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2021 Roundup: The Top 5 Must-Read Blogs on the Modern Data Stack

https://ift.tt/3EBqVt6 A curated list of the year’s best articles from the data world Photo by Claudia Wolff on  Unsplash For the mode...

https://ift.tt/3EBqVt6

A curated list of the year’s best articles from the data world

Photo by Claudia Wolff on Unsplash

For the modern data stack world, this year has been a series of new companies entering the space, funding announcements, some wars, and lots of fun data memes.

Can we call this the year when the “modern data stack” finally became mainstream? Well, only time will tell… But there’s definitely a lot happening in this space — new job titles, frameworks, tools, and predictions for the future.

It can be hard to catch up on everything, especially if you’re just starting out. So I created a list of my favorite blogs from the year, along with some follow-up reading, to help you stay updated on this year’s emerging ideas around the modern data stack.

1. We the purple people (Anna Filippova)

“A common career path for purple people can look like jumping around between what are on the surface very different roles — some flavor of analytics, data science, data engineering, operations, people management (and many more!). Each iteration builds a new and different kind of empathy for the problems at hand. Helping purple people grow in their careers is, therefore, less about gaining a predefined set of skills and more about growing the scope of their impact on the business and on others around them.
In the coming years we will see more and more examples of purple people. You will know them by titles like ‘Analytics Engineer’, ‘Operations Analyst’… or some combination of business function + ‘Analytics/Analyst’ that doesn’t yet exist but soon will.”

Read the full blog here.

Want to learn more? Check out this follow-up reading:

2. Run your data team like a product team (Emilie Schario and Taylor A. Murphy, PhD)

“Most data teams aren’t set up for success. For many years, data teams have been buried in the IT function. As IT functions, those data teams handled getting data out of their systems and presenting them to the stakeholder as CSVs from which the stakeholders could work their magic and come up with conclusions.
… When a data team emerges in a company as an afterthought, they often end up being built like service-based departments with a ‘submit a ticket with a question, get a very specific answer’ mindset. Data folks who are bound to this model rarely spend time being proactive. Without intentional space, they are unlikely to be anything more than ticket closers.”

Read the full blog here.

Here’s some follow-up reading on structuring your data teams and roles:

3. It’s time for the modern data culture stack (by me!)

“In the past four years, the modern data stack has made a ton of progress, and it’s gone mainstream thanks to the adoption of tools like Snowflake and dbt. Gaps in the modern data stack that were there as early last year (in areas like metadata management, data governance, and observability) are quickly being filled thanks to the advent of newer tools. With so much innovation in the space, I’m certain that in the next few years, all data teams will finally have a close to ‘perfect’ data stack.
This makes me believe that, as we enter 2022, the conversation needs to shift from the need for better tooling to the next ‘delta’ that will finally help us create dream data teams — the modern data culture stack. These are the best practices, values, and cultural rituals that will help us diverse humans of data (or the ‘purple people’ as dbt coined) come together and collaborate effectively.”

Read the full blog here.

Here’s some follow-up reading on building better data teams:

4. The modern data experience (Benn Stancil)

“…the modern data stack isn’t an architecture diagram or a gratuitous think piece on Substack or a fight on Twitter. It’s an experience — and often, it’s not a great one. It’s trying to figure out why growth is slowing before tomorrow’s board meeting; it’s getting everyone to agree to the quarterly revenue numbers when different tools and dashboards say different things; it’s sharing product usage data with a customer and them telling you their active user list somehow includes people who left the company six months ago; it’s an angry Slack message from the CEO saying their daily progress report is broken again.”

Read the full blog here.

Here’s some follow-up reading on how the modern data stack actually works:

5. Bring data analyst to the table (Petr Zanda)

“We shouldn’t hire data analysts to write SQL queries and churn out dashboards and spreadsheets. We should employ analysts to analyse and help us understand business problems using data.
Finding the correct data and putting it together is necessary, but there’s much more to do than that, and analysts are uniquely equipped to follow through.
Besides excellent data skills, the best analysts I know have a far more critical trait — a relentless curiosity that drives them forward to keep exploring.”

Read the full blog here.

Here’s some follow-up reading on the new role of data analysts in modern companies:

✨ Special picks ✨

If you’re like me and spend your downtime catching up on data reading for the year, here are a few more reads that I highly recommend.

Want to chat about building your own modern data stack? Reach out to Prukalpa or the team at Atlan.


2021 Roundup: The Top 5 Must-Read Blogs on the Modern Data Stack was originally published in Towards Data Science on Medium, where people are continuing the conversation by highlighting and responding to this story.



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