Newsletter (85)
Newsletter Analytics is as much about persuasion as it is truth-seeking
Not all analytics is truth-seeking; much of it is persuasion, and that changes what we should expect from BI tools and governed data layers.
Business Intelligence Vibecoding Analytics: Three Observations on Agentic Analytics
More and more people are starting to vibecode analytics, and we're seeing it at Holistics too. There are the obvious effects, but the second-order effects of AI are probably much more interesting.
Business Intelligence Slice n' Dice: A Self-Service Story
We explain the what and why of self-service analytics through a story of a fictional pizza restaurant.
Business Intelligence The 4 Types of Data Scales
Numbers aren't all created equal; they fall into four distinct categories known as data scales. Understanding this, you'll learn how to handle each type correctly to make your data work for you.
Designing Data Organizations An Interview with Christine Jiang, former Director of Core Analytics at Vimeo
For this week’s episode of Designing Data Organizations, we spoke with Christine Jiang, former Director of Core Analytics at Vimeo, who was with the organization between 2020 and 2024.
Designing Data Organizations An Interview with Michael Perlis, Director of Business Intelligence at ZoomInfo
Designing Data Organizations is brought to you by Holistics, where we delve into the intricate process of creating and optimizing data teams within organizations.
Data Modeling The Three Types of Fact Tables
A concise tour of one of the basic components of Kimball dimensional data modeling. We explore the three types of fact tables, and then analyze why they have lasted the test of time.
Designing Data Organizations An Interview with Nachiket Mehta, Head of Data and Analytics Engineering at Wayfair
Designing Data Organizations is brought to you by Holistics, where we delve into the intricate process of creating and optimizing data teams within organizations.
Business Intelligence 4 levels of Analytics-as-Code
How did Analytics-as-Code evolve? We explain the history behind the movement, and present the 4 levels of analytics as code over the years.
Designing Data Organizations An Interview with Hannes Felsberg, Group Lead Data at Trade Republic
Designing Data Organizations is brought to you by Holistics, where we delve into the intricate process of creating and optimizing data teams within organizations.
Business Intelligence Death to Dashboards, Really?
Are dashboards really 'dead'? A response to a vendor trend that seems rather premature.
Business Intelligence The Emotional Needs of Dashboarding
Treating your dashboards like a product means thinking about ALL of your user's needs — rational or otherwise.
Business Intelligence Nailing An Analytics Interview Case Study: 10 Practical Strategies
10 practical tips/strategies I extracted myself when doing analytics case study as part of job interview process.
Business Intelligence The Two Forms of Metrics: Interval vs Point
In actual business conversations, the metric's form is sometimes ignored and implicitly understood. Understanding this concept gives you much better clarity in dealing with metrics.
Business Intelligence The skills chasm of the data analyst career
Why are so few data analysts get good at business problem-solving?
Business Intelligence Data Careers: Dealing With Being in a Cost Center
Building a career in data often means building a career in a business cost center. This isn't necessarily bad. Here's how to think about it.
Business Intelligence LLM Is Not Enough (For Self-Service Analytics)
Business Intelligence How Would An Ideal Semantic Layer Look Like?
How would an ideal semantic layer look like?
Business Intelligence How to run a Data Clinic (aka Data Office Hours)
Data clinic is one of many ways you create value and drive your organization toward better data literacy. Here's how.
Business Intelligence Data analysts, think about your work from the business stakeholders perspective
What actual values do business stakeholders get from data analysts?
Business Intelligence The Misleading Data Analyst Job Title (and Career Ladder)
Investment analyst is an entry-level investment position. So is data analyst an entry-level data position, too?
Business Intelligence Business Metrics vs Customer Metrics
What happened to us; and the subtle difference between customer-centric metrics vs business-centric metrics.
Business Intelligence The Silos between Data Analysts and Data Engineers
The silos between Data Engineers and Data Analysts.
Business Intelligence The Silos of Data Organization: Data Analysts vs Business Users
Why the Data Org doesn't work well with each other, the arc of data adoption and defining data stack as code.
Business Intelligence The Goldilocks Rule of Getting Data Driven
The goldilocks rule of being data-driven, why Data Teams should run like Product Teams, and what to do if your non-data friends ask you how to get into data.
Business Intelligence Analytics as Code
A short story about my history with programmatic configuration (or lack thereof) and how it's related to analytics.
Business Intelligence The Tension Between Ad-Hoc Queries and The Work
How do you balance between ad-hoc queries that may change your business and the mundane reality of day-to-day operational analytics?
Business Intelligence The Activity Schema is Worth a Look
The first data modeling approach since Kimball worth paying attention to.
Business Intelligence What is an OLAP Cube? An Exhaustive Explainer
The definitive explainer for OLAP cubes, where we cover every single possible definition for the phrase.
