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How to Improve Data Accuracy with Integrated Solutions

by Danielle Borges - Marketing & Sales Director

Data accuracy is the ability of data to precisely describe the observed event or reality, exactly as it occurred. Inaccurate data can lead to distortions, incomplete information, or even outdated details, as in the case of addresses, for example. Learn more!

Data accuracy is the core of effective decision-making in any organization. Without accurate data, businesses risk operational inefficiencies, poor strategic choices, and missed opportunities.

From entry errors to storage issues, even minor inaccuracies can snowball into significant problems, affecting everything from customer satisfaction to financial performance.

This article explores the role of integrated solutions, particularly Claris FileMaker, in addressing challenges like data anomalies, outliers, and human or system errors. 

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What is data accuracy?

Data accuracy is one of the most important elements of data quality. This characteristic refers to the exactness of data, or rather, how well that data describes the reality or object being observed.

In other words, the more accurate the data, the better its ability to describe events exactly as and when they occur.

Let’s say your company collects the addresses of all its customers for logistics planning. Accurate data shouldn’t just state that they are in the USA, but specify the state, city, neighborhood, street, house number, and also include the last time the location was updated, as people can move.

This example makes it clear that there’s only one way to measure the accuracy of data: by comparing it with external reality. This makes it challenging to perform this data quality control, but it is still crucial for the smooth functioning of your business.

Read More: 13 Strategies to Identify and Fix Operational Inefficiencies

Why Data Accuracy Matters?

Data accuracy means having information that is correct and represents real-world events or objects. For businesses, it’s essential for consistent operations, good decisions, and reliable data analysis. When data is accurate, it reduces problems like entry errors, processing errors, and storage errors, ensuring the information can be trusted.

Issues like incomplete data, missing data, duplicate data, or outliers can cause big problems, like bad customer experiences or wrong decisions. For instance, a Harvard Business Review report highlights that poor data quality costs the U.S. economy $3.1 trillion annually. These mistakes often happen because of human error, system error, or weak data validation processes.

Keeping data accurate also helps ensure data integrity, meaning information stays reliable and consistent. Tools like Claris FileMaker use machine learning to spot mistakes and improve data management and data visualization.

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What Are the Best Practices for Improving Data Accuracy?

Lack of data accuracy can lead to a range of problems for your business, including inducing poor decision-making by managers. To avoid this issue, it’s important to take certain precautions during the data collection and storage process to ensure accuracy.

Some of the best practices for this are:

  • Use automated software for data collection, storage, and management, inhibiting human error;
  • Continuously evaluate data processes and implement updates;
  • Utilize current software updates and tools to validate data accuracy;
  • Clearly define processes regarding the types of data collected, how they are collected, and their management processes;
  • Train your team on data accuracy evaluation and set goals for it;
  • Use data cleansing tools to identify and correct inaccurate or duplicate data.

Errors and Factors that Affect Data Accuracy

Common data accuracy issues include entry errors, like typing mistakes, and processing errors, which happen during calculations or data updates. There are also storage errors, such as when files get corrupted or databases are not updated, which can make the data unreliable.

Mistakes can come from both people and systems. Human error, like typos or entering wrong information, is a common issue. System errors, like software bugs or hardware failures, can create problems such as data anomalies, duplicate data, or missing data.

Other challenges include biased data from unbalanced sources and incomplete data that lacks important details. Even valid outliers can sometimes make it harder to see the full picture. Without proper data validation and good data management, these issues can grow and affect data integrity.

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Problems Arising from Data Inaccuracies

Data inaccuracies can lead to serious problems for businesses, affecting finances, operations, and growth opportunities. Here are some common examples of data inaccuracy and the issues they can cause:

  • Financial losses: duplicate data in billing systems can result in overcharging or undercharging customers, damaging trust and leading to revenue loss. Also, processing errors in payroll systems may lead to incorrect employee payments, increasing costs and creating dissatisfaction.
  • Operational disruptions: incomplete data in inventory systems can cause stock outs or overstocking, disrupting supply chains and delaying deliveries. Human error in data entry may result in scheduling conflicts, leading to missed deadlines or wasted resources.
  • Missed opportunities: biased data in customer profiles can lead to poorly targeted marketing campaigns, reducing ROI and failing to attract key audiences. Data anomalies in sales forecasts can result in bad decisions, such as underinvesting in successful products or overinvesting in failing ones.
  • Compliance issues: missing data in regulatory reports can result in fines or legal penalties for non-compliance. Inaccurate data in tax filings can trigger audits or additional expenses.
  • Reputational damage: system errors that expose sensitive information due to inaccuracies in access control can lead to data breaches and loss of customer trust.

These problems highlight the need for robust data validation, proper data management, and tools like Claris FileMaker to ensure data quality, improve operational efficiency, and reduce risks caused by data inaccuracies.

Key Benefits of Claris FileMaker for Data Accuracy

Claris FileMaker is a powerful tool that helps businesses overcome challenges related to data management. Below are the key benefits FileMaker brings to organizations aiming to improve their data quality and data integrity.

