JetBrains product insight: Datalore
Blog|by Leanne Bevan|3 March 2023
This is our second data science JetBrains product insight blog in the series. This time we focus on Datalore and spoke to Alena Guzharina, Datalore Product Marketing Manager.
What is Datalore?
Datalore is a collaborative data science platform for teams. It streamlines insight delivery and helps data science and business teams be more productive together.
Datalore brings together:
- Powerful coding assistance for Python, SQL, R, and Scala in Jupyter notebooks.
- Data integrations for SQL databases and cloud storage systems.
- Modern business intelligence and interactive data apps.
- Real-time collaboration on code and in team workspaces.
Teams can use Datalore online in a managed cloud or host a private version on-premises.
Who is Datalore for?
On the one hand, Datalore is designed for data science teams who work with Python, SQL, and R and use Jupyter notebooks as part of their workflow. On the other hand, business teams that take data-driven decisions can benefit from using interactive reports and apps created in Datalore.
Why should they use Datalore?
Data Science Team Leads can boost the performance of their core data teams by bringing real-time collaboration, a first-class coding experience, and no-code automation to Jupyter notebooks. They can enable easy conversation with business stakeholders through the sharing of interactive data apps.
Solutions Architects, IT Directors, DevOps Managers can provide a reliable and scalable data science platform, one that fits their infrastructure architecture and security standards.
Business Leaders can get faster data insights, dive deep into existing reports, and perform ad-hoc analytics with SQL cells and no-code visualisations.
Do you have any use cases?
Datalore supports teams throughout the whole data science journey:
- Data retrieval with SQL database and S3 bucket integrations
- Data exploration, transformation, and visualisation with Python, SQL, R, Scala, and Kotlin.
- Real-time team collaboration on code and in shared workspaces.
- Model prototyping and training with powerful CPUs and GPUs.
- Insight sharing through interactive data apps.
What is your favourite Datalore feature and why?
My favourite Datalore feature is SQL database connections, which are available right in front of the Jupyter Notebook interface. I can connect to Snowflake, Redshift, PostgreSQL, and many other databases without writing a single line of code, browse the database schema and then enjoy SQL code completion when querying my data. Then I can get instant dataset statistics and visualisations, and seamlessly continue doing data exploration and visualisation with Python.
I love that my data retrieval and further analysis are kept in one place. It makes my work easy to explain and reproduce.
Do you have any Datalore tricks and tips to share?
If you want to customise a visualisation that you’ve created inside the Visualise tab, simply export it to code. I love that you can leverage the flexibility of Python while automating routine parts of EDA.
Do you have any resources that you recommend customers read/watch?
I recommend watching our Getting started with Datalore playlist, checking Datalore’s customer stories and subscribing to our blog updates. If you want to get a quick feeling of the Datalore editor, create a free Community account online to give it a try!
Find out more about Datalore pricing
Alena has provided a brilliant insight into Datalore.
If you'd like a Datalore free trial, demo, licensing advice, or have a question, please fill out the form below.
Grey Matter is a JetBrains Platinum Reseller.
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