Datalore Enterprise 2022.2: Blazing Fast Docker-based Installation, Scheduled Runs, Collaboration on Attached Files, and More

On Thursday, 28th July 2022, I gave a webinar about tips for combining Python and SQL in Datalore, our collaborative data science and data analytics platform. Here’s the recording for you to watch if you missed the live stream.

Easy access to relevant, safe data is a major bottleneck hindering developers and data scientists. But what if you could generate your own accurate, privacy-protected, shareable data?  Synthetic data can provide an inexpensive alternative to real sets of data that can’t be used due to its sensitivity or regulations. Such data is used for training machine learning models, testing, and performing quality assurance.  In this webinar with Mason Egger, we'll learn about using Synthetic Data, and we’ll learn how to get started creating our own Synthetic Data. Join us on July 2

Data science projects can be complex, consisting of many parts, such as notebooks, data, environments, and scripts, and it can be challenging for data science teams to effectively collaborate on them.

In this blog post we’ll explain 2 ways to access autocompletion and other coding assistance features for your Jupyter notebooks.

On Thursday, 23rd June 2022, I gave a webinar about how to build reproducibility into your work using Datalore, our cloud-based data science and data analytics platform. Here’s the recording for you to watch if you missed the live stream. https://www.youtube.com/watch?v=MIctg07feIc Description Have you ever had the experience of opening up an old analysis you did in Jupyter and being completely unable to reproduce the results? Maybe you can't work out where you saved the data you used, or what version of a core dependency you had in your environment. Perhaps your Jupyter notebook is

Schedule Jupyter notebooks with just a few clicks. Specify run intervals from the interface or use the cron string to configure a schedule.

In this blog post we’ll share a few updates to database support and SQL cells, announce the first Datalore webinar, and tell you how Datalore has become even more collaborative.

In the past few months, we’ve been working hard on improving the data exploration and collaboration workflows in Datalore. In this blog post, we’ll give you an overview of what’s new!

Check out the newest data exploration features and enjoy the upgraded interactive reporting experience in Datalore Enterprise 2022.1.

We talk and write a lot about sharing in Datalore as we truly believe in the collaborative nature of data workflows. Today we are happy to introduce a new feature for the result sharing workflow – publishing of Interactive reports.

Learn two easy ways to use Python and SQL from the Jupyter notebooks interface and create SQL queries with a few lines of code.

What are the most common ways to query SQL databases from a Python notebook? They might include using Python SQL libraries such as PySQL or SQLAlchemy... We can now suggest a more effective method: combine native SQL cells and Python code in Datalore notebooks.