Keep up to date with what's new
Two major industry-wide trends affected data teams in 2023: the tech downturn and the rise of LLM's. We take a look at these and how it affects the Modern Data Stack and the current state of data analytics.
Apache Arrow has allowed our engineers to save time by leveraging existing solutions to common data problems, freeing us up to work on harder problems that require novel solutions.
In this guide, we'll set up a live dashboard using Hashboard, leveraging GitHub's REST API, GitHub Actions, and Hashboard itself. By the end, you'll have a comprehensive view of your repository's activity, with tools for detailed analysis and hourly refreshed data.
Learn how Pawp, an app-based subscription veterinarian service, uses Hashboard to empower their entire team to self-serve data and analytics.
Implementing row- and column-level security at the database layer allows you to enforce these rules in a business intelligence tool as well as other tools that rely on the data warehouse. We’ll be showing an example of how to enforce database-level permissions using Amazon Redshift and how you can use it to enforce security and protect PII in a business intelligence tool– in our case, Hashboard.
Building data applications does not have to be a slog. Modern tooling enables you to create lightweight applications that process and respond to large amounts of data and require minimal maintenance, especially when you want to be on top of the latest snowfall this ski season!
A step by step guide of how to use Hashboard for interactive product marketing. Create interactive, shareable dashboards with your own data!
We’re excited to announce the Hashboard integration withMotherDuck and give a quick walkthrough of how it helps Hashboard build on our DuckDB use cases and examples. We love using DuckDB for our demos and MotherDuck has made the developer experience much better (and helps us scale our DuckDB use cases to much more data).
Sharing our learnings from our AI assistant feature - how we developed it, what users actually did and what's next.
What we can learn from historical data problems and our modern day solutions.
Somehow you got tasked with building the dashboard to track [ fill in the blank ]. It turns out, there’s a lot of disparate skills involved in making a BI dashboard, not just data engineering skills. Sure, you’ll need some data manipulation skills, but you’ll also need visualization skills, analytical skills and product skills to make a useful dashboard people will actually use.
How Beam used Hashboard to help distribute millions of dollars in aid and serve 60+ customers
Business Intelligence demos are hard to make reproducible because they live at the end of a long pipeline of tools and processes. Here's a guide to making reproducible and extendable BI examples with Hashboard, DuckDB and dbt.
Glean.io is now Hashboard - and a huge v1.0 release!
Leveraging DataOps for an orderly, collaborative data culture
Why you should pick Hashboard, Looker, Metabase, or Tableau based on self service features and pricing.
Timing will never be perfect for introducing a new tool to your stack. If you're considering the addition of a data viz tool, this post will provide guidance on identifying key signs that indicate it's probably time to take the plunge.
We're building Hashboard with the upmost care and consideration for our users' security and privacy. Rest easy knowing that we're SOCII certified, HIPAA compliant and more.
My journey of how I've ended up embracing denormalized tables, how to use tools like dbt to bridge normalized and denormalized tables, and how denormalized data accelerates exploratory data analysis and self service analytics.
It comes in as a simple request: “we want custom colors for our charts in Hashboard”. It seems simple, but doing it well is more nuanced than you may expect.
It’s surprisingly common to not have any version control for BI assets. If you don’t have it, it’s a good idea to get it in place sooner rather than later. This post covers the basics of how to get started.
Big Data is cool - and so are infinitely scalable Data Warehouses. But sometimes, you just have not-so-big data. Or maybe you have a csv file and you don’t even know what a Data Warehouse is, or don’t care about the “Modern Data Stack” - like, what is that? That shouldn’t stop you from exploring your data in an intuitive, visual way in Hashboard.
We’re thrilled to announce the launch of our public Changelog and Product Roadmap! These two resources will provide an updated overview of all product changes, as well as a preview of items our team will be tackling in the future.
Sometimes you've got some data in postgres and you just want to start analyzing it. Here's the scrappy guide to get you jamming on analytics - a guide for founders, PM’s, engineers trying to hack something together quickly.
Allowing users to explore and experiment with your data is crucial for building a data-driven culture. But when a report has become a production system – a real product with real users that depend on it – it’s important to start treating it more like an application. DataOps lets you treat them that way.
It’s never been easier to collect data and drop it in a database so you can analyze it. But what about getting to insights? Data visualization and reporting are hard - we're trying to make it easier.