When working with Jedox Integrator, logs are your best friend for troubleshooting and monitoring. But did you know you can access these logs programmatically using the Jedox Logs API? This is super useful if you want to automate log checks, integrate them into external monitoring tools, or simply avoid clicking through the UI every time.
In this post, I’ll show you how to:
Understand the Logs API endpoints
Access log data using REST calls
Use filters to get exactly what you need
Step 1: Why Use the Logs API?
Normally, you check logs in Cloud Console→Server Logs. But if you’re building automated workflows or need logs for external dashboards, the API is the way to go. It gives you:
Direct access to log entries (Integrator jobs, system events, etc.)
Ability to filter by date, level, or component
Integration with tools like Power BI, Databricks, or custom scripts
Step 2: The API Endpoint
The base endpoint is:
GET /https://logs.${Instance}.cloud.jedox.com/logs
Step 3: Authentication
You’ll need your Token, which can be found in Cloud Console Settings. Add...
If you’re working with large datasets and advanced analytics, Databricks is a powerful platform that combines data engineering, machine learning, and analytics in one place. But what if you want to bring that data into Jedox for planning and reporting? In this guide, we’ll walk through the basics of connecting to Databricks via its REST API and pulling data into Jedox.
Step 1: Open Databricks and Understand the Structure
Start by logging into Databricks. Once inside, you’ll see the Catalog section on the left-hand side. Here’s what the main components mean:
Catalog: The top-level container for organizing data assets.
Workspace: Your environment where notebooks, jobs, and data live.
Database: A logical grouping of tables within a catalog.
Table: The actual dataset you query. In our example, the table is orders_2_drillthrough.
In the screenshot above, you can see:
Catalog: main
Workspace: default
Database: default
Table: orders_2_drillthrough
This table contains columns like Year, Month, Products, Customers, and Measures—perfect for analysis in Jedox.
Step 2: Generate a Bearer Token
To access Databricks programmatically, you need an authentication...
Salesforce is the backbone for many sales teams, while Jedox is a powerful tool for planning, budgeting, and forecasting. Combining both can give your team real-time insights directly inside Salesforce, without switching between systems.
In this post, I will show you three main ways to embed Jedox reports in Salesforce, plus some technical tips to make it work smoothly.
Integration Methods Overview
There are three practical approaches:
In-App Integration – Add Jedox as a web tab inside your Salesforce app
In-Object Integration – Embed Jedox reports directly in Lightning pages
Anywhere via Hyperlink – Use hyperlinks to open Jedox reports from any object
And yes, there are other advanced options like Visualforce pages, iFrames, or Apex coding, but let’s focus on the easiest ones first.
1. In-App Integration – Jedox as a Web Tab
This method adds Jedox as a web tab inside your Salesforce app.
How it works:
Create a Web Tab in Salesforce
Choose Tab Type: URL
Add the Jedox report URL with parameters
Authenticate via SSO or username + password
Example URL...
Why this topic?
Many Jedox users ask me:
“Can I trigger ETL jobs from outside Jedox? Maybe from Power Automate, or even from a custom app?”
Yes, you can! And the answer is: Jedox OData Hub.
In this post, I will show you how to trigger ETL jobs using OData API – with and without variables. I will also explain how to get the OData license, and give you a real-life use case that maybe sounds familiar to you.
What is Jedox OData Hub?
Jedox OData Hub is a cloud-based service that allows you to access data from Jedox OLAP and Integrator using the OData v4 standard. [knowledgeb....jedox.com]
With it, you can:
Read cubes, dimensions, and views
Run ETL jobs (loads, extracts, transforms)
Pass variables to jobs
Connect to tools like Power BI, Excel, Power Automate, or your own app
🔐 How to get the OData license?
OData Hub is not included by default in all Jedox licenses. You need a separate license which can be found in Jedox Ecosystem Connector License.
To get...
Introduction
Jedox is a powerful platform for enterprise planning, but when teams span multiple languages, communication can become a challenge. That’s where DeepL, an AI-powered translation service, comes in. In this post, we’ll explore why integrating DeepL with Jedox makes sense, how to do it, and where it can add real value—especially in translating comments and user-generated content.
Why DeepL?
Accurate translations: DeepL is widely praised for its natural-sounding translations, especially in business contexts.
Fast and scalable: Translate content instantly without leaving Jedox.
Improved collaboration: Make dashboards and reports accessible to global teams.
How to Integrate DeepL with Jedox
Step 1: Get Your API Key
Visit https://developers.deepl.com/docs/getting-started/intro and sign up for an API account. You’ll receive an auth_key to use in your requests.
