What is Data Monitoring?

Data is a crucial asset for businesses to make informed decisions and better understand the digital ecosystem. However, inaccurate data can lead to devastating consequences like missed opportunities, poor operational efficiency, and even lost revenue. This is where data monitoring comes into the picture. 

Data monitoring allows businesses to evaluate their data quality regularly and ensures that the data is consistent, coherent, and updated. Continue reading to know all about data monitoring and its benefits for businesses.  

What is Data Monitoring?

Data monitoring is the process of analyzing and evaluating data to ensure the availability of high-quality data meeting business purposes and standards. It plays a crucial role in avoiding the degradation of data quality over time. Data monitoring covers major aspects of data quality including uniqueness, accuracy, completeness, and conformity. 

The typical data monitoring system includes tools for evaluating data accuracy, consistency, and completeness in order to give users a robust look into the state of their data. They can then use this information to change their systems as necessary to improve data quality and promote alignment across their organizations. 

There are many different types of data quality monitoring tools. Some tools, for example, can help modernize your system, while others are designed for more specific aspects of data monitoring. Some are made specifically for large organizations with complex data management processes; others are well-suited to small businesses with relatively small data sets. 

When choosing between data monitoring companies, it can be helpful to outline your specific needs and what you’re hoping to achieve with your tools. Different companies offer different kinds of tools, so it’s important to do your research to find the company or solution that’s most aligned with your business objectives.

Why is Data Monitoring Important?

Data monitoring allows enterprises to proactively maintain high-quality and consistent data. Monitoring data regularly reduces the risk of incorrect analytics and data-related errors. Here are some of the reasons why data monitoring is important. 

• Data Monitoring allows businesses to make relevant and accurate decisions. 
• It helps to measure data quality against established business targets and standards.
• Data monitoring reduces the risk of mistakes when moving data from one source to another. 
• Automation in modern data monitoring tools eliminates the requirement to verify the data manually. 
• Automated data monitoring reduces errors and lowers the overall operational costs.

Data Monitoring Process 

The data monitoring process consists of multiple steps, each of which is designed to evaluate data and ensure data reliability and relevance. When data is captured it is routed to the appropriate system and measured for quality. 

Different data monitoring systems each follow a slightly different process for data quality management. So you should become familiar with the ins and outs of your system of choice to determine how to best monitor data to achieve desired outcomes. 

While there isn’t necessarily a right way or a wrong way to monitor data, as each business has unique needs and capabilities, following some data monitoring best practices is key to getting the most out of the process.

You might also consider viewing an example of data monitoring system tools to see how this process works in action. Take note of what each system measures, what they specifically look for, and how they ultimately work to promote data quality. As discussed previously, not all systems are right for all types of businesses, so it’s a good idea to outline your needs and what you hope to get out of your data monitoring process and system.

Benefits of Data Monitoring 

Data monitoring tools proactively compare the new data with the list of rules that need to be followed to save data. If any issues are detected, the tool sends an alert to the administration providing information about the error so that it can be checked and corrected. Businesses can create data rules and edit them as needed to maintain data quality as per the needs. 

Data monitoring helps to enhance business agility as the new decision involving data can be made immediately without spending time on the data preparation phase. Here are some of the primary benefits of data monitoring. 

Identify Issues

Incorrect data affects the overall data present in the system. Whenever a data warehouse or data lake receives corrupt data, it can get mixed with the clean data and makes it tough to identify the issues and their sources.

Identifying corrupt data is challenging especially when it is present in a small amount in the warehouse. It can impact the products and even the decision-making abilities. Data monitoring can help avoid these consequences by identifying data errors in the pipeline and ensuring accuracy. 

Reliable Data Warehouse

A data warehouse is the most crucial part of an organization. Stakeholders and data analysts often rely on it to make decisions. A reliable data warehouse facilitates agility and efficient decisions. Data monitoring creates confidence in data lakes and warehouses allowing companies to leverage their data completely. 

Reduces Overall Response Time

Automation allows businesses to monitor their systems in real-time and even sends them alerts so that the issues can be fixed immediately. 

Enterprises can resolve data errors even before they start creating bigger issues. If real-time data monitoring repeatedly identifies the same issues related to a certain type of data source, enterprises can identify them to eliminate future challenges. 

Enhances Data Efficiency

With the help of data monitoring, businesses can create connections between different data sets and real-time monitoring systems. For instance, data monitoring helps to find relationships between issues that are related to each other. Moreover, it allows enterprises to set parameters and guidelines for controlling data standards and sends alerts if these parameters are not met. 

