Data validation has become a genuine buzzword in the business world, but too many entrepreneurs, managers, and sales specialists still don’t understand its true value. Data validation is fundamental because people, things, and organizations produce enormous amounts of data every day.
According to the report, it would take you approximately 181 million years to download all the data from the Internet. Another study reveals that 1.7MB of data will be created every second for every person on earth. The numbers are mind-boggling, but they give businesses the opportunity to analyze potential customers and learn almost everything about the target audience.
The only thing that matters is to keep your data sets neat and clean. In this post, we will discuss the concept of data validation and explain to you all of its features and benefits. Let’s begin!
Data Validation: Definition and Benefits
If you want to understand data validation, you need to learn what it really means. By definition, data validation represents the process of checking the accuracy and the quality of source data before using, importing or otherwise processing information.
Although it may seem like a routine and more or less irrelevant process, the truth is that data validation has the power to make or break entire businesses. How come?
Well, it turns out that data validation can bring you a wide range of practical benefits and drastically improve professional efficiency. Here are some of its major advantages:
– Improves data accuracy: The first benefit of data validation is fairly obvious – it helps you to clear and systemize datasets. That way, your customer-related details become better and more accurate, thus helping you to get a precise overview of your target group.
– Enables more accurate decision-making: Every decision you make is (or at least should be) based on real-world information. But if you don’t have accurate data at your disposal, how can you hope to bring trustworthy decisions? You cannot do it without data validation, so you better invest in this process to ensure better decision-making.
– Reduces time-waste: The worst thing you and your team members can do is spend hours or even days preparing special offers for prospects who do not exist. It’s a huge waste of time that can have a tremendous impact on your business results, but you can eliminate this risk through data validation.
– Generates a higher ROI: It is much better to have 10 verified leads than to target 100 irrelevant prospects. After all, those 10 clients will generate a much higher profit in the long run. Therefore, the return on investments skyrockets when you validate data and reach out to qualified leads exclusively.
– Boosts productivity: Data validation also allows you to boost professional productivity and make your team more efficient. Namely, your employees won’t have to waste time on unverified leads and so they will be able to make more in a shorter amount of time.
4 Steps of Data Validation
Data validation is a complex process that varies greatly from industry to industry, but we can recognize a few common patterns in almost every project. Here’s how the process functions in the vast majority of cases:
1. Make a plan
The first thing you need to do is to make a plan of work because it helps you to keep track of all data validation activities. The most important detail is to specify your goals and clearly define the targets of data validation such as schedules, KPIs, and so on.
2. Conduct the validation process
The second step is critical as it suggests testing and validating all of your data libraries. This is where raw numbers turn into meaningful and well-categorized datasets.
3. Data formatting
It’s not enough to systemize information as you also need to format data so as to comply with the overall organizational procedures and regulations. Data formatting enables every user within the system to access and interpret information accurately.You can check it here online assignment help and best essay writing service.
4. Sampling
The last step is sampling, a process in which you take a small amount of data and test it to learn whether it really fits your data validation plans. In this case, it is important to clarify your methodology and expectations by determining sample percentages, acceptable error rates, etc.
7 Data Validation Methods
Data validation consists of multiple procedures and techniques, but seven methods make a quintessential segment of the process. All of the data validation steps we mentioned above can be done using one of the following methods:
· Range check
This is one of the basic and most common data validation methods. Just like the name suggests, a range check is used to define the limits of a given category. For example, you can use it to set upper and lower limits and accept each number between 5 and 55.
· Type check
Using this method, you can check whether the right type of data is used. For example, data validation is supposed to make sure that you used numbers instead of text-based inputs.
· Check digit
This method is focused on number series in particular. It’s a valuable technique that depends on the nature of your number formats and entries, so it’s up to you do define parameters and check digits correctly.
· Length check
Sometimes you’ll want to limit inputs to a certain number of characters. For example, datasets should contain inputs ranging from 10 to 40 characters only. Length check will make sure to filter and sort entries with the targeted limit.
· Lookup
If your dataset is only projected to contain a certain number of values, then you can use the Lookup method to reduce errors. For example, there are only seven days in a week and you can use this fact to simplify data entering, enhance accuracy, and speed up routine procedures.
· Format check
You’ve probably guessed already that format check is designed to test the accuracy of a given format within your data list. You can use this method to check all sorts of formats, including highly tailored and classified inputs.
· Presence check
Some input fields are more important than others, which is why you cannot afford to leave them blank. If your database should contain such valuable entries, you can utilize the presence check to see whether these fields are blank or not.
Main Features of Data Validation Tools
Data validation is often a boring and monotonous process, especially if you keep doing it manually. This is why we strongly recommend you to use data validation tools to get the job done simpler, faster, and more accurately.
There are, however, hundreds of software solutions available online, so you need to know the main features of data validation tools. Here are some of them:
– Minimalism: You should be looking for a tool that demands little to no setup efforts. Besides that, it is always a good idea to use a platform with a broad scope of predefined checks.
– Simplicity: Another feature you should strive for is simplicity. After all, you don’t need a complex tool but rather a user-friendly platform that requires zero programming skills.
– Reporting: Of course, a reliable data validation program must be able to design all-encompassing reports. Make sure to find a tool with in-depth but simple analyses of failed checks.
– Multiple tabs: If you are in need of a speedy data validation platform, do your best to find one that can explore multiple tab sets in the entire data library. That way, data validation platforms eliminate task duplications.
– A built-in scripting language: Experienced users may want to design additional data verification scripts. If you are one of those users, ask for a built-in scripting language as well.
The Best Data Validation Platforms
It’s not easy to choose the best data validation platform even if you are fully aware of the most important features. This is why we prepared for you a quick list of data validation tools that we consider to be useful for almost every kind of team or organization. John who works at best essay writing service and dissertations services think:
– Datameer: It is one of the most comprehensive data validation platforms with advanced features based on machine learning.
– Query Surge: This platform conducts data validation tests around the clock and makes sure to keep your data libraries smooth and simple 365 days a year.
– ICEDQ: The platform is easy to set up and it can identify shortcomings in your data warehouse almost instantly.
– DbFit: DbFit is a test-driven data validation tool. It supports all of the major databases and allows you to run tests directly from your favorite browser.
Of course, there are many other data validation programs out there, so we strongly encourage you to check out additional options.
Conclusion
Data validation is a fundamental business concept, but it somehow gets neglected way too often. No matter what you do for a living, you should learn the basics of data validation and use it to improve professional performance. In this post, we showed you:
– The definition and the benefits of data validation
– Four steps of data validation
– Seven data validation methods
– Main features of data validation tools
– The best data validation platforms
Do you already use data validation in your work? Which strategy do you consider to be the most important in this field? Let us know in the comments so we can discuss this interesting topic with you! Don’t forget about using essay writing service UK and professional writing services