Data Modeling A 2020 Reader's Guide to The Data Warehouse Toolkit
Ralph Kimball's classic book The Data Warehouse Toolkit introduce the world to the practice of data modeling. Here's how to read it in 2022.
Business Intelligence Read Data Research Papers
A hack for when you don't understand data jargon.
Business Intelligence Induction, Deduction ... Abduction?
An unrigorous form of thinking you might encounter in your work with data.
Business Intelligence The Six Ways People Deflect Inconvenient Data
We take a look at an exhaustive list of reasons people give when they want to ignore anomalous data.
Business Intelligence Fitting Into Your Company's Learning Cadence
How a data person might fit into your company's learning cadence, and what that means for company performance.
Business Intelligence Self Service Business Intelligence is a Business Outcome
Defining what self service analytics is, by looking at what it isn't.
Business Fundamentals The Intuition Behind The Rule of 40
The origins and intuition behind a famous SaaS business metric.
Business Intelligence Actual Self Serve in Business Intelligence
We're back! Also: what does self-service mean, anyway?
Business Intelligence Obsess Over Controllable Input Metrics
Why Amazon's notion of measuring controllable input metrics is a lot more profound than you might think.
Business Intelligence This is How Amazon Measures Itself
How Amazon uses metrics. A summary of chapter 6 of Working Backwards, the first book to explain how Amazon really works.
Business Intelligence Simple Data People Tricks
Simple data people tricks, a hierarchy of feature stores, and Shreyas Doshi on product metrics.
Business Intelligence How Amazon Uses Input Metrics
How Amazon uses input metrics, a data pipeline is a materialized view, and the case against self-service data and analytics.
Business Intelligence Snowflake and the Data Lakehouse
A quick look at what Snowflake's been up to re: the Data Lakehouse, an inside look at Amazon's data-driven decision making, and how Airbnb customized Superset to fit their needs.
Business Intelligence The Data Lakehouse is a Thing
The data lakehouse is a thing, Superset is also a thing, and how to make dashboards using a product thinking approach.
Business Intelligence So You Want To Find an Analytics Engineering Job?
Looking for an analytics engineering job in your locale? Read this.
Business Intelligence What We Know and Don't Know About Analytics Engineering
Everything we know and don't yet know about the emerging role of analytics engineering.
Business Intelligence Three Data Industry Questions We're Investigating For The New Year
Three changes in the data landscape we're investigating over the next few months.
Business Intelligence Five Things We're Pretty Sure About
Five quick things we know to be true, written for the end of the year.
Business Intelligence Embrace The Data Schlep First
Every cool data project has some schlep up front. Here's why it's a good idea to keep that in mind.
Data Modeling Applying The Principles of Agile to Data Modeling
In our third and final part on Agile Data Warehouse, we take a look at the origins of the Agile Manifesto, from which Corr and Stagnitto took inspiration.
Business Intelligence A Business Process Worth Measuring
The second part of our series on Agile Data Warehouse Design, a 2011 attempt at applying the principles of agile to the practice of data modeling.
Data Modeling First Impressions from Agile Data Warehouse Design
Agile Data Warehouse Design is a 2011 attempt at applying the principles of agile to the practice of data modeling. This is the first post in a series on the ideas from the book.
Business Intelligence The Evolution of the BI Market
Instead of an article this week, I thought to share something in a different medium instead.
Business Intelligence The Four Flavors of Goodhart's Law
Goodhart's law says that 'when a measure becomes a target, it fails to become a good measure. Here are four ways that occurs.
Business Intelligence A Short Story About SQL’s Biggest Rival
A short story about SQL's better rival: Michael Stonebraker's storied query language, QUEL.
Business Intelligence Top 5 Data Books To Read in 2020
Stuck at home during the pandemic? We give you Holistics's top five data books to read in 2020.
Business Intelligence Why is Data Analytics So Far Behind Software Engineering?
Why does data analytics and business intelligence lag behind the best practices and tooling of software? Two anecdotes and a theory.
Business Intelligence Business Intelligence Lessons from Softwar: A Portrait of Larry Ellison And Oracle
What we can learn from Softwar, a book about Larry Ellison's attempt to take over the enterprise software world.
Business Intelligence Redshift, Snowflake, and the Two Philosophies of Cost
What intermix.io's forced acquisition tells us about the two philosophies of cost in data analytics.
Business Intelligence A Dive Into Metadata Hubs
A look into metadata hubs, which might just be the hottest category of data tools of the past two years.
Business Intelligence Measuring a Company When a Company Is Mature
We take a look at the business fundamentals of the operations stage — the last of three stages in a company's life.
