See how easy it is to connect your data using Panoply. In just a few minutes, you can set up a data warehouse and start syncing your LinkedIn Ads data.Try Panoply for Free
Panoply automatically organizes data into query-ready tables and connects to popular BI tools like Jupyter as well as analytical notebooks. From executives to analysts, your entire team will have access to the most up-to-date data and insights they need to drive your business forward.See All BI Tool Integrations
Seamlessly sync LinkedIn Ads and all your other data sources with Panoply’s built-in ETL. Set up a pipeline in minutes with our simple point-and-click interface, then we’ll handle the ongoing maintenance so you can focus on building value, not fixing leaky plumbing.See All Integrations
Easily sync and store over 30+ data sources. Break down the silos separating your data to create a single source of truth your whole company can rely on.Get a Demo
No matter your campaign goals, LinkedIn ads lets you set your own budget and create effective advertising that targets over 630 million active professionals to reach your ideal customer. Panoply makes it easy to load LinkedIn advertising data into your own cloud-based data warehouse using a simplified E-L-T approach that gives data analysts more flexibility and control.
Advertisers can collect ad performance and display targeting data directly from the LinkedIn Ads API without having to write a single line of code. Storing the data in Panoply also makes it easy to combine Linkedin Ads data with other advertising data sources for multi-channel analysis. Connect Panoply to any BI tool with an ODBC connection to visualize and analyze all your Linkedin Ads data. Setup takes minutes so you can spend more time optimizing and less time maintaining brittle data pipelines.
With open source Jupyter Notebook, programmers create and share interactive code, visual graphics, and text. This BI tool supports script in over 40 languages. It integrates to large data platforms like Apache Spark from Python, R and Scala. You can share Jupyter Notebook work through email, Dropbox, GitHub or the Jupyter Notebook Viewer. As with any data operations, you need an ETL to extract, transform and output your Jupyter Notebook code work. Panoply’s Jupyter Notebook integration makes the ETL process easy and seamless. This fully automated pipeline manages the entire ETL workflow on the cloud in real time. With Panoply, your data is continuously uploaded, cleaned and streamed to the client side. So the output you share is always the most relevant and up to date.