PRODUCT FEATURE GUIDE
Data analysis

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Product feature guide

Flexible
data grids

Overview Specification FAQs

A high-performance data grid built to rapidly and efficiently manage and process large intensive data sets. The data grid has the ability to render thousands of rows and columns without performance degradation making it easy for users to work with complex datasets.

Its flexibility, offers extensive sophisticated customisation options for users to interact and fine-tune both appearance and functionality, with rich set of features like querying, sorting, filtering, and grouping of complex data, which is critical for decision-making in fast-paced environments.

Key benefits

  • Efficient handling of large data sets ensures that platform load quickly, even when displaying thousands of rows or column, providing a smoother, more responsive experience – this is critical for decision-making in fast-paced environments.
  • Interact with the data grid’s built-in features such as sorting, filtering, and grouping, allowing users to easily navigate, analyse, and access the data presented, enhancing usability and accessibility.
  • The customisation and configuration options available, allow users to personalise their data view according to their preferences or needs.
  • Preview the event or activity rapidly without the need of clicking through to the full details, saving valuable time to review and complete key actions reducing response times.
  • Save, share and use queries and filters for future access including data visualisation – maps, charts, counts and lists.
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DATA GRID
Specification

Performance
Ensures rapid data handling, enabling seamless interaction with large datasets for optimal efficiency in a fast paced environment.

Interaction
Facilitates enhanced user engagement with intuitive sorting, filtering, and data manipulation features for a superior user experience.

Customise
Extensive customisation options, allowing users to tailor grid functionalities and aesthetics to full-fill precise requirements.

Saves Time
Accelerates data understanding, analysis and decision-making for users with quick access to pertinent information.

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Data grid - Setup and selection of data sources

Selecting the Data Source - Incidents & critical events, compliance activities, notifications, tasks, people, response forms.

Setting Up Filtering - specify a specific filter from the data source or apply additional filters if required.

Configuring Key Features - Options include column ordering, selection, filtering, pin columns, map view, export and action links.

Choosing Columns of Data - select which columns from the data source should be displayed in the grid.

Preview and Implementation - preview the grid with some actual data and save

Data grid - available views

List view - versatile, interactive and powerful listing tool for handling complex data efficiently.

Map view - flip from list to map to visualise the data on a map with volume-based clusters/PINs

Calendar view - interactive calendar to view data (Command & Verify - display scheduled patrols, Reporter - all events)

List View: Rows - features & customisation

Row Data - Core dataset entries displayed within the grid rows.

Row Sorting - Organise rows in ascending or descending order quickly.

Row Spanning - Extend cells vertically across multiple rows for clarity.

Row Pagination - Divide rows into manageable pages for easier navigation.

Row Inline Editing - Modify the 'Status' field directly within the grid interface for rapid updating.

Row Cell Styling - Customise cell appearance based on data or state.

Row Selection Preview Panel - Display selected row details in a dedicated slide-out panel showing high level details.

Row Filtering - Refine data display by applying various criteria filters - all fields in the grid - text, number, selection, date

Row Multi-filters - Apply multiple filters simultaneously for refined data analysis.

Row Parent-filters - Parent filtering of linked modules - category, type, severity, status, priority, site, region

Row Actions - Perform specific (configurable( operations directly on selected grid rows - view, edit, add note.

Row Export - Extract the entire or filtered down grid data to CSV file format easily.

List View: Columns - features & customisation

Column Headers - Define and customise labels for grid data columns.

Column Sizing - Adjust column widths manually or automatically for fit.

Column Moving - Rearrange columns through drag-and-drop for easy customisation.

Column Pinning - Secure columns in place while scrolling through data.

Column Filtering - Refine data visibility by applying column-specific filters - text, number, selection, date selector.

Columns Tool Panel - Interactive sidebar for managing and configuring grid columns - adding, turning on/off, ordering

Data Module - specific tools

Grouping - Cluster rows by values for organised data display (available on the 'Data' module only).

Filtering Groups - Apply filters to grouped data for targeted insights.

Tree Data - Visualise hierarchical data in an expandable tree format.

Pivot - Organise data into groups, summarise with pivot tables.

Aggregation - Summarise data values using mathematical or statistical operations.

Mobile - The data grid has a reduced filtering capability on mobile

Data Filter - Filtering of incidents, critical events & compliance activities by category, type, severity, status, priority, site, region.

Events - Sort by newest, oldest, severity high to low, priority high to low, bookmarked).

Tasks - Sort by due date, newest, oldest, assigned to me, reported by me).

Notifications - Sort by newest, oldest, unread, bookmarked).

