How to bring your businesses data under control with data modelling

You’ve worked hard and built a phenomenal business that is now larger than you could have ever comprehended.

You scaled up, scaled fast, and now you’re playing in the big leagues, but the big leagues are tougher to compete in than you ever thought was possible. So, how do you keep up? How do you go beyond? 

The answer is in your data. 

Operating a thriving, large-scale enterprise that brings in millions in revenue is wonderful, and you’ve done many, many things right to get there – but until you have your data under control, you’ll find it may just start to feel like you’re drowning at this stage. 

That’s because you need to automate. You need to make smarter, faster decisions. You need to be able to forecast trends before they change. 

For now, your business is the hot ticket in town. In order to maintain that domination, however, you need to continue to market and strategize – both of which are made so much easier when your data is working hard for you, not against you. 

Just look at Glossier. This company was once a massive success, growing from a small, 6-person team into an international giant thanks to its cult-level status. They had people lining up out the door to buy their products, and now they are barely mentioned at all by beauty influencers, news sites, or even their customers. Glossier stumbled after its rise, with massive control issues and a poor strategy for how to move forward. 

They still exist, of course, and can easily rise again, but take Glossier as a lesson to be learned. You don’t want to stumble just when you’ve reached new heights – you want to soar.

Which you can do by getting your business data under control with an effective data model. 

The data deluge problem of today 

Making your data work for you is essential because it’s only going to become an increasingly larger problem as time goes on. A study conducted by IBM has reported that businesses everywhere are generating more data than ever before. In fact, it’s estimated that by 2025, we will have produced 175 zettabytes of data. 

Storing this data is costly. Using this data can be a goldmine. The fact is, however, that until you invest in a full-scale data management strategy and solution, you won’t be able to use the data you’re amassing in meaningful ways. 

However, before you try to shove it all into a database or even a data warehouse, it’s important to strategize. Just as you would need a proposal management strategy in order to set up your project and project management efforts for success, you also need a data model to set up your database to succeed. 

How structured data can help your business

There are so many ways that you can use your data once it’s fully organized and all located in a single place. You can identify key demographics based on real user behavior, analyze customer patterns and behaviors, and predict where to take your business next to stay relevant. You can identify costly inefficiencies in your operations, allowing you to work out the kinks so your business costs less to run and is all the more efficient because of it. 

The possibilities of what you can do with structured, fully organized data are absolutely endless. After all, if your data isn’t organized, you would first need to source the data you need from all its sources, which is time-consuming and also introduces the risk of error far too many times to be trustworthy. 

Shoving all your data into one location isn’t enough, either. You need it marked up, structured, and fully organized so that analytical and AI tools understand exactly what it is and how to use it. So, how do you go about structuring all that data as it flows into your database? You use data modeling.

How to build an effective data model 

Now that you fully understand the importance of a data model, it’s time to get into how to properly plan and implement it.

1) Define Your Goals 

As with any project, you need to define the goals and scope of your efforts. You can do this in several stages. For example, you may want to organize your customer data so that you can optimize marketing campaigns. This will require a different approach than if your goal was to streamline your financial reporting. 

2) Identify All Data Sources

The next step is to go through and identify all data sources relevant to your goal. To improve your social media, for example, you may use user behavior from your own CRM system, each social media channel, and other third-party marketing tools. Work with others in your business to compile a full list of all your data sources relating to that goal. 

3) Visualize Your Data Model

Visualizing data with entity relationship diagrams (ERDs) is a great way to visually present your data model. A “Customer” can include multiple subsets, such as “Orders,” and Orders can include subsets, such as multiple “Products”. This way, it is easy to establish how the data needs to be organized to extract meaningful data from customer behavior.

4) Govern Your Data

Before you shove in the data itself, it needs to be properly governed. Data governance is a system that works to ensure consistent data management practices across the board. This way, all data is organized the same way, with the same rules for metadata, allowing systems to seamlessly use all elements of your database as needed.  

5) Use Tools that Sort and Store Data Effectively from the Start

Going through all that effort to build a data model and data warehouse would be all put to waste if your systems didn’t continually add to your new database automatically. In order to do just that, you need to make sure you use modern ERP solutions that work to store archive data automatically. Without these tools, you’ll need to go through and reorganize your data again and again, missing potential leads, insights, and more along the way.