Many companies use Microsoft’s Power BI tool as their internal dashboard to communicate with data, most likely because they have aligned their techstack to Office rather than Google. And while it’s relatively simple to connect Power BI to a data warehouse or Salesforce, connecting to social media data is difficult. In this post I want to show you how I solved the problem.
Power BI did have a native connector to Facebook, but that has been decpreciated since April 2020 — as such you need an intermediate party to pass data between the two.
The first step is to get…
Many of us who work with data are responsible for the technical aspects of collecting and preparing data for others to use — whether that’s connecting tools together to pass data into a warehouse/ CDP or maintaining databases and pushing data into BI dashboards.
And even though these tasks often involve a high degree of complexity to ensure the smooth flow of data and accuracy of the metrics, sometimes that’s where our understanding of the data stops.
We know how the SQL code accesses the CRM database and exports a table that a stakeholder is requesting, or we know that…
Suppose you’ve started a new job — or maybe acquired a new client — and you are responsible for (1) helping them to get the most out of the data they have and, (2) making recommendations to improve their data capabilities. There are many unknowns when stepping into such a role:
All of which can be challenging to tackle head on. Where do you start? Do you start upgrading…
I’ve been using Python’s pandas library to summarise large datasets. And while it can easily summarise the data, I am missing totals in my tables. The totals are useful when examining the data to understand what proportion each split of the data represents.
For example, consider this output:
What if I want to see the totals for each item in ‘food’, each item in ‘name’ and each item in ‘city’? The pivot table does not include these, so we have to add them ourselves.
In this post I’ll show you how I managed to add subtotals.
Here’s my very small…
Ever since the world realised the value of data to help make better decisions, we’ve seeked out more and more of it — in the naive view that more data = better decisions (as less of our rationale is based on opinion).
And while the number of data sources continues to grow, and we build data pipelines, lakes, warehouses and automated tracking, we’ve increasingly found ourselves in a predicament of not being able to extract as much value as we thought we could from it all.
Simply put, having more data does not result in better decisions.
In this post I want to show you how I have been able to draw custom shapes in Google Slides to use with plotting data on maps. I probably could have used a Python or R library or even Data Studio, but some of the problems I run into with those approaches include:
In the past decade or so, ‘data’ has emerged from its origins in areas considered logical, numerical and rational like economics, finance, statistics and science; and has been rapidly making inroads into subjects normally based on expertise, experience and evaluation.
Algorithms work behind the scenes to influence relationships in the likes of Facebook and Tinder.
Econometric models are being applied in sports: Moneyball introduced sabermetrics to the general population, and here in Australia it’s been applied to the AFL, especially helping the Sydney Swans win the Grand Final in 2005.
Scientific research has been used to determine the best way…
Advertising finds itself in a tenacious spot these days serving two masters: creativity and data.
On the one hand, it values creativity; and it’s not hard to understand why. Creativity helps make brands distinct from each other and meaningful to consumers, it wins awards and improves recognition of the brands, agencies and people involved. And according to Hurman (2016) — who analysed three decades of data — more creative advertising is more effective advertising, driving sales and revenue.
On the other hand, we are seeing the rise and rise of data. From its beginnings in advertising as post-campaign performance measurement…
I’ve worked as a data specialist in a few advertising agencies over the past 5 years now and I’ve encountered a pattern of behaviour in strategists and creatives alike when it comes to using data in their decision making process. This might resonate with you if you work with data in an agency (and maybe similar client-side).
The team have bought into the value data provides and are eager to see how it can shape their strategic and creative decisions. They hire a data specialist, invite them to meetings and planning sessions and request a data extract from all the…
In my last post, I spoke about the research mindset a data scientist should have to avoid jumping into the data as soon as a problem is raised. Instead, it is better to spend some time understanding the question behind the problem so the data you collect and analyse is actually relevant to the problem at hand.
In this post I want to discuss how I handle that step of moving from problem to question — that is, how I figure out what the real issue is when a manager is jumping up and down because sales have dropped. Using…
All things data