Features

1. Adavanced Analytics: You can analyze large datasets, gain insights and discover hidden patterns and trends
2. Data Visualization: You can plot your data in interactive graphs and charts. This can help you present your data in a more accessible way to your team or clients.
3. Predictive Analysis: You can build machine learning models to predict future trends based on past data. Some very powerful use cases are Lead Scoring or Churn Prediction Models
4. Text Analysis: Analyze and extract relevant information from free text, identify the main topics and keywords in just a few clicks. We use natural language processing (NLP) algorithms that you can easily apply to your reviews or any free text that you want to analyze.
5. Social Network Analysis: You can analyze social network structures, discover clusters, influencers, etc.
6. Customer Segmentation: Based on the various data of customers, you can classify them according to various categories to better target your marketing.
7. Network Analysis: It is used to understand and visualize complex relationships between different data points.
8. Collaborative Analysis: You can work with your team by sharing cases and results directly in the Graphext project. Generate reports or export inisghts in your favourite format

Yes, we offer various possibilities for sharing your insights:

1. You can save interesting insights within the Graphext project and share the entire project with your team so that they can explore the insights interactively and dynamically.
2. You can export plots or any visualization you like in all the most common formats.
3. You can export all insights as a PDF report.
4. You can write back the output of your models or clustering algorithms to your favorite data source.

Graphext is not a Black-box! We are committed to full transparency in Graphext. Therefore, under each transformation or flow, you can always read about every model or function that is running. If you have no data science knowledge, you can trust our good practices and expertise. However, if you are curious to know more about the algorithms or even tweak the parameters, you can do so by modifying the code of our recipe. You can read much mora about our low-code in our API Docs

All the export_to… steps have a parameter if_exists that allows you to choose different options to handle it. The default value is ‘Fail’ to prevent you from accidentally losing your data or compromising a table’s structure in your database. - ‘Replace’ if you want to override the existing table. Keep in mind this option deletes your previous data. - ‘Append’ if you want to append the dataset’s rows to the table.

Must be one of: "fail", "replace", "append"