The ease of switching between python and sql and publishing apps, how frequently they are launching new product features, and their customer support is fantastic!

If I had to nitpick, it's that they're an early product, so they haven't built out all the functionality that they want to. But they'll get there :)

For technical users, Hex is way easier to use and faster to produce results than the current big-name visualization tools. There are many use cases for Hex that have made my life easier. Also, customer support is quick to get back with potential solutions to problems, and they're eager for feedback on additional product updates. I've used Hex for about 1 year and have seen many great product update releases during that time!

I've used it for deep dive analyses, building quick tools for operation personnel, to create dashboards, and for ad-hoc requests.

We've been impressed by the balance Hex provides in offering the technical flexibility you’d want as a data scientist with low technical overhead for effortlessly publishing interactive apps. This makes it easy for us to go from prototype to deployment.

There's nothing really to dislike about Hex - we're mainly excited to see future iterations of some current features! For example, we'd love to see the extension of no-code tools (e.g. the chart editor for visualizations) to encompass code-free data processing as well. This would make Hex accessible to a larger fraction of our user base and enable more non-technical users to create and share analyses.

We've been able to develop interactive data apps to (1) provide code-free analysis dashboards, (2) automate data-driven workflows, and (3) track metrics for various teams and processes across our organization. Hex has been the unifying platform that has allowed us to create apps for all of these use cases.

Ability to collaborate with multiple people in real-time. A combination of SQL, Python, and Jinja in one environment makes for a very powerful ecosystem and allows us to provide much refined insights to our stakeholders.

Standard visualisation options are quite basic and require a lot of workarounds to make them look nicer. Can not import customer colour pallets.

The inability of authors to save a data source connection that they can import into a new project.

Collaboration between different team members in the analytics team. Increased transparency in terms of insights being delivered and the version-controlled nature of SQL scripts powering those insights. Better experience for stakeholders while engaging with data team.

Hex was extremely welcoming. It has phenomenal defaults, but also lets you use more nuanced and advanced tools if you'd like. I was able to make a very presentable notebook on my first go, and I've never even used Jupyter before! I think tools like this, that break down walls for highly technical people to communicate with non-technical folks, are extremely important.

Hex has an opinionated design. I think this is a really good thing! But there were a few times I wanted slightly more flexibility than was provided. I'm sure that'll come as the platform matures though, and would never hold me back from recommending Hex to another analyst.

I've only used Hex for a side project, specifically to analyze some data related to the New York Times Spelling Bee game. It was very easy to share this with folks on social media.

1) The ability to move between SQL and Python. SQL query outputs are stored as dataframes, which can be manipulated in Python or queried via SQL. This allows for incredibly easy and powerful exploratory data analysis, and after completing EDA it's dead simple to build a web-app for viewers with only relevant visualizations and tables.

2) The flexibility of Hex notebooks. We began using Hex for EDA, but quickly found use cases outside of that where Hex truly thrives. Recently, we've been able to use Hex to easily build QA tools comparing data obtained from our DBs as well directly from APIs (using the python requests package, which comes installed with Hex).

The standard visualizations are a bit limited, but this is not a large issue as our team uses primarily open source Python or R packages.

We originally had concerns Hex wouldn't meet our basic BI and dashboarding needs, but it is a fantastic tool for both EDA and building long-term dashboards.

We started using Hex only for exploratory data analysis, but quickly expanded beyond that use case. We now have migrated most of our dashboards away from Tableau into Hex, and have even built QA tools for our operations team powered by Hex. The flexibility of Hex allows us to build a variety of analytical tools for our internal teams. It's become an indispensable tool in our data team's arsenal.

Hex serves as a robust workbench for all parts of the data science process. Exploration of data and communication of insights are made frictionless through Hex's many features, like in-notebook SQL, an intuitive app builder, sharing, scheduled execution, and more.

Other BI tools focused on the no-code data visualization experience, and many do it quite well. Hex isn't quite there with their no-code visualization feature. but will be able to catch up rapidly.

We're building ML models, pulling ad-hoc reports for business users, creating mission-critical dashboards, and performing data exploration. Though we've been able to do this without Hex, the ability to do it all within one tool makes it easier than ever to provide value to the business through data.

1. It is so easy to set up and get started. If you especially have a smaller team, Hex is great because you don't have to think about maintaining anything from the infrastructure standpoint.

2. Hex makes it so easy to share your work with your stakeholders, set up scheduled runs, and build filters so you don't have to duplicate your code for similar requests.

3. Building reports/dashboards/apps on Hex has been super easy. They adopted Jupyter-style notebooks for their development environment -- it makes it super easy to get started if you ever used Jupyter, and you can use SQL and Python together without dealing with writing wrappers for your SQL in Python.

The organization of the queries/reports could definitely be better as there are just tags for now for you to organize them. However, this is not a pain for us as the # of queries we have is not that large.

We are using hex to help our stakeholders keep track of KPIs that they are interested in. Our organization has definitely become more data-aware since we adopted Hex as it makes it so easy for the data team to build dashboards/apps and share them with the team.

Hex's notebook is miles ahead of other products out there and has everything you need for running an analysis. Absolutely love the fact that you can move between SQL and Python so seamlessly. Writing SQL against dataframes and Python against query outputs is just so magical. Passing variables from the front end "app" to the backend notebook has been extremely valuable too for so many use cases. The Git integration brings a lot to the table, allowing our team to back up our code and also run code reviews before moving dev work to production.

In addition to a high-caliber product, the Hex team is innovative, responsive, and consistently (and rapidly) enhancing their product.

Updated this because what I wrote previously is no longer valid with the release of new features.

Hex is an awesome tool, but if I had to pick something is that the out of box charting is kind of lacking. Ive tried to use it a couple of times but then ended up writing Python.

Set up a trial! Best way to see if its the right tool for your team.

So far, we have mainly used Hex for all of our more complex, ad-hoc analysis which involved using Python/R for data modeling & visualizations. Through this analysis, we have better understood gaps in our day-to-day care center operations and found actionable insights that will lead to more efficiency and a better experience for our members.

There are many things I like about the tool:

- Clean UX and easy to navigate

- Environments are easy to maintain and spin up

- Python to SQL (vice-versa) has super easy handoff

- Sharing capabilities are amazing, charts or scripts

- Graph view is really handy in knowing which Cell links to which

- Building quick scripted apps is super easy

- Scheduling apps is also really easy

Overall the tool is fantastic, something that they're actively working on are:

- Improving charts and filters/sorting

- Better connection with GitHub would be nice, just to see exact changes in GitHub. To be fair, there is already good version control, so you don't lose any changes but a way to see it in GitHub would be nice

Hex Tech team is actively working on a ton of new features, which is amazing! Soon to be the best tool in the data world (if it's not already)

Since we're just getting started with our data team, it's best to use a tool like Hex which can span across multiple functions. It can allow us to do the extraction, transformation, and loading of data, and helps with visuals as well. This is a perfect tool for our small team.