With how much data is generated per day, navigating the massive flood of information can be overwhelming. But it is a necessity, as making data-driven decisions allows businesses to stay ahead of the competition. According to Entrepreneur’s article on big data analytics, at least 44% of executives think data is necessary for decision-making, while 37% believe it provides deeper insights into their business.
So, how do businesses begin to decipher this saturated sphere of information? The answer lies in data modeling. When used wisely, it could lead to smarter, more informed decisions.
Let’s take a closer look at data modeling and discover why it is the future.
What is Data Modeling?
Data modeling refers to the method of creating a data model that stores important data in a systematic and visually comprehensive way. It’s a way of creating a conceptual representation of data objects, how they interact, and the rules applied to them.
MongoDB’s guide to data modeling explains these relationships in detail, even citing an example: libraries will need to know which books have been borrowed by which user. The thing is, each user is entitled to five books at a time. So, just like a blueprint of a complicated machine, a data model highlights these intricate details to help us understand complex systems.
7 Benefits of Data Modeling
Reducing Complexity
As stated earlier, data modeling’s main purpose is to reduce the complexity of reading data. A data model provides a simplified visualization of the hundreds or thousands of tables and entities for decision-makers to keep track of, which helps reduces the time and effort needed for data analysis.
Improved Business Processes
With data models, it becomes straightforward to identify inefficiences and areas for improvement in various business processes, such as supply chain management and customer support. This leads to a better overall business performance and improved decision-making.
However, it’s important to note that data models are still merely tools. Harvard’s thought piece on data and intuition explains that intuition is also critical in making decisions, especially regarding abstract or ambiguous issues.
Consistency in Information
One of the biggest challenges when dealing with a vast amount of data is maintaining consistency. Data modeling aids in establishing a singular “source of truth” by standardizing definitions and formats, hence ensuring accuracy and uniformity across departments.
Fulfilling Regulatory Compliance
Organizations, especially within sectors like healthcare and finance, face various regulatory compliance and data security legislation. At least through data modeling, businesses can secure private and sensitive data more effectively and meet necessary compliance standards more easily.
Gear Up for Artificial Intelligence
Artificial intelligence (AI) and machine learning technologies depend heavily on data sets. Data modeling organizes and prepares this data, helping to provide the necessary fuel for these powerful systems to operate accurately and efficiently.
To know more about how AI is already disrupting the business landscape, read our previous piece on ‘AI in Business’ and the ways AI is changing the future of payments.
Promotes Collaboration and Understanding
Data modeling bridges the gap between technical members and business stakeholders by creating a clear and concise visual representation of data structures. It could encourage cross-team collaboration and understanding, which could then lead to better project management and execution.
Advancements in Technology
As the power of computing continues to increase, so does our ability to handle larger and more complex data sets. Data modeling tools and techniques are continually evolving and advancing to leverage these capabilities, promising even greater insights and efficiencies.
Naturally, programming languages are also being updated to match the demands of today’s digital era. Check out our similar article on reasons why Python is the future.
Conclusion
Data modeling is more than a tool; it’s a future-facing strategy. It acts as a navigator in the vast sea of data, guiding us towards crucial insights hidden beneath the surface. As we continue to generate data, the importance of data modeling will only rise. Indeed, it is the future!
