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- Using Enso to Analyze Google Analytics Data
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Cassandra Clark
Data comes from a variety of different sources. A common source used in Marketing is Google Analytics. We’re going to focus on connecting to Google Analytics, running a report using Enso, and then bringing in a second, external data source, as marketing data is rarely housed in only one location. To connect to your Google Analytics for use in Enso, we’ll need to create a service account. There’s an in-depth guide to this in Google’s documentation. Follow steps one and two of this guide to enable the Google Analytics API and create a service account. You’ll then be able to download a credentials.json file. Once you have this file and have configured the service account with Viewer permissions on your property, we’re ready to access data in Enso. To use your service account in Enso, you can pass in the credentials file, or set up an Environment Variable called GOOGLE_APPLICATION_CREDENTIALS. This will be used automatically to authenticate with your service account in Enso. To run a…2024-04-03 - Detecting Credit Card Fraud
- Cassandra Clark
In our increasingly interconnected world fraud has become a pervasive force. Criminals worldwide are using increasingly sophisticated techniques to steal data and money from hapless victims. These techniques cause losses of billions of dollars worldwide. Fortunately, technology is incredibly helpful for identifying these attempts at fraud. In this article, we will focus on credit card transactions specifically. We will demonstrate how to use Enso to bring in multiple data sources to flag transactions identified by a variety of systems as fraudulent, from stolen credit card details to compromised payment terminals. To start things off we’re going to read in our dataset of credit card transactions. This dataset has a transaction_id which is a unique identifier per transaction, tx_datetime which shows the time the transaction occurred, customer_id which identifies each user, a terminal_id which identifies where the transaction took place, and tx_amount which is the amount of the…2023-11-24
- Getting Started – Parsing, Selecting and Grouping
- James Dunkerley
In this post, I will build on top of my last post and go over how to parse values in the dataset, select down to just the columns we are interested in, and finally aggregate the data. The previous post covered installing Enso and then loading in some data. This post starts from the workflow created in the last post, still using the Kaggle Superstore Dataset. If you have not read that post, I recommend you do so before continuing. That workflow can be downloaded from here. The goal of this workflow will be to get a table of the total sales by category for each month (using the order date). Let’s start by taking a look at the structure of the data. We can do this using the info function on the first node. To add this node, select the first node and press Return or drag out from the bottom of the first node. Then, in the new node, type info or choose it from the Component Browser. This function returns a new table containing the metadata about the table. In this case: | Column…2023-11-10 - Getting Started
- James Dunkerley
In this post, I will use Enso to read and process a CSV file. Enso is being designed and built to make it easier to process, blend and analyse data. It is a new programming language designed to have a dual representation both as text and as a visual graph. The dataset used in this walkthrough is available from Kaggle here. The goal of this post is to cover reading this data and finding the five highest-value furniture sales. Let’s start by getting Enso installed. It will work on Windows, Mac, and Linux. This guide is based on Windows. You can download the installer from here. Download the appropriate Enso IDE entry for your operating system and run it. On Windows, you must have the Visual C++ Restributable installed. If you don’t have it, you can download it from here. Once the installation has been completed, you can launch Enso from the start menu or desktop shortcut. It may need to be approved by your firewall. Once it has started, you will see the following screen: The login is…2023-11-02 - Using Enso to Solve Preppin Data Challenges
- James Dunkerley
Enso is a functional programming language that lets you quickly and simply load, blend, and analyze your data. We’ve been building out the core capabilities of the product and are rapidly working on the IDE and cloud release to give a straightforward experience for users using it. To show some of the new capabilities, I have tackled the first three challenges of 2023 posted on Preppin Data. These data challenges are posted by Carl Allchin, Jonathan Allenby, Jenny Martin, and Tom Prowse. They are solvable in many data tools and make an excellent set of tasks to show how to use Enso. This blog was written using a recent nightly build; many features and functions are still maturing and subject to change as we approach our release. In addition, we are still working on adding more “widgets” to the nodes and improving data visualization capabilities to help guide you through building the workflow. These will appear over the next month or two in the nightly builds. https://preppindata…2023-03-10