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AboutRead In 8 Minutes
Ensuring Data Integrity
One of the most basic premises of Data Integrity is to ensure the data in your project management system is current, accurate and complete. This means that the processes and systems in place to manage project data are performing integrity checks both upon initial entry of the data, and also while the data is at rest in the database. In other words, applying data integrity processes is important from start to finish throughout the lifecycle of all information. This includes what happens to any element of data after it has been input into the system.
We talk a lot about getting project data into the hands of the project team in real-time. Real-time data matters on construction projects. It leads to better decision making and the ability to take early, corrective action on issues as they arise.
We also go to great lengths to discuss how the project management system can be configured to ensure the highest levels of accuracy upon data input by preconfiguring constraints, tolerances and ranges of acceptable values. In other words, making sure data is accurate and complete when it’s first entered.
The added plus of a project management system is that it doesn’t stop there.
Project controls professionals need to trust the data they’re working with on construction projects. It’s critical for the project software to be on duty 24 hours a day and 7 days a week – long after the data has been entered. Your teams will lean on the project cost management software to work tirelessly 24-by-7 to monitor the data, and perform continuous integrity checks, reconciliations, and benchmarking.
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Data Integrity Checks
After any project data has been input, automated data integrity checks will be ongoing day and night to catch any issues that may have either slipped by the initial data validation on input, or that may have emerged through background synchronizations with other systems. When it comes to construction project data, it can originate from multiple places – such as from the field as daily jobsite data. Or from in the office as budgets, documents, change orders, forecasts, etc. Data can also come from an integrated synch with other enterprise systems – like the ERP or timesheets. In these cases, external data entering the system has the potential of modifying, overwriting or deleting data in the system. Clearly, data checks are performed during the sync process, but errors and anomalies are always possible. The system data checks can spot these irregularities and either flag them, or directly make the correction.
The key is, that these integrity tests the software is performing, are ongoing in the background to ensure persistent data integrity over the long term.
Data Benchmarks on Big Data
Part of that automated background data checking activity is to run algorithms on the data to aggregate it into meaningful benchmarks, averages, trends, etc. This is not only valuable information in the aggregate for users to take advantage of – like, when analyzing the data for broader trends – it can also be used to spot data anomalies and outliers that can be flagged as potential errors.
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The 4castplus suite of tools enables your team to enter a vast amount of project information on a daily basis. From estimates to purchase orders, jobsite tracking to change orders, progress measurements to forecasts, timesheets to customer invoices and so much more. Contact us to learn more.
