Getting Started with Labguru Analytics – Labguru

Labguru Analytics is the new home for reporting in Labguru, replacing the legacy Labguru Dashboards. It gives you a richer way to explore your lab data — trends over time, combined information from different parts of Labguru, your own reports and charts, and the ability to view your Labguru data in a tool such as Power BI, Tableau or Excel.

This article is the first stop for new users: it explains what Analytics is, how to open it, what you can do once you are in, and walks you through building your first query, chart, and dashboard end to end.

Optional module. Labguru Analytics is a separately licensed module. If your organization has not enabled it, the Analytics options will not appear in the Labguru menu. Contact Cenevo Support or your account representative to learn more.

Legacy Dashboards are being retired. The previous Labguru Dashboard module is being phased out in favor of Analytics. Existing dashboard users should move their reporting workflows to Analytics; see Cenevo Support or your account representative for the retirement timeline for your organization. For guidance on moving an existing dashboard, see Migrating from Legacy Dashboards.

Analytics is designed for reporting rather than only real-time monitoring. Data is refreshed on a regular schedule configured for your organization.

What you can use Analytics for

See what's happening in your lab
Build your own report or chart
Look at long-term trends and history
Combine data from different Labguru areas
Open the data in Power BI, Tableau or Excel

How your data gets here

Analytics is built on two layers working together: a data lake that prepares your Labguru data for reporting, and a reporting application that lets you explore and present it.

Your Labguru data is synced on a regular schedule into Databricks, a managed data lake. This is where raw, transactional Labguru data (experiments, samples, inventory, and so on) is cleaned, structured, and organized into reporting-ready tables — this stage is often called the gold layer.
Analytics itself is powered by Omni, a business intelligence application embedded directly inside Labguru. Omni connects to the Databricks gold layer and provides the workbook, dashboard, and querying experience described throughout this guide.
Because Omni is embedded, you never leave Labguru or sign in separately — the Analytics options in the Labguru menu open Omni's interface directly, using your existing Labguru identity and permissions.

This separation matters in practice: the data refresh schedule is a property of the Databricks sync, while everything about building, viewing, and sharing reports is a property of Omni. If a number looks out of date, it is almost always a Databricks refresh timing question rather than an Omni one — see If something does not look right.

What is Omni?

Omni is a modern business intelligence and analytics platform. Cenevo has embedded it inside Labguru so you get a full-featured reporting experience without needing a separate license, login, or application. Everything you see when you open Analytics — workbooks, dashboards, the AI assistant, charts — is Omni's interface, styled and delivered through Labguru.

Because Omni sits on top of a shared, curated data model (the topics described in A few terms before you start), everyone building reports works from the same consistent definitions. Note that this covers who can build and what topics are available to query — see the callout below for how this differs from data-level visibility once a dashboard is shared.

A note on data visibility

Access Dev Tools controls who can build queries and dashboards, and which topics they can query against. It does not currently filter what data a shared dashboard shows based on the viewer's own Labguru permissions (for example project or group membership). Once a dashboard is shared, whoever it is shared with sees the full result the query returns. See Organizing and Finding Content for more on sharing responsibly.

Opening Analytics

Once Analytics has been enabled for your account, it appears in the workspace menu at the top right of Labguru. Selecting it opens the reporting experience inside Labguru. You do not need a separate login.

Sign in to Labguru as you normally would.
Click the workspace name at the top right of Labguru, then choose Analytics.
The reporting area opens in the main work area. You may see a short loading indicator the first time you open it in a session.

You stay signed in to Labguru the whole time; Analytics uses the same identity, so anything you are not allowed to see in Labguru will also be hidden in Analytics.

A few terms before you start

A handful of terms come up throughout this guide. Knowing them up front makes the rest of Analytics much easier to follow:

Document — The saved unit of analytics content. A document is made up of a workbook (where queries are built) and a dashboard (how the results are presented).
Workbook — The main analysis environment. Each workbook holds one or more tabs, and each tab is a query you build and refine.
Dashboard — A presentation layer built from a workbook, where queries appear as interactive tiles you can arrange, filter and share.
Topic (dataset) — A curated collection of related fields prepared for analysis, such as Experiments, Inventory, or Samples. Every query is built on top of a topic, which keeps results consistent across whoever builds them.
Dimension — A field you group by, such as a date, project, or sample type.
Measure — An aggregated value calculated over your dimensions, such as a sum, count, or average.
Fact — A single value in the data, such as one measurement or record, before any grouping or aggregation is applied.

