What's New?

July 24, 2022

New Features

Even Bigger Data

Graphext is now able to handle even more data. We have increased our capacity by a factor of 2.4, with projects created with integrations of with up to  2M rows.

Graphext Enhanced: Current Status

With the addition of status updates and error messages, creating highly personalised projects and interpreting the Recipe has never been easier.

Fixes and Improvements

Stories Worth Sharing

May 17, 2022

New Features

Adding, Sorting and Flipping Axes in Plot charts

There are also new options available in Plot to make exploration infinitely easier. Now you can change your Variables' orientation  (vertical or horizontal) and Sort by a third variable to make the visualization more intuitive.

Debug your New Projects with Ease

Keep your progress and applied steps in check at all times with the new access to a Project's Blocks. Blocks will help you debug since you will now receive improved feedback on warnings and errors about your project's execution.

Fixes and Improvements

Stories Worth Sharing

May 4, 2022

New Features

We've added the option to Overwrite your Projects! Now you won't have to create a new Project outside the one you are working on. Simply go to Wizard, create an updated project, and select overwrite before you execute. You will also find the option to create a Backup copy of the existing project; this feature is great for version control. If you have saved Insights before updating your project, don't worry; we keep them for you!

Fixes and Improvements

Stories Worth Sharing

April 27, 2022

Introducing Graphext Fluid

We’re proud to announce a major product update that we’re calling ... Graphext Fluid.

Data science should be an interactive cycle, giving analysts the autonomy to make reactive decisions and adapt their projects on the fly. To reflect this, we’re making Graphext more dynamic and more flexible so analysts can move faster from raw data to insights.

Feature Summary

Automatic Projects - Instantly explore your data with projects created as you upload data.

New Data Table - A smart tabular presentation offering value summaries and ways to grow analysis.

Cast Variable Types - Change the types of your variables on the fly.

New Variable Manager - Group, describe, move, pin and hide columns using variable cards.

Visualize with Plot - Plug your data into a range of common chart types and find patterns (guidance).

Create Graphs & Model Data - Layer on advanced data analysis steps like predictive models and clustering.

What’s Next?

  • More integration sources like Snowflake, Databricks, Redshift, Notion and Airtable.
  • Projects that automatically refresh as datasets update or change.
  • Apply transformation and enrichment functions to your data as you go.
  • More chart types and better customization options in Plot, including adding custom styles to charts.
"Data analytics is iterative - you check the data, explore it, create models and you move back and forth. Fluid is about adapting Graphext so that it helps analysts to analyze data in a more natural way. At the same time, we’re adding major features that make Graphext more powerful."

Victoriano Izquierdo, Graphext CEO & Co-founder

Public Pricing Coming Soon!

Alongside the release of Graphext Fluid, we’re excited to launch affordable pricing options on our website in the very near future. Soon, new customers will be able to pay using credit or debit cards through our website. We’ve designed our new pricing tiers to help you easily scale your plan as and when you need it. But if your just looking to try Graphext out ... our free accounts remain the same and will always be there.

New Features

01. Automatic Projects

As soon as you upload a dataset to Graphext, we’ll create a project for you to explore its contents. Exploratory data analysis is critical to getting familiar with datasets and involves inspection, visualisation and simple transformation. By creating an initial project for you to work with, we’ve pushed all of the decisions further down the line so you immediately have a chance to get to know your data.

Automatic projects are created with any new dataset you upload or integrate with Graphext. Whether you upload a simple CSV file or set up a PostgreSQL database integration, you’ll get an automatic project to explore. Open up automatic projects and get instant feedback on your datasets using Plot or Compare to visualize simple variable or value patterns.

02. New Data Table

Tabular representations can be so much more than endless rows of data points. Our new Data table presents value distributions, organizes variable names and descriptions and lets you filter, hide, pin, sort and search for variables.

But more than this, use the Data panel as a workspace to grow and adapt your projects. Data is also home to Graphext’s data enrichments, data transformations and data modelling/network algorithms. In Graphext Fluid, you can add all of these analysis steps to your project on the fly.

03. Casting Variable Types

You can now change the type of variables inside of your project. Previously, variable types remained fixed inside projects. But as knowledge of a dataset increases, hypotheses can change. Changing the types of variables from inside of a project gives analysts more power to adapt their dataset at any point - a flexibility that can be very useful when applying Graphext’s predictive models to your datasets.

To cast variables, use the Wizard to Start a Project from inside your Data panel. Then, click on the icon next to any variable name and change its type to another from the dropdown list.

04. New Variable Manager

We’ve completely redesigned the management of variables in Graphext making it more intuitive to group, describe and organize the columns in your dataset. Our new variable manager brings together everything you need to manage columns in your data into one central hub, featuring draggable interactive cards to add descriptive information and tags to your columns.

Use the variable manager icon at the top of your right variable sidebar to bring up the variable manager, then start organizing the variables in your data. Add tags to group similar variables together throughout your project, hide variables or use the description text box to clarify more complex ones.

