Dashboards have been the primary weapon of choice for distributing data over the last few decades, but they aren’t the end of the story. To increasingly democratize access to data we need to think again, and the answer may be closer than you think…!

Hello Dashboard, my old friend

When I started my career, I was working in a large tech manufacturing company. The company had just purchased its first dashboarding tool and our team was responsible for the exciting transition from tired spreadsheets and SSRS reports to shiny, new dashboards.

The jump from spreadsheet to dashboard was a significant leap forward in analytical maturity…


The tools analysts use today were all built for a particular purpose at a particular time. But these same tools are holding us back. Now is the ideal time to step back and see what of these legacy tools we carry with us, and what we leave behind.

The Life of an Analyst

Given the demand for analytical insights is at an all-time high, it’s amazing to think the analyst’s workflow has been virtually unchanged for over a decade.

And while there’s certainly been progress to make individual tasks easier, the workflow often remains a patchwork of hackneyed software held together with CSV files and…


And keep the pirates at bay

Photo by Austin Neill on Unsplash

Beware of Pirates

One of the most universally demoralizing experiences is to see the results of your hard work go unseen, unappreciated, and unused. In the world of data that is something we experience all too often. Take the following hypothetical situation:

  1. Jim submits a request to the data team for a deep-dive analysis for a client presentation the following week.
  2. You and Jim spend all week working on the analysis, working closely to make sure he has the right visuals and feels confident presenting the findings.
  3. The day of the presentation arrives, and not a word from Jim. That’s odd.
  4. When you…


A simple solution with “big” results.

The BigQuery Dilemna

BigQuery is one of the most popular data warehouses in the market today, but if you aren’t careful you can easily rack up a debilitating bill. If BigQuery powers your analytics stack then partitioned tables can be a no-brainer solution to keeping costs down.

What are Partitioned Tables?

Partitioned tables are tables that are, erm, partitioned into smaller tables, usually by date.

Example of tennis data partitioned by year of match. (image by author)

Partitioned tables are not unique to BigQuery. They most commonly appear as those notorious tables with long suffixes (e.g. sessions_2017_01_01, sessions_2017_01_02). …


How to introduce BI notebooks into your organization.

This is article 4 of our “call for better analytical tools” series:

Notebooks are powerful tools with multiple use cases. But what’s the best way to bring them into your organization? Where can they have the biggest impact? …


To make better decisions, we need data tools that communicate more than just numbers.

With all the hype around data, it can be easy to forget that data is about making better decisions.

Building a data-driven organization is no easy task. There’s no shortage of products or theories promising us faster insights and more powerful analytics. But if our goal is to use this data to make better decisions, then there’s something else we need.

Stripping it back

While there have been many decision-making frameworks to make the rounds over the years (e.g. MDMP [1], Cynefin [2]), they all follow basically the same pattern:

Problem definition + Facts + Interpretation + Evaluation = Action

The key steps of decision-making

Here’s a quick…


How to do Advanced Data Cleaning in SQL

Introduction

Once I heard you could request all your personal data from Netflix , I was excited to dig in to see what I could find. In the end I not only learned a lot about myself — like which season of Friends I watch the most (Season 6) — but it was also a great opportunity to put BigQuery’s analytical capabilities to the test. This article covers how I did the most complex transformations in BigQuery, but you can find the full project here:

Why BigQuery?

Perhaps the obvious question is why I chose to do this analysis in BigQuery when I…


Photo by NESA by Makers on Unsplash

“Through 2022, only 20% of analytic insights will deliver business outcomes.” — Gartner [1]

Data has made a home between worlds. Most frequently, data teams are wedged between the technical side of the business, and the operational side. And while often that can make us feel like misfits, it actually puts us in an incredible position to leverage the best of these worlds in our own domain.

Over the last 2 years, I’ve worked in a small start-up, and spent all day physically and metaphorically sandwiched between our development team and our operations team. As the sole data person, I…


and the data democracy hierarchy of needs

Photo by Chris Liverani on Unsplash

TL;DR

Building a data democracy is difficult, but not impossible. No tool can fix things like culture or create processes for you, but how well any tool integrates with these parts of your business can make the difference between making your data democracy a new reality, or just a failed experiment.

Data has a knack for dividing opinions and preferences, but there is one thing we all seem to want: a data democracy. Whether you’re an analyst, a CEO, or a business user, the idea of bringing the ‘power [of data] to the people’ is downright captivating.

And yet very few…


A quick intro to window functions and a very real look at how much Netflix I actually watch. 🙈

If you’re anything like me, you’ve found yourself watching a lot more Netflix these days. And if you’re even more like me, you’ve been dying to get your hands on some data to prove it.

Luckily, you can download your own viewing history from Netflix, and have a data party all on your own! 🥳

Even more good news: this turns out to be an excellent example of how to take advantage of the powerful and elusive window function. This family of functions is often considered ‘advanced’ SQL, and therefore, not as commonly used as they should be.

In the…

Taylor Brownlow

Head of Data @ Count (https://count.co)

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