Step 2: Create a REST Connection in Jedox Integrator
Go to Integrations > Connections
Choose REST as the connection type
Set the base URL:https://api.deepl.com/v2/translate
Add parameters:
Authorization=DeepL-Auth-Key [YOUR_API_KEY]
Content-Type: application/json
Accept: application/json
text=YourText
target_lang=EN (or any supported language code)
Use Cases in Jedox
1. Translating Cell Comments
Enable users to write comments in their native language and have them auto-translated for reviewers in other regions.
2. Multilingual Dashboards
Use DeepL to translate...
If you're new to Jedox Integrator, one of the most powerful tools you’ll want to learn early is the tracepoints. It’s a simple but useful feature that helps you see what your data looks like at different stages of your ETL process.
In this guide, we’ll explain what tracepoints are, how to use them, and walk through a real-world example using employee data.
What Are Tracepoints?
A tracepoint is like a checkpoint in your ETL process. It lets you capture and inspect the data flowing through your Extract, Transform, and Load steps — without changing the data itself. Think of it like placing a camera on a conveyor belt: it takes a snapshot of the data at that moment, so you can see what’s happening behind the scenes.
Why Use Tracepoints?
Here’s what tracepoints help you do:
Debug: Spot errors in your data flow
Validate: Confirm that transformations are working
Audit: Track what data was processed and when
Filter: Focus on specific rows (e.g., one employee)
Real-World Example: Trace a Specific Employee
Let’s say you’re working with a CSV...
Hey Jedox friends! 👋
If you are already playing with version 25.1, you may have noticed two cool things:➡️ Native Chart component on Canvas➡️ New Themes feature in Administration
And if you haven’t yet—no worries! That’s why we have this blog 😄 I will show you step-by-step what is new, what is possible now, and why this is super cool, especially for beginners who want to make nice-looking dashboards without coding.
Native Chart on Canvas – What is that?
Before, if you wanted to show a chart in Canvas, you had to create it in a spreadsheet report and then show the full report inside Canvas. It was not very flexible, and charts were not really part of Canvas directly.
But now — you can add a chart just like a label or image. It’s a real Canvas component 💪You can resize it, move it, copy it, all inside the Canvas itself. No need to switch between reports.
Here’s what it looks like:
👉 Click "Add Component"...
If you're working with data in Jedox and need to pull information from Google's BigQuery, you're in the right place! In this guide, we'll walk you through how to set up the REST connector in Jedox, authenticate using Google tokens, and pull data from BigQuery.
Why Big Query Uses a Modified JSON Format
Before we dive into the steps, it's good to know why BigQuery uses a slightly different version of JSON. BigQuery expects newline-delimited JSON (NDJSON), where each JSON object is on a separate line. This makes it easier to process large datasets efficiently. If you're preparing data for loading , make sure it's in this format.
For example:
{"id": 1, "name": "Alice"}
{"id": 2, "name": "Bob"}
This is why we can't just use standard JSON where everything is wrapped in one big array.
Step 1: Get Your Google Token for Authentication
To connect Jedox to BigQuery, you need to authenticate using a Google token. Here's how to get it:
Go to the Google Cloud Console https://console.cloud.google.com/.
Navigate...
In today's data-driven world, companies operating in Germany and across the EU must comply with strict data privacy regulations, such as the General Data Protection Regulation (GDPR) and other local laws. One key requirement in many industries is the removal of user behavior data after a certain period to protect user privacy. This can include deleting user accounts that have been inactive for a specific duration.
The Problem: Removing Inactive Users Automatically
Many businesses store user login data, but regulations may require them to delete users who have not logged in within a specific timeframe—for example, 90 days. Manually managing this process is inefficient and error-prone, especially for large organizations.
To address this challenge, we can use Jedox ETL (Extract, Transform, Load) to automate the identification and deletion of inactive users. This ensures compliance while reducing manual effort.
Solution: Using Jedox ETL to Identify and Delete Inactive Users
Jedox ETL allows us to create a streamlined workflow to extract user login data, filter out inactive...
In multidimensional databases like Jedox, managing dimensions and hierarchies effectively is crucial for accurate data analysis and reporting. Consolidations, which define parent-child relationships within dimensions, are an important part of this process. In this post, we’ll explore how to automate the creation of base and consolidated elements using Groovy scripting in Jedox ETL. We’ll also dive into a practical business use case to showcase the power of this approach.
The Problem: Automating Dimension Hierarchies
Managing dimension hierarchies manually can be time-consuming and prone to errors, especially when dealing with dynamic or frequently changing datasets. Using Groovy in Jedox ETL, we can automate the creation and management of elements and their consolidations. This makes the process faster, more reliable, and easier to maintain.
Below is a Groovy script that demonstrates how to:
Connect to a database and retrieve a dimension.
Create base elements and a parent element.
Add consolidations between the parent and its child elements. Java documentation here.
The Script: Building Base and Consolidations in Jedox
Here’s the...
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