Standard Data Format

Real-time data monitoring tools record data continuously from multiple sources and convert it into a standardized format. It means data collected from one source can contribute to the data set for the entire organization. Moreover, data monitoring can also clean the data to make sure it is useful and valuable. 

Best Strategies for Data Monitoring 

Improving data means making it error-free and reliable by getting rid of duplicates, outdated information, and inconsistencies. In order to establish an effective strategy for data monitoring, check out the following practices.  

Setup Clear Data Objectives

Data monitoring begins with setting up clear objectives and goals to lay a strong foundation. It includes identifying key metrics, targets to be achieved, and performance indicators. Also, it helps in focusing on the essential features of data and avoiding unnecessary barriers. It helps in setting a path on what needs to be done in order to ensure effective data monitoring and reliable data.

Choose the Right Data Sources

Picking up the right data sources that are highly relatable to your company’s objective is another essential practice of data monitoring. Choose the data applications, sources, databases, and systems that you need to monitor. It helps in ensuring that you are collecting actionable and valuable data.

Establish Realistic Benchmarks

Set the appropriate benchmarks to analyze the normal or abnormal behavior of your data. These benchmarks should be based on the current industry standards, your company’s principles, business rules, and historical data. It helps to identify data anomalies and fix them on time.

Set Regular Alerts

Data monitoring tools allow you to set up alerts whenever data errors occur. Enterprises need to ensure that the alerts are sent to the right people so that action can be taken against the errors adequately. It helps prevent issues from escalating.

Use Visualization Tools

Visualization tools help to identify outliers and trends quickly. Moreover, they allow us to gain insight into vast amounts of data and recognize new patterns. Making sense of data patterns these tools help users to pay attention to areas that indicate progress or red flags.

Perform Regular Audits

Enterprises should regularly review their data. It includes assessing the relevance of the data being monitored, the usefulness of data visualization, and the effectiveness of data alerts. Audits help in improving the data quality and meeting the business needs adequately.

Ensure Data Safety and Security

Data security and safety is the most essential aspect when it comes to ensuring data reliability. Make sure that the data monitoring is accessible to authorized people only. Moreover, follow the privacy rules and laws related to data security.

Regularly Monitor Data Performance Impact

Pay attention to how data monitoring is helping the performance of your systems and the business. Be open to adjusting the frequency and methods for data collection to balance monitoring according to the business needs and system performance.

Data Monitoring Platform

Using a data monitoring platform, you can more easily keep track of the data that’s flowing in and out of your system, checking for quality and making sure that everything is in its correct place. Data monitoring systems are extremely useful for evaluating data on a broader level. Rather than simply zoning in on one component, you can get a big-picture look at your data.

The top monitoring tools, such as Acceldata, offer robust observability and allow users to easily find what they’re looking for without having to sort through piles and piles of useless information.

There are many types of application monitoring tools, so whether you’re a large organization with a myriad of complex data-related needs or a small business that’s just looking for a simple tool to help with the monitoring process, you should be able to find something that meets your unique requirements.

Cloud data monitoring tools are among the most common because they can be accessed by anyone anywhere they are connected to the internet. This can be a great option for businesses with remote data teams or companies that are otherwise unable to get everybody into the office regularly. Cloud-based tools offer flexibility and convenience to various types of users.

Data Monitoring Company

A data monitoring company provides the tools and software for other companies to monitor their data systems. Acceldata is a data monitoring company that provides multidimensional data observability. This means users can view their data holistically to get a big-picture look. They can see how different components interact with each other to impact data quality, whether for better or worse.

The Acceldata platform predicts issues before they hurt business outcomes, correlates events, and prevents cost overruns due to unreliable data. In this way, users can evaluate data from all angles rather than just focusing on a single aspect of data monitoring.

To view an Acceldata tutorial or learn more about the platform, visit the Acceldata resource library. It contains helpful tips and success stories that show how the platform can assist users in getting started with data observability.

Understanding different data monitoring systems and what each brings to the table is crucial to ensuring quality data and, by extension, promoting greater business growth. Low-quality data can have a huge negative effect on business outcomes, so it’s important to use the correct tools to appropriately monitor data at all times.

Improve Data Quality with the Acceldata Data Monitoring

Acceldata is among the top data monitoring companies, offering multidimensional data observability for those working within complex data environments. With Acceldata, you can get a more comprehensive look at your data. This includes checking for performance and gaining helpful insights for improving data quality.

Acceldata data observability platform empowers users to optimize their data systems. This enables them to get more out of the data that’s available to them. Data observability can result in up to 300% higher data engineering productivity and 90% fewer data-related incidents. So, to maximize efficiency and maintain quality, it’s important to continually monitor data from a multidimensional angle.