4 Benefits to Utilizing Data Analytics for Your Business

4 Benefits to Utilizing Data Analytics for Your Business

There are so many reasons to invest in data analytics. Whether you’re looking to improve productivity, cost savings, or decision making, data analytics can help. When you want to understand your customer better, choose data analytics. Read on to discover the four benefits of utilizing data analytics for your business.


There are so many day-to-day tasks that could be automated. Let’s consider just one department: human resources. There’s no need for people to manually push buttons to make payroll processing or candidate screening happen. Data processing can be significantly automated, leaving your workforce with more time to spend in other areas. AI doesn’t need to eliminate human jobs, but rather it can be a massive aid to the people doing those jobs.


Intuition is excellent, but intuition paired with statistics leads to more consistent results. Data analytics can go hand-in-hand with your employees to take decision making to a new level. Data is stellar at predicting future trends, so couple your workers’ minds with hard numbers, and you’ll see near-immediate results.

Predictive Modeling

Predictive modeling may feel futuristic, but it’s the same as playing out a scenario in your head. The only difference is the accuracy that data analytics can provide. Financial services can make great use of predictive modeling to quickly assess someone’s creditworthiness or pick out fraud risks. To say that data analytics tools are smart is an understatement!


In the modern era, customers expect a personalized experience. They want emails to address them by name and advertisements to cater to their unique sensibilities. Without data analytics backing your company’s personalization efforts, your customers will be left wanting. With modern analytics, you can easily determine niche interests and appeal to your customers in a way that’s beneficial for both parties. You make the sale, and your customers get the product or service they want!

Now that you know these four benefits to utilizing data analytics for your business, connect with Chain-Sys Corporation to determine which data analytics tools are right for you.

Differences Between Data Masking and Data Encryption

Differences Between Data Masking and Data Encryption

When you search for data security, you probably come across terms like “data masking” and “data encryption.” Lots of times, these words can sound like nothing more than synonyms. In this case, these terms refer to different processes, each with its own merits. Read on to learn more about the differences between data masking and data encryption.

Data Masking

People sometimes refer to data masking as “data de-identification,” and that term describes the protection process well. Instead of keeping sensitive parts of data on display, data masking replaces these chunks of data with random values. Therefore, masking hides identifiers and makes data useless to bad actors.

The three main types of data masking are static data masking, dynamic data masking, and on-the-fly data masking.

Static masking saves the masked version in your original database and sends a backup to a new location. Dynamic masking keeps all your data inside other systems of your development environment, giving you on-demand access. Finally, on-the-fly masking uses a process called extract, transform, load (ETL) to store masked data in the development environment.

Data Encryption

Like data masking, encryption also turns data unreadable with algorithms. However, you can think of encryption as a code. If you have the key to the code, then you can read the data it hides. If bad actors figure out the key with enough force, they can also read the code. Decrypting data makes it vulnerable, so the best use for encryption is for data that doesn’t need to be functional, such as data in storage.

How They Differ

Should you choose encryption or masking when you’re looking for processes to help with data breach prevention? The best data security strategies employ both processes for different reasons. You should secure data that you and your team are actively using with masking, while it’s best to protect data in storage with encryption.

Now that you know the differences between data masking and data encryption, you should contact ChainSys for more information on data security.