As modern businesses continue to rely heavily on accurate, timely, and high-quality data for informed decision-making, a growing number of data quality tools have emerged, promising to monitor, analyze, alert, and even clean data across various platforms. However, there’s a catch: many of these traditional data quality tools export your data from their native environment to external systems for analysis. This approach not only consumes valuable time but also poses significant risks and increases costs.

At digna, we believe there’s a better way. We take a fundamentally different approach: “In-Database Data Analysis”. Our platform works within your data infrastructure, minimizing the need to export and move data around. Instead of shifting data out of the database, we analyze it directly at the source and export only the necessary metrics, ensuring data integrity and saving both time and costs.

Let’s explore why this approach is not only more efficient but also more secure and cost-effective.

The Hidden Cost of Export-based Data Analysis

Many data quality tools require you to extract large volumes of data from your database before running their analysis. While this might seem straightforward, it introduces several inefficiencies and risks:

Time-Consuming Process

Exporting data from a database can take significant time, especially when dealing with large datasets. The process of exporting, transferring, and re-importing data can slow down workflows, impacting productivity across teams. For businesses that rely on real-time data, these delays can lead to missed opportunities and sluggish decision-making.

Increased Infrastructure Costs

Exporting data comes with hidden costs. Moving data out of your database requires additional infrastructure to store and process it externally. These data movements often increase bandwidth and storage expenses, adding a financial burden to your organization. The bigger your datasets, the higher the costs.

Security and Compliance Risks

When data leaves its original environment, it becomes vulnerable. External systems and platforms introduce new attack surfaces, increasing the risk of breaches and non-compliance with data privacy regulations. Exporting data puts you at greater risk of unauthorized access or loss, as your data passes through different systems and environments.

Data Inconsistencies

Extracting and moving data between platforms can lead to inconsistencies or errors during the transfer process. Data discrepancies between the original source and the external analysis platform can compromise the accuracy of your insights and decision-making, defeating the entire purpose of data quality management.

The digna Difference: In-Database Data Quality Platform

At digna, we’ve flipped the traditional model on its head. Our platform performs data quality analysis directly within your database. This means your data stays where it belongs—safe, secure, and efficient. With compatibility with any preferred database base you want including Databricks, Oracle, Microsoft SQL Server, Teradata, Snowflake, Netezza, SAPHANA, MySQL, PostgreSQL, Timescale, MariaDB, Apache Impala, we export only the necessary metrics for reporting, reducing overhead and allowing you to retain full control of your data.

Here’s how our in-database approach helps you stay ahead:

Faster, Real-Time Analysis

By analyzing data directly in the database, digna avoids the time-consuming process of data export. We profile your data continuously with our Autometrics feature, capturing key metrics for real-time analysis. This ensures you get insights as the data is updated—no delays, no extra steps.

Lower Infrastructure Costs

Since digna analyzes data without needing to extract it from the database, your infrastructure costs stay low. Our solution eliminates the need for additional storage or processing power, keeping your operations lean and efficient.

Enhanced Data Security

With digna, your data stays in your database. Our in-database approach minimizes exposure to external systems, keeping your data secure from breaches and third-party risks. We understand how crucial security is in today’s regulatory environment, and we’re committed to safeguarding your data at every step.

Consistency and Accuracy

By maintaining data integrity within the database, digna reduces the risk of discrepancies caused by external data movement. You’re always working with the most accurate, up-to-date information, enabling confident and informed decision-making.

Experience the Power of In-Database Data Quality Analysis

The traditional method of exporting data for quality checks is becoming a practice of the past. With digna, you can perform comprehensive data quality checks directly in your database, ensuring faster insights, reduced costs, and enhanced security. Our advanced features are designed to give you peace of mind and control over your data.

Ready to save time, cut costs, and protect your data? Book a demo with digna today. Discover how our in-database data quality solution can streamline your processes and deliver superior results with real-time anomaly detection and automated insights.

Experience the power of keeping your data secure and analytics sharp, all without ever leaving your database. Say goodbye to the complexities of data export and hello to streamlined, in-database data quality management with digna.

To check whether your own database is among the platforms where digna runs this in-database analysis, see the list of digna integrations.

Frequently asked questions

What is an in-database data quality platform?

An in-database data quality platform analyzes data directly where it is stored instead of exporting it to an external system. digna works this way: it runs its analysis at the source and exports only the metrics needed for reporting, so the data itself never has to leave the database.

Why is exporting data for quality checks a problem?

The article names four problems with export-based analysis: it is time-consuming, it raises infrastructure costs for external storage and bandwidth, it adds security and compliance risks through new attack surfaces, and it can introduce inconsistencies between the source and the analysis platform during transfer.

Which databases does digna's in-database approach support?

The article lists Databricks, Oracle, Microsoft SQL Server, Teradata, Snowflake, Netezza, SAP HANA, MySQL, PostgreSQL, Timescale, MariaDB and Apache Impala. On each of them, digna analyzes the data in place and exports only the metrics required for reporting, leaving you in full control of your data.

How does in-database analysis improve data security?

Keeping data inside the database limits its exposure to external systems. Because digna does not move the data out for analysis, there are no extra environments for it to pass through, which reduces the risk of breaches, unauthorized access and third-party exposure in a strict regulatory environment.

How does digna monitor data continuously without exporting it?

It relies on its Autometrics feature, which profiles data continuously inside the database and captures key metrics for real-time analysis. Insights arrive as the data is updated, with no export step, and without the additional storage or processing power that export-based tools typically require.