What is data validation?
Data validation is the process of ensuring data is accurate and clean before it is imported into or processed by an application or automated system.
Why is validating data important?
Without a data validation process, businesses could end up erroneously using inaccurate, outdated, or irrelevant information to inform their decision-making. It is important to note that the average American business has 347.56 terabytes of data.
Considering the sheer amount of data that businesses generate from potentially hundreds of applications, it becomes readily apparent that assuring the quality and integrity of that data is exceedingly critical. This explains why more and more companies are investing in data validation software.
The Current State of Data Validation Practices
According to research from Gartner, poor data quality costs businesses on average $9.7 million per year. Unfortunately, many businesses are ignorant of the impact of poor data quality or have difficulty creating a business justification or business case for data validation initiatives.
As a result, there are an alarming number of enterprises relying on low-quality, erroneous, or incomplete information when making vital decisions about the future of their ventures, which can result in compromised strategic planning and inferior service delivery.
How is Paxata addressing data validation concerns?
At Paxata, we know that the more informed a business is, the better it performs. That’s why we have worked tirelessly and diligently to create a self-service data preparation application that unifies key data profiling and data validation capabilities.
Our Paxata Rapid Data Profiling, part of the Paxata Self-Service Data Preparation application, allows business analysts to quickly scan their data in its entirety and then visualize anomalies, outliers, and patterns with the help of built-in, intelligent algorithms. Once the scan is complete, Paxata generates a summary scorecard showing an assessment of the content and its quality.
From there, business analysts can continue to shape, validate, and transform the data for their specific use. This can be done in a number of ways, including: conforming data into required patterns, standardizing data variations, applying string, text, and date functions, and much more.
These industry-leading data validation methods give business consumers and analysts an intuitive, visual, and interactive means by which they can onboard, profile, and create quality information.
What separates Paxata from other data validation tools?
There are several different platforms that businesses can use to conduct data validation checks and monitor the quality of the data they generate — but few of them offer the convenience and speed that Paxata has to offer, nor do they provide the same business user-friendly experience.
Clicks, Not Code
One of the most compelling advantages Paxata offers is our visual, easy-to-use interface. There is no need for end users to understand code or navigate their way through onerous amounts of figures and numbers. Neither do they have to rely on scarce IT developers to perform data validation and data cleaning tasks.
Instead, our data validation capabilities use smart, machine learning algorithms that intelligently process and display all of your information in a visually-appealing, hassle-free, tabular format. This allows analysts to explore their data in an interactive way, with common input controls and navigational components they’ve already become accustomed to using in programs such as Excel or Google Sheets.
Paxata also simplifies the data validation process by using automated algorithmic intelligence to recognize and correct errors or duplicates. Visual guides direct the user and provide recommendations on how the data should be standardized.
This significantly reduces the likelihood of human error, improves analytical results, and ensures that data is handled in accordance with business processes.
Built For Scale
Many traditional data preparation or data validation tools are limited in the amount of data they can ingest to provide insight into the quality of the data. Instead of working on the full body of data, these tools rely on small samples that are then used for visual profiling and exploration. The risk is that the sample often does not provide a full picture of the data, misses outliers, or generally requires multiple, time-consuming iterations to catch all anomalies.
Paxata, on the other hand, is powered by an adaptive, elastic architecture that can scale out and contract as needed. In fact, Paxata can process a full spectrum of data preparation operations on datasets with up to 20 million rows and 198 columns with an aggregate median response time of less than five seconds.
Our ability to handle large amounts of data without compromising on speed or convenience is a major contributing factor to the success of our platforms and the positive feedback we receive from the brands who utilize our software.
Data validation statistics to consider
- Experian published a research paper on data quality recently that offers some interesting statistics suggesting 95% of C-level executives believe that data is an integral part of forming their business strategy.
- The same report suggests 65% of retailers say inaccurate data continues to undermine customer experience efforts.
- A 2016 Harvard Business Review article suggests the cost of bad quality data to the US is estimated at $3 trillion per year.
- Paxata recently published a research paper on The State of Data Quality that shows only 15% of organizations have actually deployed (and just 40% have developed) a mature data quality mode.
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