Data February 19, 2024
5 min read
How to Boost Scalability with Automated Data Processing
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Lily McFadden
Lily McFadden Peaka / Tech Evangelist

How to Boost Scalability with Automated Data Processing

Whether you are a startup or an established business, automated data processing (ADP) can help you gather and share data. To scale your business, focus on improving efficiency as the workload expands.

Automate your data, automate your business

Recent research shows that most businesses spend 50 percent of their time on mundane data quality tasks. No matter how detail-oriented your team is, mistakes are bound to happen. With Peaka’s expertise and automated data processing software, you can transform data into a more comprehensible format. The following sections examine the top benefits of automated data processing to boost scalability.

Top 10 Benefits of Automated Data Processing

Use an automated data processing tool to process continuously while eliminating errors. These tools identify trends, patterns, and correlations of data. Here are the top 10 benefits of ADP.

1. Boosts Efficiency

The propensity for human errors plagues manual data processing. For example, assigning your staff to clean data and validate orders is a tedious task that causes mistakes. If there are delays, you risk losing your customers. With automated data processing, you don't have to spend time managing high-volume data.

ADP does all the heavy lifting to reduce the costs associated with errors, so you can focus on critical operations. If you're looking for a reliable platform to help build projects and bring your data together, Peaka has all the necessary tools.

2. Improves Data Security

Data breaches can occur when you least expect them. The best way to keep your sensitive data safe is by using automated data processing software. To start with, data automation simplifies security processes like threat detection, data encryption, and access control. Beyond that, it ensures secure data validation and timely recovery.

3. Avoid Creating Data Silos

Data automation eliminates the barriers that hurt productivity and promotes data accessibility. Typically, data silos are separate from the rest of the business and are under the control of one business unit, such as a department. With an automation strategy in place, you can unlock the silos to bring data from disparate sources.

Since automation gives users greater autonomy, they can make data-driven decisions. Regarding automation, Peaka can connect you to almost anything, including GraphQL API and REST. These tools process data from different sources to suit various tasks. The other benefits of eliminating data silos include:

  • Centralized data storage

  • Enhanced collaboration

  • Improved data accessibility

  • Efficient reporting

Non-compliance with data privacy and safety can attract hefty penalties. The best strategy to navigate complex data privacy regulations is to use automation tools to assist with privacy laws that protect sensitive information. When you meet the legal requirements to manage data subject requests, you can create inventories that maintain the trust of the shareholders.

5. Enhances Productivity

Another way to scale your business is by eliminating repetitive tasks, allowing your employees to focus on what matters most: Productivity. ADP saves time on tasks like data entry. Best of all, it frees your workers from mundane chores to focus on innovative activities. By eliminating the need for extra human resources, you boost production.

6. Cost and Time Savings

Automation ensures your employees do more work within a specific timeframe. The money you've been using to pay your employees can now be channeled away from data processing tasks. Even better, you eliminate the bottlenecks and correct them. Aside from saving on hiring more employees, you abolish repetitive processes. As a result, ADP reduces the expenses associated with errors.

If you employ a data analyst, they may be wasting time and resources by retrieving data from a sheet instead of focusing on tasks like statistical analytics. However, with data processing software, the analyst can concentrate on operations that enhance business growth. Of course, you can eliminate the headache of hiring a large team altogether.

7. Standardized Data

A key aspect of data automation is tracking and measuring key performance indicators (KPIs). When information is entirely handled by humans, it's likely to contain errors. Measure the effectiveness of your strategy; with a reliable ADP tool, you'll get standardized data to diagnose the pain points and make informed decisions.

8. Improves Data Accuracy

Inaccurate data can lead to compliance violations, financial losses, and damage to reputation. ADP improves data accuracy and eliminates the costs associated with such errors. By relying on software, you increase the accuracy of data analysis.

When data is organized, you can handle large datasets accurately. Since every step in automation is recorded digitally, you get auditable records and end up paperless.

9. Real-time Data Analysis

Imagine the frustration that comes with manually sifting through large volumes of data. Sectors like e-commerce, logistics, and customer service need real-time data for accurate decision-making. If you rely on manual data, you won't get accurate results.

Adopt ADP software to streamline your operations. Your clients will enjoy your services if you collect and analyze data within minutes.

10. Improves Customer Experience

If you can handle data without error, customers will have a better user experience. Skip the tedious manual processes and prioritize your clients’ needs.

The Bottom Line

Automated data processing can scale up your business through increased productivity and doing more within a specific timeframe. It relieves you from manual tasks like data collection, cleaning, analysis, and reporting. When done correctly, you can analyze large amounts of data with few resources.

With Peaka, you can integrate all your data sources—relational and NoSQL databases, SaaS tools, and APIs. Query them as a single data source immediately.

See Peaka’s growing library of custom integrations.

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