The rise of automated data processing: A comprehensive guide

Are you still using an Excel spreadsheet to store data points? Or maybe you’re copying and pasting data from your source system into your target system. You’ll be happy to know that with the rise of automated data processing, you can automate everything involved with organizational data, from extraction to loading and transformation.

So if you’re interested in automating data processing, this guide is for you. Below, we’ll cover the benefits of automated data analysis and how you can use artificial intelligence and data processing to make your life easier.

Benefits of automated data processing

Are you tired of manually collecting, cleaning, and structuring organizational data? Automated data processing may be a good solution for you. 

Here are some benefits you can experience soon after introducing automated data processing into your business:

• Increased efficiency
• Improved accuracy
• Cost savings
• Scalability

Increased efficiency

Without automated data processing, you’re left manually processing and cleaning raw data, and this is tedious. 

But when you utilize a CDP (Customer Data Platform) to process this information for you within seconds, you can complete these repetitive tasks faster, increasing efficiency. 

Improved accuracy

The quality of your data also improves when you automate data processing. This is because you aren’t going through the error-prone process of processing and managing data manually. You’re utilizing automation to consistently collect and store accurate information.

Cost savings

Automated data integration is also much cheaper. For example, you’ll probably spend money on a CDP and a few classes to teach your employees about data literacy, and that’s it!

But when you’re manually collecting first-party data, you’ll have to pay multiple employees. If there are any mistakes, this money will come out of your pocket.

Scalability

The last benefit we’ll be looking at is scalability. 

If you’re a startup, you can still manage data manually, even though it’s impractical. But manual data management becomes almost impossible if you grow into a larger organization.

This is where automated data processing can help. It doesn’t matter how much data you’re processing; a CDP will effectively process all organizational data.

Challenges in implementing automated data processing

However, not everything is smooth sailing. These are some challenges you can expect to face:

• Data quality 
• Security
• Integration with legacy systems
• Cultural resistance 

Data quality

Ensuring data quality is probably the biggest challenge you’ll experience when automating data processing. 

An effective way to avoid this is to use a CDP that’ll extract, clean, transform, and load data for you, minimizing human intervention and potential mistakes.

Security

Many businesses think that if they implement automated data processing, the risk of data breaches will increase because of the limited human involvement. 

However, this couldn’t be further from the truth. As humans, we’re flawed and tend to make mistakes that can lead to data breaches. 

Fortunately, automation reduces human involvement, thus, reducing the chances of mistyped, confusing, and inaccurate data points.

Integration with legacy systems

Retailers currently spend 58% of their IT budget on maintaining legacy systems.

So when you’re automating data processing, you also want something that’ll integrate with these systems and eventually end your reliance on them.

Cultural resistance

Becoming a data-driven organization by automating data processing also results in resistance from employees. 

Many employees won’t understand the value of automated data processing, so you’ll have to educate them by creating online courses and seeking the help of data consultants.

Automated data processing tools and techniques

These are a few data processing automation tools and techniques that’ll kickstart your journey:

• Data extraction
• Data cleansing
• Data transformation
• Data loading 

Data extraction

When introducing automated data processing, you want to first consider the data extraction method you’re using:

• Full extraction
• Incremental stream extraction
• Incremental batch extraction

Full extraction refers to loading everything from your source system into your target system. This is often used when populating a target system for the first time.

You could also opt for incremental stream extraction, where you only extract data that has changed since the last extraction.

Your final option is incremental batch extraction, which involves extracting data in small batches instead of all at once.

Data cleansing

After you’ve excreted data and loaded it into your target system, you want to clean it. This often calls for removing duplicate or irrelevant observations, fixing structural errors, filtering unwanted outliers, and validating your data.

Data transformation

When transforming data and converting it into more usable formats, you want to use data soothing, which is the process of automatically removing noise from your dataset. This makes your data much easier to understand, so analysts and marketers can use it to make more informed decisions.

Data loading

When it comes to loading data, you have two options:

• ETL 
• ELT

ETL is a better option if you’re loading small amounts of unorganized data, while ELT is better when conducting large transfers.

How Lytics can help you with automated data processing

Lytics can help you automate data processing by allowing you to extract, clean, load, and transform organizational data. Lytics automates everything involved with data processing, so you don’t have to do it manually. 

From here, Lytics organizes your customer data into individual, 360-degree customer profiles, giving you a detailed view of customer behaviors across social media platforms.

Lytics also offers everything you need to connect your data warehouse to the rest of your MarTech stack, making it a must if you’re a data analyst, scientist, or engineer.

Automate data processing with Lytics

With the endless amount of data companies are collecting, automating data processing is necessary. You’ll save time and money while improving the quality of your data.

So if you’re thinking about implementing data processing automation into your business, try Lytics. The Lytics CDP extracts, analyzes, and loads your data, so you don’t have to do this manually.