05. Visualizing Data with Plot

As you might already know ... Plot is a space to visualize simple patterns in your data. It contains a range of common data science chart types like histograms, bar charts, time-series charts, box plots and heat maps that you can use to instantly visualize value distributions.

Plot is a fundamental component of Graphext Fluid because exploring data visually is one of the best ways to expose insights that will guide and direct further analysis. Open up Plot in your automatically created project to start visualising key variable and value patterns.

06. Creating Graphs and Adding Models

You can now add advanced analytics steps like predictive models and Graphs that cluster your data to Graphext projects - on the go. Rather than building new projects as you level up your analysis, Graphext Fluid lets you add steps like clustering and NLP transformations using the Data panel inside your existing project. This way, analysts can get to know their datasets better before deciding which models to use and how to apply them.

To add a Graph and/or Model to your project head to the associated panel in the top menu bar of your project and click Create Graph or Create Model. This will bring up the setup wizard where you can choose which kind of analysis you want to conduct. Follow the wizard steps to configure your Graph or Model.

Checking the box to overwrite your project will add the Graph or Model to your existing project, whereas leaving the box unchecked will tell Graphext to make another version of your project containing the Graph or Model.

Fixes and Improvements

Stories Worth Sharing

February 24, 2022

New Features

Inside Plot - our new analysis panel - we’ve added more charts to visualise the relationships between one or two variables. With Plot, you can create bar charts, heat maps, box plots and all of the time-series visualisations previously found inside Trends!

Yep ... Graphext’s exploratory features just got a lot more powerful. Here’s an overview of what we’ve added but check the full Plot documentation to learn more.

"There is magic in graphs. The profile of a curve reveals in a flash a whole situation - the life history of an epidemic, a panic, or an era of prosperity."

Henry D. Hubbard

What Can I Do With Charts in Plot?

Plot charts are designed to help you quickly measure value distribution between one or two variables in your data. The different types of charts you will find require different data types - for instance Overview, Compared Segments and Segmented Overview charts require date values.

You can use your sidebar filters to restrict the data presented inside charts in Plot as well as changing the way that data is aggregated or summarized using the dropdowns at the top left of your chart.

Note: Plot is an evolution of Graphext’s Trends panel. You can still use our Trends charts inside Plot but we’ve added more variety to the types of visualizations you can create.

New Charts in Plot

Bar Charts

Bar charts are a simple representation of two variables. The variable represented on the Y axis must be quantitative. The variable on the X axis can either be quantitative or categorical.

Best used for ... Understanding how values from one or two variables are distributed.

Box Plots

Box plots are great for showing the value distribution belonging to a quantitative variable over a number of different categorical data segments. They represent quartile ranges and median values associated with these categories.

Best used for ... Understanding frequency distribution patterns.

Heat Maps

Heat Maps are great at spotting correlation patterns between pairs of variables. They use a color spectrum to represent density of your dataset at points where values from two variables meet.

Best used for ... Measuring correlation between pairs of variables.

Read more about Plot in our documentation here.

Fixes and Improvements

Stories Worth Sharing

January 27, 2022

New Features

This month we’ve built more Trends charts, a new Graph manager and a data enrichment to upsample survey data on top of a number of important improvements.

01. Trends: Recurrent Pattern Charts

We’ve added a new type of chart to Trends! Charts showing recurrent patterns are designed to reveal similarities in the way that quantitative data evolves over specific time periods.

These charts look a little like box plot charts and show the median and quartile range of values aggregated by hour, weekday, week, month, quarter or year. Recurrent patterns are great for spotting repeating trends like seasonal dips in property price, stock price increases in January or decreases in email open rates on Friday afternoons.

How can I start using it?

  1. Open Trends in a project with date values.
  2. Choose Recurrent Patterns.
  3. Select a quantitative value to plot using the top dropdown menu.
  4. Choose a time period to aggregate your data by.
  5. That’s it. Switch between aggregations to see different perspectives.

02. New Graph Manager

The Graph Manager we’ve just built lives in your right sidebar, making it much easier to see changes you make in real-time. Just bring up the Graph Manager sidebar and watch your actions have immediate effect.

We feel this change makes it much faster and easier to adjust labels or change the size and color of nodes in a Graph.

How can I start using it?

  1. Open a project with a Graph.
  2. Click the settings icon at the top left of the Graph.
  3. Change aspects of your project’s configuration.
  4. See the changes in real-time.

03. New Enrichment: Upsample Survey Data

Survey data often needs to be weighed in order to adjust the influence of certain individuals in the final survey estimates. We’ve built an enrichment to scale survey datasets using a column containing predefined weights.

Our enrichment uses the weights already in your survey data to produce a transformed dataset that adjusts the importance of respondents. Read more about the theory behind surveys and why we built this enrichment in our post here.

How can I start using it?

  1. Open a survey dataset with a predefined weight column.
  2. Choose any type of analysis using the project setup wizard.
  3. Open the data enrichment tab and choose Upsample Survey Data.
  4. Specify which variable contains your predefined weights.
  5. Set a minimum number of rows required to scale your dataset considering its lowest weight.
  6. That’s it. Graphext will transform your survey data.

