CloudConnect Example Projects

CloudConnect is a legacy tool and will be discontinued. We recommend that to prepare your data you use the GoodData data pipeline as described in Data Preparation and Distribution.

To get started using CloudConnect to build real-world solutions, you may download and import the following projects into CloudConnect, where you can explore how they are configured and modify them to suit your purposes. These CloudConnect projects are intended to provide beginning users the means to create successful integrations with common data sources.

These projects can be explored in the order listed below.

Contents:

Twitter Search API Example Project

This CloudConnect project enables integration with the Twitter Search API, which can be used for retrieving tweet content and usage statistics for specified strings. Starting with the base project, which searches for references to the string gooddata, this project can be modified to utilize your own Twitter account to retrieve tweet activity of interest to you.

As part of the Getting Started workflow, this project is a great introduction to CloudConnect and development for the GoodData platform in general.

This project is later used in the final example, in which the Google Analytics and the Twitter Search API projects are combined into a single CloudConnect project and published.

HR Example Project

This example project models a simple Human Resources application, in which employee payment transactions are modeled. These transactions are integrated into a hierarchy of information, in which transactions are associated with employee records in the Employee dataset. These records are, in turn, associated with records in the Department dataset. Additionally, the project includes a simple ETL graph, in which data is gathered from three separate CSV files and uploaded to the corresponding datasets in the GoodData project.

Google Analytics Example Project

This CloudConnect example project creates an integration between your Google Analytics account and the GoodData project that you designate. This project features six datasets, corresponding to the following categories of Google Analytics data: Campaign, Visitor, Content, Geography, Browser, and OS.

While the range and volume of data may seem large, the project itself is fairly simple. Each dataset is populated by a separate graph featuring the same three components to extract, transform, and load the data into the designated project.

As part of this project, you must configure a CloudConnect connection to your Google Analytics account, so that CloudConnect can access the data. When the ETL is executed, your GoodData project is populated with a rich repository of useful information about activities on your web site.

The Google Analytics API resource has been deprecated. See Update the Google Analytics Connection in a Project.

This project is later used in the final example, in which the Google Analytics and the Twitter Search API projects are combined into a single CloudConnect project and published.

Facebook Example Project

This CloudConnect project provides an integration between the Facebook Insights API and CloudConnect Designer. As part of your exploration of this project, you build a personalized connection to Facebook within CloudConnect, so that it can integrate with your Facebook account to retrieve data. These types of connections are frequently defined in CloudConnect, so that Reader components can extract data from authenticated web systems.

This project also introduces how to configure the Facebook Reader component to execute a query specified in FQL (Facebook Query Language). When query data is received, it is passed through the ETL process. In each step, you are introduced to additional data-specific configuration that you must apply in order to complete the integration.

Due to the changes in the Facebook Platform API, we dropped the support of the FQL option in CloudConnect (the Facebook Reader). Only the Graph API option is available. Check your graphs in CloudConnect, and make sure that they are using Graph API.

As a final step, you redirect the data from the GoodData platform to a local flat file, which is a useful technique for debugging ETL. In a linked article, you can learn how to redirect the output from the local CSV file to a project in the GoodData platform. Part of this process includes building a simple logical data model from scratch and publishing it to the GoodData project.

Salesforce Example Project

This example project steps you through the process of connecting to Salesforce to acquire data from the Sales Account, Opportunity, and Opportunity Line Item objects. After you provide your Salesforce credentials to the project, you configure the ETL graph to use a SOQL query to retrieve the specified data and then pass that data through each step of the ETL process.

As part of the ETL process, the Opportunity and Opportunity Line Item data sources are combined using a Joiner, which is a useful mechanism for blending two data sources into a single dataset within GoodData.

Advanced - Agile Data Warehousing Service Example Project

The Agile Data Warehousing Service is a leading-edge columnar datastore specifically designed to capture your data directly from the source and retain its entire history. This CloudConnect project provides the necessary framework for configuring CloudConnect Designer to connect to a Data Warehouse instance. Once connected, you can use standard SQL queries to load, transform, and extract your data for uploading into your GoodData projects.

Use of Agile Data Warehousing Service requires the ability to design database tables and to define and execute SQL queries.

Your Next Project

If you have completed more than one of the above projects, then your next project is to combine multiple example projects into a single CloudConnect project, feeding a single GoodData project.

In this example, you combine the Google Analytics and Twitter Search API projects, so that you can report on how Tweets might influence the behaviors of visitors to your web site.

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