How to combine data from LinkedIn with Hive

Pipes allows you to quickly Integrate LinkedIn with Hive data for a combined analysis.
Load data from LinkedIn and Hive into your central data warehouse to analyze it with the business intelligence tool of your choice.
Pipes allows you to connect to LinkedIn, Hive, 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 Hive

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

Combine data from LinkedIn and Hive

Pipes lets you select the data from LinkedIn and Hive 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 Hive

Apache Hive is a data warehouse infrastructure which provides query, data summarization, and analysis, built on top of Hadoop. The Apache Hive data warehouse software facilitates writing, reading, and managing large datasets with distributed storage using SQL. A JDBC driver and command line tool are provided to connect users to Hive.

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.