A data dictionary defines all the critical metrics and terms your business uses. It’s a simple idea that dramatically impacts how effectively your business can use its data.But how do you create a data dictionary?Continue reading How to Create a…
Continue reading How to Create a Data Dictionary: 5 Tools + (Free Template!)
Power BI increases its adoption among the most experienced users each day. Thanks to being a user-friendly tool with various data sources to connect to, it helps analyze distinct data sources within the same console.In this post, I’ll show you…
Modern consumers expect a streamlined & personalized service from the retailers with whom they do business. If you can’t fulfill their expectations for an efficient and targeted product offering, many of them will waste no time in taking their business elsewhere.For retail…
Continue reading How Data Analytics Can Help You Grow Your Retail Business
Google released Google Analytics 4 (GA4) in October 2020 in an effort to improve upon the previous generation called Universal Analytics (UA).The update to GA4 provides some new analysis features like the ability to find advertising work tools and the ability to…
Google BigQuery is a serverless data warehouse solution that aims to be cost-effective and highly scalable, allowing businesses to analyze large amounts of data with speed and efficiency.It also comes with some very useful SQL functions that make handling common business cases much…
Continue reading 9 Most Useful BigQuery SQL Functions for Efficency
One of the first big challenges in my career was migrating an application from Microsoft SQL Server to Oracle.A coworker and I were tasked with the migration, which included the translation of views, functions, and stored procedures from one database…
Continue reading Postgres to BigQuery: Convert PostgreSQL Queries into BigQuery SQL
Designing and creating a data dictionary for your company is a big process with big returns. It’s something you need to do if you want deep insights from your data and have a high-functioning analytics team.While you can use one…
Continue reading Building a Data Dictionary: Seven Best Practices
In the world of data and analytics, data observability is an important but often overlooked process.Much of what goes on in data science today isn’t observable because we built most data pipelines to move data, not monitor it. In the…
Continue reading Data Observability Tools: Enhancing Data Quality & Insights
On a high-level, ETL transforms your data before loading, while ELT transforms data only after loading to your warehouse.In this post, we’ll look in detail at the differences between how ETL and ELT work to help you identify which process is…
Continue reading ETL vs ELT: Understanding the Key Differences
When you love a piece of software the way our users love Panoply, there’s nothing more exciting than finding out what new features are on the roadmap. We’ve been watching user videos, meeting with customers, and doing a ton of internal…
When it comes to storing data, we generally have two options: SQL (relational databases) and NoSQL (non-relational databases).The idea for SQL was first introduced in 1970 by Edgar F. Codd in his model for relational database management. This type of…
In our last post, , our intrepid analyst Regina was building a dashboard for her company’s management team. Regina works at a fictitious coffee delivery company named Mocha. One of Mocha’s projects is to acquire more specialty coffee houses to…
Continue reading Data Visualization 101: How Gestalt Principles Yield Better Charts