These concepts are covered in more depth in Analyze & Build and Visualize & Present.

What you can do

Analytics replaces the legacy Labguru Dashboard module. Inside Analytics you can:

Ask questions about your data in plain English with the Analytics Assistant, and refine the query it drafts.
Open dashboards that have been published by your organization, for example monthly sample throughput or equipment utilization reports.
Explore the data by filtering, grouping and pivoting to answer ad-hoc questions.
Save your own views as personal bookmarks for next time.
Download results as CSV or Excel for further analysis or sharing.
Schedule deliveries of dashboards by email or other channels, where your organization has enabled this.
Set up data alerts that notify you only when a condition is met, such as a value crossing a threshold. See Downloading, Sharing, Scheduling and Alerts.

The exact set of dashboards available to you depends on what your organization has published and on your permissions.

Building vs viewing

Building and sharing dashboards requires the Access Dev Tools permission in Labguru. Users with this permission can build queries, create dashboards, and publish them for others. All other users have view-only access — they can open and explore published dashboards but cannot build them. See Analyze & Build.

The fastest way to start: Cenevo's prebuilt dashboards

Rather than building a dashboard from scratch, the fastest way to get value from Analytics is to start from one of Cenevo's prebuilt dashboards. Cenevo publishes a set of ready-made dashboards covering common lab reporting needs — for example sample throughput, inventory levels, and experiment activity.

Open Analytics from the workspace menu at the top right of Labguru, then choose Hub in the sidebar.
Look for the Cenevo-published dashboards, visible to everyone in your organization's Hub.
Open a dashboard that's close to what you need and explore it as-is — no build access required.
If you have the Access Dev Tools permission and want to customize it, copy the dashboard into your own account. Your copy is fully editable, and the original stays untouched for everyone else.

This gets you a working report in minutes, and gives users with Access Dev Tools a solid starting point to adapt rather than building a query from a blank workbook. See Organizing and Finding Content for more on the Default Dashboards folder and copying dashboards.

Your first query, chart and dashboard

If none of the prebuilt dashboards fit what you need, the next quickest way to understand how the pieces fit together is to build something small end to end. There are two ways to start:

Ask the Analytics Assistant — open Analytics Assistant in the Analytics sidebar and describe what you want in plain English, for example “how many experiments were created per month over the last 6 months?”. The assistant drafts the query and a result. You can then refine it, chart it (Step 2) and add it to a dashboard (Step 3). See Analytics AI Assistant.
Build it manually in a workbook — follow Step 1 below, choosing the fields yourself.

Step 1 — Build a query manually

Click + New to create a workbook — your analysis canvas, where each tab is one query.
Choose the topic you want to query against. A topic is a curated set of related fields prepared for analysis (for example, Experiments, Inventory, or Samples).
From the field picker on the left, pick the fields you want — typically one to group by (such as a date or a project) and one to summarize (such as a count or a sum).
The query runs automatically and results appear in the table. That is a complete query — no code required.

For everything you can do here, see Querying Data.

Step 2 — Turn the results into a chart

With results showing, open the Chart tab.
Pick a chart type that suits your question — a bar chart to compare values, a line chart for a trend over time.
Adjust the chart's title and series if you want to tidy it up.

See Creating Visualizations for the full chart library and configuration options.

Step 3 — Put it on a dashboard

Open the dashboard that comes with your workbook. Dashboards are the presentation layer, where queries appear as interactive tiles.
Arrange your chart on the canvas, and add more tiles, text, or filters as you go.
Save the document — it is unsaved by default — so you can return to it later.
Publish it when you are ready to share. Your work stays in draft until you publish, and others cannot see it until then.

See Building Dashboards to lay out a dashboard.

Access Dev Tools controls who can build and publish dashboards, not what data a shared dashboard's viewers can see — see A note on data visibility above.