Why is data modelling important?
With about 2.5 quintillion bytes of information flooding organisations every day, wrangling data is no small feat. The insights you draw from your data can have a game-changing impact across your business, from improved customer service to a more resilient supply chain. But to get the best analytics from your data in the long term, you need a plan that will stand the test of time.
Data modelling software tools are applications that help you create database structures using a simple and visually appealing data model—a roadmap for how your business will organise and manage data to reach your business objectives going forward. The data modelling process is often compared to the way an architect creates a blueprint before building a house. Without a plan that considers the home’s infrastructure and how the people who live there will need to use the rooms, it wouldn’t function well.
Data modelling gives stakeholders across your organisation a high-level view of the types of data you collect, how it should be managed, and what you want to achieve with it. Data modelling concepts are rendered as easy-to-read visual representations, such as simple graphs, that label data types and the relationships between them using jargon-free, real-world terms such as customers, suppliers, vendors, and products. Developers and non-technical staff can collaborate in the modelling process using natural language. Modelling allows everyone to come to a mutual understanding of the needs of the business and how end users will use information to make data-driven decisions whenever they need to. It’s an important first step towards better business intelligence.
How data modelling management tools benefit you
It can be tempting to dive straight into to a data management project without first taking the proactive step of creating a model. But spending time up front creating a strategy for your data will save you countless headaches down the road. Here are ten reasons why it pays off to use a logical data modelling tool to craft a foundation for how your business uses data.
1. Get everyone on the same page
Data modelling tools allow developers to describe your organisation’s vast information landscape in easy-to-understand terms that both technical and non-technical staff can have valuable discussions about.
Developers don’t always start out with a full understanding of the types of decisions stakeholders in various departments need to make or what kinds of reports end users will be generating with business analytics tools. Likewise, the people with the best knowledge of business processes might not have a complete understanding of data management. Data modelling is a collaborative process between people from all disciplines that keeps the core business needs in mind so that the model you create is a bespoke solution, not a cookie-cutter structure built on false assumptions.
2. Clarify your project scope
Data is vast and unwieldly, but a logical data modelling tool makes the relationships between each data object concrete and easy to understand. Once created, a data model lays out the conceptual, logical, and physical concepts that underlie the database design in a way that is not open to interpretation. Modelling accelerates the work of developers, business analysts, and data architects because it allows them to become firm in their knowledge of what they will need to deliver.
3. Improve data quality
The data modelling process establishes rules for monitoring data quality and identifies any redundancies or omissions. Your data objects are now represented as accurately as possible with fewer errors—ensuring that the people using your business analytics tools will be able to make data-driven decisions confidently. Put simply, accurate data produces accurate reports; inaccurate data can lead to poorly informed decision making.
4. Save time and money
The planning stage that produces your data model represents a small proportion of your overall project budget, but it can uncover significant problems that would be much more costly to resolve in the execution stage. Forward engineering is always less expensive—and less frustrating—than reverse engineering. Think of data modelling as a dose of preventative medicine that will help you avoid costly triage later in the field.
Using data modelling tools to forge your data strategy will also empower your business to achieve quicker times to market by catching errors early. No matter how complex your data estate is or how much it grows, you can return to your data model often and revisit the basic rules you’ve set to govern it.
Premature coding causes many software development efforts to fail. Proper data modelling, however, can prevent unnecessary delays and impediments to productivity.
5. Improve database performance
Well-organised databases built on a strong foundation run faster, are easier to tweak, and require less reverse engineering—a.k.a. reinventing the wheel—in the long term. With a blueprint in place for how you use information in your business, inefficiencies are easier to diagnose. Similarly, a blueprint makes it easier to find new opportunities for optimisation as your business needs change.
6. Enable better documentation
Inevitably, your business will have employee turnover. When you plan your information landscape using data modelling management tools, it enables consistent documentation that newcomers can understand. Consistent documentation simplifies ongoing database maintenance and preserves operational efficiency for the whole organisation.
7. Improve application quality
The data modelling process gives your organisation a clear vision for how data can fill your business needs. Developers and business decision makers use models to address misconceptions early so that any problems that occur later are likely to be small hiccups that are easily resolved—rather than huge pitfalls.
8. Improve regulatory compliance
The data management rules you establish in the modelling phase set the stage for ease of compliance with government regulations and industry standards. It isn’t uncommon for a business to be subject to data regulation standards from multiple entities, and the complexity of these requirements is on the rise globally. A logical data modelling tool can help your organisation raise the bar for its data governance while still making data easy to consume.
9. Set the stage for data mining
Data modelling tools help automate and scale your analytics so you can do more with data as your business changes. Data mining involves capturing and processing information in dedicated data warehouses to reveal hidden relationships that humans might not uncover. Data mining can help organisations get ahead of trends and identify brand-new opportunities for business growth.
10. Prepare your business for what’s next
The only certainty about technology is that it will continue to take quantum leaps forward. If you organise and manage your data according to a clear set of rules, it makes the next big IT infrastructure change much less challenging. Whether the next step is some fine tuning, a bit of proactive maintenance, or a major upgrade, a sound data model will help you get through it with less cost and downtime.