04. New Tooltip for List Values

Lists are a special kind of data because they hold multiple values. We’ve added a new metric - Total Count - to tooltips associated with lists. Hover over a list value to see it.

Total Count shows the total number of times a value appears. Everything and Selection metrics refer to the number of rows featuring this value and don’t account for instances where a value occurs twice in one row.

How can I start using it?

  1. Open a project with at least one list variable.
  2. Find the list variable sidebar chart.
  3. Hover over any value to inspect the Total Count metric.
  4. That’s it. Start filtering your dataset to see this metric update dynamically.

Fixes and Improvements

- Improved Graphext’s ability to recluster segmentations in big data projects.

- Improved the presentation and organisation of variables in our Text / Social Media > Topics analysis type.

- Add a new variable to Text projects. Length specifies the number of characters in a text value.

- Improved our method of ordering variable charts in Correlations.

- Improved our method of presenting charts without using decimals on either axis.

- Fixed presentational issues with the wizard’s display of creating project steps.

- Fixed a bug causing unexpected behaviour when a user tried to save a manual segmentation.

Stories Worth Sharing

01. 36 Data Podcasts to Follow in 2022

We’ve been curating big list of the best data media around. Here’s one on our favorite data podcasts. Read more.

02. When Dating Apps Met Survey Theory: Sampling, Weighting & Romance

A picture of a population is what most surveys hope to achieve. We're taking a look at the fundamentals of survey theory - sampling & weighting - through the lens of a Pew Research survey that examines American attitudes towards relationships and dating apps in 2021. Read more.

December 13, 2021

New Features

This month we've added search bars in our data tables as well as making it easier to explore Compare & Correlations with large datasets. We've also made it easier for you to monitor the progress of your project setup with a new distinction between processing & configuration steps.

01. Search Bars Across Data Tables

Finding variables in large datasets can be frustrating. We've added a search bar to data tables across Graphext to help you find variables quickly and simply.

Start typing the name of a variable inside the search bar in either Details or the Datasets panel of your team workspace. Graphext will automatically scroll to the location of your variable in the data table.

How can I start using it?

  1. Open up a data table in either Details or the Datasets panel of your team workspace.
  2. Start typing the name of a variable in the search bar.
  3. Click on the variable name from the dropdown list.
  4. Done ... watch as Graphext finds your variable.

02. Dynamic Loading in Compare & Correlations

We've changed the way that charts are loaded in Compare & Correlations. To make it easier to work with datasets with lots and lots of variables, we've added dynamic loading to these panels.

You probably won't notice much difference here on the face of it but behind the scenes ... this feature means that you can load charts a lot faster even when you are working with surveys that have thousands of questions to compare or correlate.

How can I start using it?

  1. Open up Compare or Correlations and load up some charts.
  2. Keep scrolling ... and click 'show more'.
  3. That's it.

03. Filtering Steps During Project Setup

The steps you see as your project is being created are now separated into processing and configuration steps. We've made this change to make it easier for you to monitor the progress of your project setup.

Processing steps relate to the data science steps involved in transforming your dataset and creating your network. Configuration steps relate to the presentational aspects of your project setup. Start building a project and check the new dropdown menu inside of the project execution sidebar.

How can I start using it?

  1. Start building a project and execute the setup.
  2. Check the project execution sidebar.
  3. Toggle between processing steps and configuration steps using the new dropdown menu.

Fixes and Improvements

- Fixed a bug making it difficult to filter data using our interactive histograms

- Fixed a bug preventing a user from editing a manual segmentation with expected behaviour.

Stories Worth Sharing

01. How Aquaservice Use Graphext To Improve Their Prediction Models

We spoke to the data science team at Aquaservice about how they used Graphext to build a clustering model to improve the way they forecast consumer demand. Their project grouped delivery routes using over 30 factors to calculate similarity and exposed patterns in the errors made by their prediction models. Read more.

02. Reverse Engineering Infamous Marketing Strategies from Innocent Drinks

Why are the social media strategies of Innocent Drinks considered as the gold standard for marketing teams the world over? We collected every tweet (10,521) posted by the communication department to deconstruct Innocent's content, style, reach and engagement with a simple topic analysis. Read more.

November 25, 2021

New Features

We've made significant improvements to Correlations! With the addition of relative mode, Correlation charts can be simpler & easier to read because they show the percentage distribution of values belonging to a variable.

Correlations: Relative Mode

Across Graphext, relative mode presents data as a proportional representation. In practise, this means you see data as a percentage distribution rather than an absolute count.

This is especially useful in Correlations charts because these use size and color to visualize the correlation between lots of values belonging to pairs of variables. With relative mode, the size and color range of bubbles in Correlations charts are restricted to a percentage distribution (either on the x or y axis). This makes it easier to spot patterns.

How can I start using it?

  • Open a project and head to the Correlations panel
  • Choose a variable to map your correlations charts or choose two to map specific correlation.
  • Using the Relative vs Absolute dropdown - switch to Relative mode.
  • Notice how the size and color of your bubbles adjust to present a percentage distribution.

Fixes and Improvements

Stories Worth Sharing