Getting Started

Before you can visualize data in Kooltra Analytics, you need to create a dataset which contains data from Kooltra and/or imported information from third-party systems. This dataset is built using a tool called a dataflow which can be found in the Data Manager. To access the Data Manager, click on the gear icon in the top right of the Analytics Studio and select Data Manager.


What is a Dataflow? 

Dataflows are the underlying instructions that specify what information you'd like to be a part of your dataset and how you'd like to massage this information. The dataflow builder is a simple click-and-point interface with a variety of tools that allows you to specify these instructions without having to write any of the queries.

Data Manager


The data manager has a navigation menu highlighted in blue that allows you to navigate between the Monitor, Dataflows and Recipes, Datasets and Setup. Each one of these sections is described below. 

Monitor - Dataflows can be run every hour to update the data in the datasets that they create. You can monitor the status of the dataflow by viewing its status on the Monitor page. 


Dataflows and Recipes - You can view existing dataflows or create new dataflows in this section. A step-by-step example of a new dataflow is shown at the end of this user guide.


Datasets - Any datasets created from your dataflows will be listed here.


Setup - This section allows you to set up a schedule for data replication. Replication is a tool that extracts data on a seperate schedule from your dataflows resulting in the dataflows running faster. Replication only needs to be configured once.


Available Dataflow Tools

Simple dataflows can be built using the datasetBuilder tool which is the first button available in the toolbar. This tool allows you to quickly extract information from Kooltra data objects, and join them together. For example, you can quickly create a 

Additional tools that you can use to expand or refine your dataflow are:

These tools are available in the top row of the dataflow builder.


Note that the link for each tool overviews the tool and dives into the code behind the tool. While the code may be relevant for advanced users and developers, users that would like to build simple to intermediate datasets can still use each tool's clickable interface by clicking on the tool. This is shown in the video below for the sfdcDigest tool.


Building a Sample Dataflow

Follow the steps below to build a sample dataflow that extracts trade and account information from Kooltra.

Step 1. In the Dataflow and Recipies section, click on Create Dataflow and enter a name for your Dataflow. Once you've clicked create, you will be taken to the Dataflow builder. Note that you are able to create multiple datasets from a single Dataflow, but for the purposes of this example we are creating a new dataflow.


Step 2. In the Dataflow Builder select the first tool - datasetBuilder. This tool allows you to quickly build simple dataflows.


Step 3. In the Select the FXTrade data model (Salesforce object). This is the first data model that you'll be extracting data from. Once you've selected FXTrades, you can click on the + icon to the right to the right of the box and select the fields you'd like to extract. In this example we'll extract Trade Name, Action, Account, Currency 1, Currency 2, Amount 1, Amount 2, StandardPairName, and USDTransacted Value.


Step 4. On the FXTrades object, click on the relationships tab and select Accounts. Similar to the FXTrades object, you are able to click on the + icon and select fields that you would like to extract from Accounts. In this example, we'll be extracting just the Name field.


Note that many of the data models in Kooltra are linked together. You can extract the data from multiple data models as long as there is at least one field linking them together. In the case of Trades, there is a field called Account (Counterparty) which links the trades to the Accounts object. When linking different data models together in the datalow, always start with the child data model, or the data model that looks up to other data models.

Step 5. Click the Next button at the bottom of the window which will create the dataflow. This dataflow will join both the Account and FXTrade Object using the augument tool and then register the dataset using the sfdcRegister tool. You can click on each of the purple boxes to open up the details of each tool. To complete creating this dataflow, click on the Update Dataflow tool highlighted in blue.


dataflow, dataset