Data-led Academy is here — a place to learn how to work with data
Read on to know why I built it and what’s in it for you
2022 Update: DLA has been acquired by Amplitude!
What started about a year ago as a side project to share what I had learned has become a full-time endeavor for me — one that I have been enjoying more than anything else I have worked on before.
Data-led Academy (DLA) is a place to learn how to work with data and get expert answers to questions about data tools and technologies.
What’s the need?
The data space is fascinating and there is so much to learn. But at the same time, the space is evolving at a rapid pace, and keeping up is hard for anyone who is not deeply embedded in the data communities or spends a significant chunk of their time to stay on top of everything new.
DLA aims to solve that by making it really easy to keep pace with the innovation happening in the data technology industry and find the right tool or set of tools to solve a problem. Currently, you can find straightforward answers to these 4 questions about a data product:
- What need does the product fulfill?
- What are its benefits?
- What are its core features?
- Which teams does it cater to?
Additionally, you can find answers to common questions about the product or the category it operates in. The answers are provided by the product companies as well as practitioners who have a deep understanding of specific tools and technologies.
Moreover, we try our best to remove bias from the answers to ensure they are purely educational in nature. And I strongly believe that getting expert, unbiased, and actionable answers to questions is one of the best ways to learn about technology (and maybe everything else too).
Our long-term vision is to offer the largest data knowledge base comprising expert, unbiased answers to questions about tools, technologies, people, and processes related to data.
What can you do on Data-led Academy?
Here’s what you can do right away:
- Explore data tools based on the data pipeline stage they solve for — Collection, Warehousing, Analysis, Activation, and Integration
- Explore emerging data technologies/categories
- Understand quickly what exactly a tool does and the need it fulfills
- Learn via actionable Guides like this or straightforward Answers like this
- Share your knowledge in the form of Answers or Guides if you’re a data practitioner
- Get your company profile up if you represent a data product company
Going forward, you’ll be able to find answers to more specific questions about data.
What’s in it for data practitioners?
DLA is a place for data practitioners to share their knowledge, exhibit their expertise, and gain visibility in the data space.
As Data-led experts, they can be found by folks looking for help implementing data tools or by companies looking to onboard channel partners. Experts will soon be able to showcase their projects, list their service offerings, and let people subscribe to their newsletters.
However, none of this is groundbreaking and the question remains why a practitioner should contribute to DLA.
Here’s why:
I’ve answered a few hundred questions about tools and technologies in a bunch of Slack communities and I continue to do so because I really enjoy it. But I find myself answering the same questions over and over again with no easy way to refer to my past answers. Moreover, I’ve got nothing to show for all the time I’ve spent providing expert answers to people’s questions.
DLA aims to fix this by enabling experts to publish short, unbiased answers to common questions they encounter and build a portfolio in the process.
If you’d like to join as an expert, get started here.
What’s in it for data product companies?
DLA offers data product companies a place to build community presence and the tools to engage with prospects, partners, and customers via education.
One can learn a lot about the data landscape by discovering the problems data companies are solving and by understanding the solutions to those problems.
On the other hand, for data companies, the best form of marketing is to create and contextually distribute educational content about the problems their products solve (I wrote about this recently).
It’s worth highlighting that while a majority of data companies sell to data teams, stakeholders from other teams are almost always involved in the buying decision — data companies ought to make sure that those stakeholders understand the need their products solve.
I’ve been a buyer of data technology and have experienced first-hand how difficult it is to get buy-in from executive teams when they don’t fully understand the need that a product fulfills.
The data tools directory now lives on https://tools.databeats.community
Wish to contribute to the community?
You can submit original content, be a guest or a host on the show, or share a playlist with the community 👉Let us know
