What is Datalore

The core concept of Datalore is a notebook, a document where you code in one of the supported languages. While code cells is the main building block of Datalore notebooks, you can use various types of no-code cells, which help you create descriptive or explanatory texts, access and analyze data, build data visualizations, and provide interactivity for your outputs without writing any code.

Python is the default programming language in Datalore, but this platform also allows you to code in Kotlin, R, and Scala.

Datalore does a lot to facilitate collaboration in data teams. Whichever part of the process you're involved in, Datalore makes sure you all work in tight-knit collaboration. At any point in time, you can quickly share your work with your team members, and you choose which access level they will have to the shared content. As everyone on your team can leave their comments and track each other's input in real time, you can collaborate most seamlessly and transparently.

Datalore allows you to connect to a rich variety of data sources with its native support of dozens of database types and most popular cloud storage systems. You can also work with data files imported from your local machine or external resources.

Moreover, Datalore features a special type of cells (SQL cells), which enables you to query your data sources and convert the results into DataFrames.

Datalore is packed with no-code tools that allow you to interact with your datasets and build customizable visualizations from them without writing a single line of code. All you need is a data source.

Even if you do write some code, you're backed up by Datalore's AI assistant, which will help you generate, edit, or explain your code based on the context of your project.

Code completion is yet another powerful feature that helps you edit your notebook as fast and efficiently as required.

In short, anyone in your team can use Datalore even if they have minimum or no coding experience.

You can choose from a wide range of machines to run your code in Datalore, depending on how quick you want your computations to be and how resource-consuming your projects are.

Background computation is a Datalore feature that makes sure your notebook is still running even after you're no longer active there.

And there's Reactive mode, an alternative to the classic Jupyter mode, which ensures faster notebook computations via calculating only modified cells and those affected by them.

Having a finalized notebook is a great thing, but when you publish it as report, an HTML page, where you highlight the outputs of your code, it's even better. Reports is how you present your work in Datalore, stripped of code and everything else, leaving just what you want your target audience to see.

A masterfully crafted report is a powerful source of information, a result of your data analysis, and that's what the initial goal of most of your projects as a data specialist is.

You can use our Cloud version of Datalore, where everything is pre-installed and set up for you and your team. Or, you can use Datalore On-Premises, your own Datalore platform installed, hosted, and configured the way you want it, with computation resources and storage capacities of your choice.