How to combine data from LinkedIn with MongoDB

Pipes allows you to quickly Integrate LinkedIn with MongoDB data for a combined analysis.
Load data from LinkedIn and MongoDB into your central data warehouse to analyze it with the business intelligence tool of your choice.
Pipes allows you to connect to LinkedIn, MongoDB, and more than 200 other APIs, web services, and databases with ready-to-use data connectors. Automate your data workflows through data pipelines without a single line of code.
1

Connect your data warehouse

It will be the destination of all data pipelines you build. Pipes supports relational databases in the cloud and on-premises.
2

Connect to LinkedIn and MongoDB

You just need to enter the associated credentials to allow Pipes access to the LinkedIn API and the MongoDB API.
3

Combine data from LinkedIn and MongoDB

Pipes lets you select the data from LinkedIn and MongoDB that you want to load to your data warehouse. These data pipelines will run automatically on your defined schedule!

About LinkedIn

LinkedIn is an employment-oriented and business social networking service which is mainly used for professional networking and communication. With LinkedIn employers and job seekers can both create profiles and form real-world professional connections.

About MongoDB

MongoDB is an open-source document-oriented cross-platform database program that uses JSON-like documents with schemas and is classified as a NoSQL database. The main features of MongoDB among others cover file storage, load balancing, indexing, ad-hoc queries.

Your benefits with Pipes

Get central access to all your data

Access data from 200+ data sources with our ready-to-use connectors and replicate it to your central data warehouse.

Automate your data workflows

Stop manually extracting data and automate your data integration without any coding. We maintain all pipelines for you and cover all API changes!

Enable data-driven decision-making

Empower everyone in your company with consistent and standardized data, automate data delivery and measure KPIs across different systems.