Scaling up your business through data automation

Data automation allows you to fully utilize available resources to achieve accelerated results and increase your business’s value. There is no reason you shouldn’t employ data automation in your business process. Do it right now, and watch your business scale up.

Data automation

What is data automation?

Data automation uses technology and software to collect, organize, and analyze data. 

Data automation can be applied to various data types, including structured data (flat files and databases) and unstructured data (images, text, voice, and video). It can also be used across different data sources, such as internal databases, external databases, cloud-based data sources, and data from third-party applications, web services, and API. 

Data automation can be implemented using various technologies, such as robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and data integration tools. While AI and ML technologies can automatically analyze and derive insights from data.

Businesses, data scientists and analysts can free up time to focus on higher-value activities such as developing marketing strategies and making data-driven decisions by automating repetitive tasks such as data entry, processing, and analysis.

What can be automated with data automation?

Data automation can make marketers’ lives much easier by automating various tasks, including:

Data Collection

Data automation tools can collect data from various sources, such as social media platforms, website analytics, and customer relationship management (CRM) systems.

Data Transformation and Enrichment

Data automation can transform data from different sources into a unified format, enabling easy analysis and visualization. For example, it can convert currencies from different campaigns or group similar metrics that different platforms give different names (e.g., price and costs).

Data Analysis

Data automation tools can analyze data and generate reports, dashboards, and insights to guide your marketing efforts.

Data-intensive processes

No one is immune to basic human error, especially when dealing with data-intensive processes. One of the best ways to handle these processes in a more efficient and less error-prone manner is to employ data automation. Data automation helps you to maintain consistency, since processes will no longer heavily depend on human involvement.

Business benefits of data automation

So, what does that mean in real business terms? What benefits can businesses expect from automating their data?

1. Enhanced cost-efficiency and consistency

Data automation can reduce high costs since you’ll need less manual labor to handle data handling tasks. According to research by the Gartner Group, almost 85 percent of big data projects are predicted to fail. Big Data automation allows data to be analyzed and understood many times faster and more effectively, and in extreme cases, it will enable handling data that could not be analyzed manually. 

This, in turn, leads to more quality insights and opportunities to scale. The more you adopt automation in the initial data collection, storage, and processing stages, the fewer resources you’ll need to ensure and maintain high-level data quality.

2. Removal of data-intensive processes

No one is immune to fundamental human error, especially when dealing with data-intensive processes. One of the best ways to handle these processes more efficiently and less error-pronely is to employ data automation. Data automation helps you maintain consistency since processes will no longer heavily depend on human involvement.

3. Improved operational speed and competence

Markets are changing rapidly, and competition in every field grows as boundaries are replaced with interconnections. Operating based on data insights is crucial to becoming an industry leader in delivering high-quality, customer-centered services. Time is essential and a significant factor in any business’s sustainability, growth, and development. 

Manual data handling takes significantly more time than its automated equivalent. Significant time loss occurs during decision-making in the initial stages of defining source data standards.

4. Removal of manual decision-making

Before the introduction of data automation, most decisions were driven by professional judgment in combination with supporting manual data calculations. All work – data source collection, extraction, cleaning, analysis, and storage, was performed manually. 

Manually maintaining large-scale decentralized data is highly costly, error-prone, and time-consuming. This is why data automation is crucial for your business to operate efficiently.

Don’t waste the talent and potential of your data scientists.

Data scientists spend about 80 percent of their time on data preparation and cleaning. However, many data handling processes do not require human intelligence since they mainly consist of routine and recurring tasks. 

Data automation is an excellent solution for these processes. It allows your data scientist to focus on tasks that engage and require their deep competencies and creativity instead of getting involved in time-consuming tasks of basic-level data analysis.

What data automation challenges do businesses face?

While data automation has many benefits, it can also have some limitations. A few potential data automation limitations and challenges include:

Initial investment cost

Implementing data automation tools or systems involves initial investment costs or subscription charges. However, once data automation is set up, it will save an organization money in the long run. 

Evolution of team roles

When data engineers no longer focus on manual tasks, they can do more impactful and vital work. Employees who previously focused on such tasks may find their roles shift into new areas, such as determining how to effectively leverage data automation solutions and ensuring systems are configured correctly. Be prepared to examine how team roles may need to evolve and how you can shift or broaden employee roles. 

Learning curve

Introducing a new tool or technology includes a learning curve. Data automation is no different. It may take a while for employees to become familiar with data automation tools and learn to use them to their full potential. 

Human intervention is still needed for troubleshooting

While data automation can streamline data integration and reduce manual effort, critical workflow tasks may still require human intervention. For example, when a pipeline failure occurs, human intervention may be needed to understand what happened and how to fix it.

Data automation tools

Data automation tools, such as ETL, can automate data processes. Several companies make data automation tools, but finding the right tool for your needs can be challenging. A few key things to look for in a data automation tool include:


The data automation tool should be able to scale to meet the growing demands of data processing quickly.


The tool should provide logging and monitoring capabilities to ensure data integrity and accuracy and help troubleshoot when issues arise.


The tool should have robust security features like encryption, access controls, authentication and auditing.


The tool should seamlessly integrate with other data tools and systems, such as data warehouses, data lakes, analytics platforms and visualization tools, to enable end-to-end data automation workflows. It should also adapt to various data sources, formats and workflows. 

Ease of use

The tool should allow users to easily configure, design and manage data automation workflows without requiring extensive coding or technical skills.

Using data automation

Data automation uses intelligent processes, software, equipment, or systems to collect, process, or store data. allows your business to focus the newly available resources on more critical tasks, investments, and innovation, bringing more value to your business, such as deep and sophisticated analysis and freedom for your employees to experiment and improve existing products or solutions to exceed customer expectations.

Ultimately, it describes a method of replacing manual work with machines and software, including the application of artificial intelligence.

For your business, data automation allows you to fully utilize already available resources to get accelerated results and increase the value of your business by realizing the hidden potential of your products or services.

There is no limit to the potential of data automation. Data automation is helping businesses optimize their processes and discover new business potential. It is essential to set up a good data automation strategy. 

If needed, engage the help of an experienced partner. There is no reason you shouldn’t employ data automation in your business process

Do it right now, and watch your business scale up.

Data Automation FAQs

How does data automation work?

Data automation entails leveraging technology and software to integrate and automate tasks and processes related to an organization’s data. It uses algorithms, scripts, and tools to automatically collect, process, transform, and analyze (ETL) data without requiring manual human intervention.

What is a data scientist?

Data scientists extract, analyze, and interpret large amounts of data from various sources, using algorithms, data mining, artificial intelligence, machine learning, and statistical tools to make it accessible to businesses.

What data automation tools are used the most?

It depends on the case of the company and the business. At Proekspert, we can use several tools, some of which are listed here.

What companies use data analytics?

Proekspert business intelligence and data analytics services help every company or organization transform data into actionable and relevant insights. This enables informed strategic decisions, improved operational efficiency, and business productivity.

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