Business Intelligence Understanding the Scale Stage
The scale stage is the second of three stages in a startup's life. In this post, we discuss what product-market fit means, and then we look at healthy growth (the kind that leads to winning) and unhealthy growth (the kind that leads to company death).
Business Intelligence Measurement Before Product Market Fit
A startup's first job is to create a customer. We take a closer look at how that affects the metrics you measure at the product stage of a startup's lifecycle.
Business Intelligence How Metrics Change When Your Company Grows
When your company grows, the metrics that matter changes along with it. Here's a look at the three growth stages of every company, along with the metrics that matter most at each stage.
Business Intelligence The Magic Money Machine Model
One way to get better at business communication is to learn the fundamentals of business. We explain Return on Invested Capital from first principles, written with the data analyst in mind.
Business Intelligence Clearer Communication: How To Use The Ladder of Inference When Communicating Data To Your Business Users
If you work in data analytics, communicating complex information is just part of your job. Here's how to use the Ladder of Inference to get better at it.
Business Intelligence Data Quality from First Principles
Why data quality is an ongoing, people, process, and tools problem, and how to think about getting better at it.
Business Intelligence The Data Modeling Layer
While writing The Analytics Setup Guidebook, we realized that the tools we recommend (apart from Holistics!) were really drawn from a small handful of ideas.
Data Modeling Slowly Changing Dimensions (SCDs) In The Age of The Cloud Data Warehouse
What a new approach to slowly changing dimensions tell us about the future of dimensional data modeling.
Business Intelligence When Doing Digital Transformation, Think Capabilities, Not Maturity
Why maturity models can be a bad idea, and why using a capability model is a better idea for digital transformation.
Business Intelligence How to Measure Software Development, from ‘Accelerate: The Science of Lean Software and DevOps’
Tracking the performance of your software development team is really, really difficult. The 2018 book Accelerate: The Science of Lean Software and DevOps gives us a fantastic way to measure just that. Here's how.
Business Intelligence Why Measuring Cash Flow is More Important Than Measuring Profitability
Why your CEO is so obsessed with cash flow metrics, and what you can do to help as an analytics person in your company.
Business Intelligence The Two Philosophies of Cost in Data Analytics
There appears to be two philosophies today when it comes to managing costs in a modern data stack. We explore what they are.
Business Intelligence Developing an Intuitive Understanding of the SaaS Quick Ratio
An explanation of the SaaS Quick Ratio that focuses on the intuition behind the metric. Written with the data analyst in mind.
Business Intelligence OLAP != OLAP Cube
There's a tendency for people to conflate OLAP with OLAP cube. We take a quick look at how this happens, why it shouldn't, and why it matters if you're a data practitioner.
Business Intelligence The Rise and Fall of the OLAP Cube
A definitive history of the rise of the OLAP cube, how it's affected our industry, and what comes after.
Business Intelligence The Dark Side of Digital Transformation
This week's post comes from Holistics team member Yahya Apristianto, who wrote it after attending a talk on digital transformation by a CEO in his home base of Indonesia.
Business Intelligence How We Combine Data Sources at Holistics
Good data teams combine data from different sources in order to do their jobs well. Here's what we've learnt while putting this into practice at Holistics.
Business Intelligence Judge Your Company: Using The Three Levels of Data Analysis For Data Career Decision-Making
Data team careers are different from equivalent careers in software engineering, product management, or UI design. Here's how to evaluate prospective employers as part of your data career.
Business Intelligence Why Google Analytics sucks and what you can do about it
Google Analytics is an incredible tool to have in your toolbox. But it only offers aggregated data, which limits your ability to track visitor behavior. In this post, we discuss a simple, affordable alternative to GA that we've implemented at Holistics.
Business Intelligence How to Use a Spreadsheet as Your Team's Data Dictionary
A data dictionary is a document that assists you in navigating your team's mountain of data.
Business Intelligence The rise of SQL-based data modeling and DataOps
The resurgence of SQL-based data modeling is a something we should all be interested in. Here's why it's important.
Business Intelligence Hire Your Data Analysts First
In the past, setting up an analytics department meant hiring data engineers first. But in a cloud-first world, you can and should hire data analysts first. Here's why.
Business Intelligence When Should You Get a Data Warehouse?
Occasionally, we get asked “when should we consider getting a data warehouse?”. The answer is a lot simpler than you think!
Business Intelligence When Measuring Performance, Find Lines in the Sand
One of the most useful ideas from the 2013 book Lean Analytics is the notion of 'lines in the sand' — concrete values that tell you how well you're doing on a metric that matters.
Business Intelligence Beware What You Measure: The Principle of Pairing Indicators
When you're implementing company-wide analytics, it's easy to fall into the trap of measuring only one metric. Don't. The principle of pairing indicators is why.