The hardest part about building a data warehouse isn’t getting data into it... It’s integrating and modeling that data to create a single source of truth. Anyone can pull data from multiple sources, but the real challenge is fitting it in to a data model. When you have different ways data can be generated and historical data from legacy systems that need to fit into a unified source of truth, not everything aligns seamlessly. However, there are a few strategies you can use to make integration...
6 days ago • 1 min read
Data integration is one of the hardest things to do in data. It's the thing that everyone dreads and the thing everyone has to do. And if you're doing it within Excel by using XLOOKUPS (or VLOOKUPS or INDEX(MATCHES)), it quickly spirals into a chaotic mess. Soon enough, it's like that one messy closet in your house that you never open and try your hardest to forget. That’s why integrating data in a data warehouse environment is a game changer. It provides structure, scalability, and the...
15 days ago • 1 min read
While there are several critical areas within a comprehensive data strategy, there are three foundational pillars that your business needs to get right: 1. Data Integration This is how you create a "single source of truth" around a thing your business care about (orders, customers, product etc...). Creating a single source of truth is vital for efficiency and decision-making. Data integration ensures that your key business metrics—whether customer profiles, order histories, or product...
18 days ago • 1 min read
If you're following developments in AI, you’ve likely come across the term RAG (Retrieval-Augmented Generation). But what does it mean, and why is it important for your business? RAG refers to a process where a Large Language Model (LLM)—such as ChatGPT—retrieves specific, relevant information from a connected data source to enhance the quality of its generated responses. Instead of relying purely on its pre-trained knowledge, the LLM pulls real-time, contextual data to answer questions more...
20 days ago • 1 min read
How do you or your analytics team handle errors in a pipeline? By pipeline, I mean any type of low-code, no-code, all-code solution that runs on a schedule and performs some sort of activity. Because here's the truth. Pipelines fail. It doesn't matter if it's a ETL, ELT, or application integration pipeline. It will fail. It doesn't matter if you have a Dev, Test, Prod environment. It will fail. It doesn't matter if you have 1 person or 10 people supporting it. It will fail. Eventually. So...
29 days ago • 1 min read
Picture this: You’re onboarding a new employee fresh out of college, and they have no idea what the difference is between a Broker and a 3PL. Traditionally, it takes about six months, on average, to bring them fully up to speed. But what if there was a way to accelerate this learning process by visually showing how everything in your industry is interconnected? That’s where conceptual models come in—they provide a fast, straightforward way to demonstrate relationships and roles within your...
about 1 month ago • 1 min read
Most companies have accounting software, a bookkeeper, and an accountant to record and track their finances. You are probably spending over 10k (if you outsource your bookkeeping and accounting- if not, it's likely a lot more!) to ensure your accounting is done right. Why do you spend all this money on accounting and finance? If you get it wrong, you could end up spending a lot more! The same is valid for data. Your data can be the difference between job success and job failure. If you don't...
about 1 month ago • 1 min read
Any technical development is constantly threatened with being rushed, and this is especially true for data projects. Data is often rushed because it costs a lot and doesn't generate direct revenue. It's a cost center. Executives leading data projects are under pressure to deliver quick, tangible results to justify the project's existence. This type of development can quickly fall into delivering quick, tangible, and unscalable results. While it may seem like you're picking up momentum for the...
about 1 month ago • 1 min read
Imagine this: You've finally saved enough money to build your dream home. You've found the perfect builder, You've laid out what type of flooring you want, the lighting and the countertops. The builder takes all of the details you've laid out and gets to work. When it's all finished, you walk through the front door and find rooms placed awkwardly around the house. The kitchen is upstairs, the living room is in the basement, and your master bedroom is the entire first floor. You probably...
about 1 month ago • 1 min read