How to combine data from Twitter with SAS

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

You just need to enter the associated credentials to allow Pipes access to the Twitter API and the SAS API.
3

Combine data from Twitter and SAS

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

About Twitter

Twitter is an online social networking and news service that enables users to read and send short 140-character messages called “tweets”. Registered users can both post and read tweets while unregistered users have read access only. Twitter allows user access through the website interface, SMS and with the mobile app.

About SAS

SAS provides a business analytics suite which help clients to gain insights from their data. The SAS software includes a basic SAS component that performs analytical functions and several other modules that add graphics, spreadsheets or other features.

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.