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Data Normalization: Solving Big Data Issues for Fleet Risk Management

Data normalization is being used more and more to solve the growing issues surrounding big data and fleet risk management.

Understanding what data normalization is and knowing why it’s important to fleet risk management gives companies a real advantage in both valuing and utilizing the big data they are already gathering.

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What is Data Normalization?

As a short answer, data normalization helps fleet risk management by making all elements of the collected data comparable and consistent.

With this, accurate insights on the where, what and who of a fleet’s risk trends can be gained, allowing fleet managers to address them through training and management resources.

On the other hand, without effective data normalization, big data insights can be flawed – leading to the wasting of training and management resources by deploying them in the wrong places.

Big Data and Fleet Management

The amount of data being produced, collected and stored grows exponentially year after year. This extends to a fleet’s vehicles and drivers.

As they become more and more connected, fleet managers work to use this data to better manage fleet operations and reduce associated risks. Companies can then reduce incident rates and claims costs through improved training effectiveness.

Of course, this data abundance is only set to grow.

In the last decade, we’ve seen the rise of telematics, dash cams, GPS devices, smartphone apps and tablets in fleet management as ways to deliver efficiencies in operations, improvements in safety and better customer service. In the coming decade, this trend will only increase with 5G, (semi) autonomous vehicles and the true, mobile, always-connected Internet of Things.

Add to these in-vehicle data points the increasing amount of out-of-vehicle, employee data we now have in digital formats – such as reviews, training records and compliance checks – and the effective use of big data is a big challenge.

>> Learn why Excel is a dangerous tool for managing vehicle and driver data <<

The Joe Bloggs, Mr. Bloggs and J. Bloggs Problem

With big data, the integrity and ability to synchronize data across multiple and disparate data sources is the key to its use and value.

As a human, reading the above sub-heading, you would suspect that Joe Bloggs, Mr. Bloggs and J. Bloggs are all the same person, and therefore data attributed to one should be attributed to all. For a machine, that deduction is not as intuitive but is crucially important if the full benefit of all the associated data is to be realized.

This is where data normalization comes in. It addresses the challenge of data sets becoming bigger and more diverse, and how to incorporate them into a platform for effective analysis.

If this challenge isn’t met, gaps in the data sets grow, which in turn leads to wrong insights and wasted actions. All of which can be masked by the belief that because the data is so big and rich, the insights, conclusions and actions must be correct – meaning that what should be a virtuous circle can instead become vicious.

Other Big Data Issues for Fleet Management

The Complexity of a System of Systems

Big data is driven by the growth in connected platforms and the amalgamation of all the data they take in and pass on – a system of systems. And as the connected world grows, so does this system of systems. Understanding the nature of this system and its connections, so that when something is wrong it can be identified, isolated, and corrected is a skill in itself.

The Shortage of Professional Big Data Analysts

With this exponential rise in data creates a huge demand for data scientists and data analysts to both work the data and, just as importantly, to understand it. Also, their skill set needs to cover communicating what they find to other parts of the business, such as fleet managers, in ways that can be understood. This crucial capability is in short supply.

Uncertainty About the Future Elements of Data Management

A further challenge for fleet managers wanting to use big data insights is the changing nature of the technologies available. Adopting the right tech for the job is a crucial decision in itself. It is also one that impacts the range of choices that can be made in the future, so it needs to be well thought out.

Data Privacy and Security

A concern in everything and anything to do with data is that of security and privacy. By its use of disparate data sources, this is a vulnerable area for big data and therefore always needs to be a front-of-mind consideration for fleet operators.

Data Normalization – the Solution to Big Data Issues for Fleet Risk Management

Big data is referred to as “unstructured data.” The role of data normalization is to organize it and turn it into a structured form that can be used for analysis and insight by fleet managers.

Data normalization covers these five core areas:

Removal of duplicates. This cleans up the data, making it easier to analyze.

Grouping. Making related data easier to access and use by having it in close proximity.

Resolve conflicts. Again, cleaning up the data and improving the insight from analysis of the data.

Formatting. Converting data into a format suitable for further processing and analysis.

Consolidation. Combining data into a much more organized structure, again making it easier to access and analyze.

An important point to note is that data normalization is not a static, one-time activity. It is an ongoing, critical process.

Explore the Benefits of Data Normalization

A fleet risk management database should use data normalization so that the data can be visualized and properly analyzed. Without it, a fleet operator can collect all the data it wants, but most of it will simply go unused.

Additionally, data normalization means databases take up less space, saving data warehousing costs and improving performance. A database that isn’t clogged with irrelevant information means analysis can be actioned more quickly and efficiently.

Interpreting this data is critical in improving fleet operations and safety. But if the data has come from multiple sources, cross-examining them can be challenging. Data normalization makes this process easier, allowing fleet managers to answer the questions they have more quickly with full confidence that the data they are using is accurate.

Telematics devices provide a fantastic (and increasingly popular) method of improving fleet management. Considering a telematics solution? Download this guide to learn how you can better leverage your data to capture the complete picture of risk. 

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