Faster Decision-Making

With Claris FileMaker, businesses can access clean and reliable data in real-time, speeding up data analysis and enabling faster, more informed decisions. Accurate data ensures that decision-makers can act confidently without delays caused by data anomalies or missing information.

Eliminate Data Silos

FileMaker integrates data from multiple sources, breaking down silos and creating a unified view of information. This integration improves data visualization and ensures consistency across departments, reducing storage errors and improving overall data management.

Reduce Human Errors and Redundancies

Automated processes in FileMaker reduce the chance of human error during data entry or processing. By identifying and addressing duplicate data and redundant workflows, the platform streamlines operations and improves data validation efforts.

Improve Customer Experience

Accurate data leads to better customer interactions. FileMaker enables businesses to use reliable analytics for personalized services, minimizing issues caused by biased data or inaccurate data. This enhances trust and loyalty among customers.

More Reliable Analytics for Strategic Planning

FileMaker ensures that analytics are built on high-quality, consistent data. By addressing data anomalies and outliers, the platform delivers insights that businesses can trust for long-term strategic planning, improving operational efficiency and driving growth.

Read More: How to Create a Custom CRM with FileMaker Pro: Step-by-Step

How to Integrate your Systems for Better Data Accuracy

Integrating your systems is a critical step toward achieving better data accuracy. Proper integration eliminates silos, minimizes human errors, and streamlines data validation for more reliable operations. Here’s how to get started:

1. Assess Your Current Systems

Before integrating, evaluate your existing tools and processes. Identify weaknesses, such as incomplete data, duplicate data, or system errors, that may affect data quality. Understanding these gaps is essential for building a foundation for better data analysis and data visualization.

2. Design a Custom Solution

A custom-made solution is key to effective system integration. Claris FileMaker offers powerful tools to connect various platforms, creating a cohesive workflow that fits your unique needs. 

At Codence, we specialize in building integrated solutions that align with your business processes, ensuring efficient data management and enhanced operational efficiency. FileMaker’s integration capabilities make it a versatile choice for businesses seeking to unify their systems.

3. Automate Data Entry and Synchronization

Manual data entry is prone to entry errors and redundancies. Automating these processes with tools like FileMaker ensures accurate data synchronization across platforms. 

Automation also reduces the risk of missing data and ensures that all systems stay updated in real time, improving overall data quality.

4. Monitor and Optimize

Integration doesn’t stop at implementation. Regularly monitor your systems to identify data anomalies, outliers, or any recurring issues. Use analytics to optimize workflows and refine the integration as needed. Continuous improvements ensure that your data remains accurate, reliable, and ready to support business decisions.

How to Measure Data Accuracy?

Measuring data accuracy is essential to ensure your information is reliable and effective for decision-making. Here are some practical steps to measure data quality and maintain data integrity:

1. Define Accuracy Metrics

Start by setting clear criteria for what “accurate data” means for your business. These could include:

  • Completeness: checking for missing data or gaps in records.
  • Consistency: ensuring data is free from data anomalies or outliers across systems.
  • Validity: verifying data against predefined rules or data validation protocols.

2. Conduct Data Audits

Regular audits help identify errors, such as human error, system error, or processing errors. Use tools like Claris FileMaker to detect biased data and maintain data management standards. Audits provide a clear picture of how well your data aligns with the metrics you’ve set.

3. Use Data Accuracy Ratios

Measure data accuracy using ratios, such as:

  • Error rate: percentage of incorrect records compared to the total data set.
  • Duplicate rate: percentage of duplicate data within your system.
  • Completion rate: percentage of records that are complete, with no incomplete data fields.

4. Leverage Data Analysis Tools

Tools like Claris FileMaker and advanced data visualization software help you assess and visualize accuracy levels. These tools use features like machine learning to detect patterns, uncover data anomalies, and highlight areas that need improvement.

Woman working on a tablet in a modern office environment, with charts and notes on the desk.

How to Overcome Common Challenges?

Keeping data accurate can be tricky, but there are ways to solve common problems. For example, mistakes during manual data entry can be reduced by using automated tools and double-checking the information. 

Missing or incomplete data is another frequent problem that can disrupt operations and decision-making. Automating checks to flag incomplete records and using tools like machine learning to fill gaps can help. 

Lastly, system errors, such as corrupted files or software bugs, can compromise data quality. Regular maintenance, backups, and real-time monitoring are crucial for resolving these issues. By addressing these common challenges, businesses can improve data quality and ensure reliable, accurate information.

Read More: Integrate Google Maps with FileMaker: Complete Guide

Enhance Data with Codence

Claris FileMaker provides a powerful, customizable, and scalable solution to improve data accuracy, streamline processes, and support seamless data integration and automation. By addressing common data challenges and tailoring solutions to your unique business needs, FileMaker ensures your organization can make informed decisions with confidence.Ready to see how FileMaker can transform your data management? Contact Codence today for a personalized demo and discover how we can help you enhance your data and operations.

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