DATA GRIDS
Frequently Asked Questions

A customisable data grid 'wizard' builder is a powerful tool designed to help users create and configure data grids dynamically. It guides users through a step-by-step process to select and customise various aspects of their grid, including the data source, key features, columns of data, and filtering tools. The wizard streamlines the process of setting up a complex data grid but also empowers users with little to no technical expertise to create highly functional and customised data presentations. This approach enhances user experience and productivity, allowing for rapid deployment and iterative development.

Here’s how such a builder typically works:

Step 1: Selecting the Data Source

  • User Interface: The wizard starts with the user selecting a data source, which could be events (critical events, incidents etc.), notifications, tasks, people, response forms etc. and followed by a data filter, which is a pre-created (either system, by one of your users, or yourself. An example could be; Source: Events > Data Filter > All open security incidents.
  • Data Preview: Once a data source is selected and connected, the wizard displays a preview of raw data to ensure the correct source is chosen and to aid in column selection.

Step 2: Configuring Key Features

  • Feature Selection: Users can choose from a range of features to include in their grid. Options might include column ordering, selection, filtering, pin columns.
  • Customisation Options: Depending on the selected features, further customisation settings are available, such as map view, export and actions links.

Step 3: Choosing Columns of Data

  • Column Selection: Users select which columns from the data source should be displayed in the grid. This could involve ticking checkboxes next to column names or dragging and dropping them into the grid layout.
  • Column Customisation: Further customisation may include setting column widths, choosing which columns are resizable or movable, and deciding initial sorting.

Step 4: Setting Up Filtering Tools

  • Filter Types: Users can specify what additional filters are available.
  • Advanced Filtering: The wizard will allow you to add a sophisticated filtering mechanism called 'Query Builder', which allows custom filter functions, or the ability to create filters combining multiple conditions and save them.

Final Steps: Preview and Implementation

  • Grid Preview: Before finalising, users can preview the grid with some actual data to see how their configurations work in practice. This step is crucial for making any necessary adjustments.

Integration and Adaptability

  • Adaptability: A well-designed grid wizard should adapt based on the selected data source and user choices, only presenting relevant options and hiding non-applicable settings.
  • Guidance and Help: Throughout the process, the wizard can offer help sections, and validation messages to assist users in making informed decisions.

 

Data grid offers numerous advantages over a traditional lists, especially in scenarios involving complex datasets and the need for dynamic user interaction.

Interactivity:

Provides extensive interactive features such as sorting, filtering, and pagination, which are not typically available in static lists. This allows users to engage with and manage the data more effectively, tailoring the view to their needs.

Handling Large Datasets:

Optimised for performance with large datasets, efficiently managing thousands to millions of rows without degrading the user experience. Traditional lists can struggle with performance issues as data volume grows.

Customisation & Flexibility:

Customise almost every aspect of the grid's behaviour and appearance, from cell rendering to complex data structures like tree data and grouped rows. This level of customisation is generally not available in simpler list implementations.

Rapid Data Updates:

Supports rapid data updates, which is crucial for applications that require the display of continuously changing data.

Integrated Advanced Features:

Features like row grouping, pivoting, and aggregation are built-in with Ag-Grid. These allow for sophisticated data analysis and visualisation directly within the grid, which static lists cannot provide.

Accessibility and Internationalisation:

Designed with accessibility in mind, supporting roles and keyboard navigation.

Swop Views:

Switching between list and map views allows users to choose the most effective way to view and interact with data based on their specific needs at any moment, thereby enhancing the functionality and accessibility of an application.

Export Capabilities:

Users can export data from the grid to CSV, facilitating further analysis or reporting outside the application.

 

Flipping from a list view to a map view in an application can offer several benefits, enhancing user experience and providing more context to the displayed data. Switching between list and map views allows users to choose the most effective way to view and interact with data based on their specific needs at any moment, thereby enhancing the functionality and accessibility of an application. Here are some of the key advantages:

Spatial Context:

A map view provides geographical context that a list simply cannot offer. Seeing data plotted on a map allows users to understand spatial relationships and distributions, which is especially useful for location-based data.

Visual Appeal:

Map view is a visually engaging and can make the application more interactive and appealing to users. This can lead to a more enjoyable user experience and potentially increased user engagement.

Immediate Insights:

In a map view, patterns such as clustering or geographic trends can be immediately apparent, which might not be noticeable in a list format. This can be crucial for decision-making and analysis in many fields like real estate, logistics, and environmental studies.

User Interaction:

Map view often allow users to interact with the data more dynamically. Users can zoom in and out, pan across different regions, and click on markers for detailed information, which can make exploring the data more intuitive than scrolling through a long list.

Data Filtering:

In map views, data filtering can be visually represented, such as highlighting areas that meet certain criteria or dimming others that don't. This visual differentiation can help users quickly identify areas of interest or concern.

Customisable Data Layers:

Map view can support multiple layers that users can toggle on and off to view different types of data simultaneously or isolate specific datasets. This flexibility is useful to see locations of sites, people and other events.

 

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