplifying complex datasets into organized, digestible groups. As a new SI user, this is not a function you may look to use right away.
  - Hide this field from visualization - When you select this option fro a specific field, SI will remove the field from your current visualization without deleting the data from your query. This means you can keep important data accessible for analysis while maintaining a clean and clear visual representation.

Foundation for Analysis - Use the data pane as a starting point for in-depth analysis, where you can validate data accuracy, identify outliers, and understand the basis of your visual insights.

7. "Run" button

The "Run" button is your command centre for bringing the data to life. Positioned prominently in the upper-right hand corner of the explore, this button is the final step in the process of data exploration and visualization. After selecting all of your data fields, applying filters, and setting up any specific visualization elements, clicking Run executes your query.

Key features of the "Run" button include:

Instant Insights - with a click, the Run button compiles your data criteria and refreshed the visualization pane with updated insights.
Dynamic Exploration - each time you adjust your exploration criteria - whether it's adding or taking away fields, filters or changing the visualization - utilizing Run will refresh the explore to provide you with the updated view of your changes to any of your data analysis parameters.

In addition to what the Run button does, it is important to also keep in mind some best practices:

Pre-Run Checks - Before clicking "Run", ensure you've selected the appropriate fields and filters for your analysis goals.
Iterative Exploration - Don't hesitate to use the Run button multiple times as you refine your analysis, exploring different facets of your safety data.

Creating a New Tile

Creating a tile visualization in SI is critical to customizing your dashboards and extracting specific insights from your data. This section will guide you through the process of creating a visualization from scratch, directly within a dashboard.

Step 1: Enter 'Edit' Mode on Your Dashboard

Before creating a new tile, ensure your dashboard is in 'Edit' mode. This allows you to modify and add new components to your dashboard.

Locate and click the 'Edit' button located in the top right-hand corner of your dashboard.

When you have correctly entered 'Edit' mode, you will see a large blue bar appear at the top of your dashboard:

Step 2: Create a New Tile

To add a new visualization tile to your dashboard, click the 'Add' button in the top left-hand corner of the blue bar. A drop-down menu will appear with several options. In this case, you will want to click the 'Visualization' option:

Step 3: Select your Explore

After clicking the 'Visualization' option, you will be prompted to 'Choose an Explore' - also known as your data source. This is where you will choose the type of data that you want to conduct your analysis on.

Select the Explore that contains the data fields relevant to your visualization and analysis needs:

Explore's are subject to change, we are always working to improve and optimize your safety data and how you are able to access it.

Step 4: Choosing Dimensions and Measures

Once in the selected Explore, you will have options to add dimensions (categorical data) and measures (quantitative data) to your tile. Select the field that you want to include by clicking on your desired fields in the Field Picker. This action will automatically add the fields to your visualization unless you choose to hide them in the data pane menu.

Enhancing Your Data Pane

Hide Field from Visualization

Within the data pane, you have the flexibility to refine what appears in your visualization. The 'Hide Field From Visualization' option allows you to remove specific fields from the visual output without deleting them from your query. This is especially useful for maintaining a clean and focused visualization.

To use this feature, simply click on the menu next to a field in the Data Pane and select 'Hide Field From Visualization'. The field will remain part of your data model, but won't clutter your visual representation. When fields are hidden, you will see an icon at the top of the field of en eye with a diagonal line.

In the example below, we are hiding the measure field for Form Count - you can see the feature apply immediately to the visualization upon selecting it:

Row Limit

The 'Row Limit' function lets you control the amount of data displayed in your visualization. It's a valuable tool for focusing on the most relevant data points and ensuring your visualizations are digestible and performant.

One common use case for the row limit feature is to obtain a dynamic 'Top 5' based on a measure. For example, to observe employee adoption of eCompliance, you might choose to create a visualization that provides you with the 'Top 5' employees who have submitted the most number of forms. To do this, you may select the Employee Name dimension and the Form Count measure. Sort your measure by clicking on the title area of the measure to 'Descending' sort order, enter '5' into the Row Limit section and Run your tile.

You will see that by toggling a few simple areas of your data pane, you can generate meaningful insight into the behaviour of your employees. The accompanying visualization may look something like this:

This concludes Lesson 4, next we will show you how to interact with your dashboards further and how they can be used as a foundation for further data exploration.

Top 3 key takeaways from this lesson are:

Grasping what an Explore is and how it functions as the starting point for data analysis within Safety Intelligence is crucial for leveraging the full capabilities of the platform.
Understanding the distinction between dimensions, measures, and custom fields is essential, as these are the components that shape the structure and outcome of your data visualizations.
Learning the navigate the Explore interface and effectively create a new tile in your dashboard provides the hands-on experience necessary for personalized data reporting.

Homework - To solidify your grasp of these concepts, complete the following:

Explore Navigation - Choose any 'forms-related' Explore and use the 'Find a Field' search box to add a dimension and a measure to the Explore. Utilize the 'Info' button to learn more about the fields you've selected.
Visualization Creation - In 'Edit' mode of a blank dashboard, create a new tile by selecting an Explore and adding relevant dimensions and measures. Experiment with sorting and applying the Row Limit to display a "Top 5" list for a measure like Form Count.
Data Pane Adjustment - Within your new tile, practice using the 'Hide Field From Visualization' feature to refine the visual output. Try different configurations to see how it impact the clarity of your visualization.

Continue to the next lesson by clicking here: Lesson 5 - Setting Up & Interacting with Dashboards/Looks