A voluminous increase in unstructured data has made data management and data extraction challenging. The data needs to be converted into machine-readable formats for analysis. However, the growing importance of data-driven decisions has changed how managers make strategic choices. A research study shows that businesses that engage in data-driven decision-making experience 5 to 6 percent growth in their productivity. Modern data extraction tools with built-in scheduler components help users automatically pull data from source documents by applying a suitable data extraction template and load structured data to the target destination. These data extraction tools are now a necessity for majority organizations.
Understanding data extraction and why it is significant for organizations to extract insights from data? What are the key features of a data extraction tool? Read on to find out.
What is Data Extraction? How Can it Help Businesses?
In simple terms, data extraction is the process of extracting and gathering data from semi-structured and unstructured sources, such as emails, PDF documents, PDF forms, text files, social media, barcodes, and images. How is unstructured data extraction done? An enterprise-grade data extraction tool makes incoming business data from unstructured or semi-structured sources usable for data analytics and reporting.
For example, a real estate business might want to extract various data points, such as the tenant’s name, premises details, and rental amount from rental agreements. These agreements are generally in the form of unstructured PDFs – a mix of free text and tabular data. Extracting insights from data, especially PDFs, is challenging, as unstructured data sets are human-readable and machines require structured information to process it digitally for further analyses or integration with other IT applications.
Moreover, unstructured data extraction needs to be automated for faster and efficient insights. Therefore, automated data extraction programs are needed to streamline the entire process from start to end.
Data Extraction vs. Data Mining
People often confuse data extraction and data mining. The process of data extraction deals with extracting important information from sources, such as emails, PDF documents, forms, text files, social media, and images with the help of content extraction tools. On the other hand, data mining is a process used to look for patterns, anomalies, and correlations in their data.
Therefore, a data mining tool allows users to analyze data from multiple perspectives to identify patterns hidden in large data sets. Now that it’s clear what data extraction is, let us move on to its significance.
Importance of Data Extraction Tools
Many businesses are leveraging ETL tools for data management and converting unstructured data to structured format. These tools allow information users to break data silos, combine relevant data from multiple sources, convert it into a consistent format, and load it onto a target destination. Even though unstructured data is readable by humans, machines need structured data to process it digitally.
Therefore, ETL unstructured data is required to be extracted from its source and converted into a structured format using an automated data extraction solution.
The first step in the ETL process involves data extraction, which basically helps extract data tables from structured or unstructured source. The right tools and techniques allow the information trapped within disparate systems, such as third-party cloud-based tools and files, to be standardized and made ready for further transformations so ETL teams can easily extract insights from data.
In addition, extracting data and using data extraction tools offers numerous benefits, including:
Better Analysis & Decision Making
A study conducted by Forrester revealed that not more than 0.5 percent of the world’s data is analyzed and used. Document extraction software allows users to extract meaningful information hidden inside unstructured data sources.
For example, a company is experiencing a fall in revenue due to a shrinking customer base. The spreadsheet maintained shows the list of loyal customers and customer churn status for each month.
To analyze the trend in churn rate, the manager wants to extract the rows with churn status and aggregate them. This will help identify whether the company can retain its customers or not and decide upon the necessary measures, such as improvement in customer service, that should be undertaken.
With the help of a data extraction tool, the business can easily extract this information. A data extraction solution can also combine the extracted data with sales, product, marketing, or any other type of data to gain more insight into the reasons for the increasing customer churn rate.
Enhanced Data Quality
Many businesses still rely on their employees to manually extract insights from data. For example, converting unstructured PDF to structured data is an arduous task.
Imagine, how taxing would it be for, let’s say, a marketing executive to obtain important customer information trapped in PDF files. If the executive wants to extract email addresses from PDF files, it will waste time and negatively impact data quality. This can also result in errors, such as incomplete records, missing information, and duplicates.
Data fetching tools do not only guarantee valuable business insights but also save time, money, and resources involved in manual extraction while ensuring data accuracy. Hence, investing in a data extractor tool and data extraction programs is beneficial and positively impacts the ROI.
Increased Data Accessibility
Forrester deduced that a 10% increase in data accessibility could lead to a more than $65 million increase in net income for a typical Fortune 1000 company. An effective data extraction solution enables users to gain full visibility of incoming data, hence simplifying data processing. Data extraction tools may seem costly initially, but have a positive effect on the bottom line in the long term.
Improved Data Efficiency
Employees are a critical asset of any business. An employee’s productivity directly impacts an organization’s chances of success. An automated data extraction software can help free up employees, giving them more time to focus on the core activities instead of repetitive data collection tasks.
Automating data extraction makes it possible to streamline the entire process from the time data enters the business to when it is stored in a data warehouse after being processed, eliminating the need for manual work. For instance, the sales department can automatically extract data from a PDF invoice to an excel database. It is important to invest in the right data extractor tool to be able to achieve this level of automation.
Features of Data Extraction Tool
Opting for the right database extraction software, which meets the data preparation requirements of an organization, is vital for information management. The data fetching tool should be able to transform incoming raw data into information that can generate actionable business insights.
A few important points that an organization should consider while looking for a robust data extraction tool include:
Extract Document Data & Information from Multiple Formats
Organizations receive data in structured, semi-structured, or unstructured formats from disparate sources. Unstructured data extraction tools for unstructured data help structure it. Most business intelligence tools can process structured formats directly after some scrubbing. However, an ideal PDF scraping tool must also support common unstructured formats, including DOC, DOCX, PDF, TXT, and RTF, enabling businesses to make use of all the information they receive.
Real-Time Data Extraction for Big Data Analysis
Having access to timely data is imperative for better decisions and smooth business operations. Many businesses are dependent on batch data extraction, which processes data sequentially depending on the user’s requirements.
This means that the information available for analysis might not reflect the most recent performance data or crucial business decisions have to be based on historical data. Hence, an effective automated data extraction tool should enable real-time extraction using automated workflows to prepare data faster for business intelligence.
For instance, an employee is responsible for analyzing the inventory levels at the time of a year-end sale. To make this possible, the business will need real-time extraction of data points, including order ID, items sold, quantity, amount, etc. from the sales invoices to keep a check on the current inventory levels. A top data extraction tool will have the ability to perform complex analysis efficiently.
Reusable Templates with Report Extraction Software
The right data extraction software should allow the user to build an extraction logic that can be applied to any unstructured document of the same layout. This compensates for the need to build extraction logic anew for each incoming document.
Built-in Data Quality & Cleansing Functionality
The data extraction tool should be able to identify any variations and cleanse the data automatically according to business rules defined by the user. For example, if a company uses an extraction model to extract order quantities and order details from PDF invoices. The PDF data extraction software should be able to detect and delete any orders with negative quantity values.
It is important for these data extraction programs to have an intuitive interface where business users can easily design different data extraction templates. It should allow easy data handling with little to no coding involved.
Export Data to Widely-Utilized Destinations
A smart data extraction software should allow users to export the converted data to popular destinations, such as SQL Server, Oracle, PostgreSQL, and various BI tools like Tableau. They enable businesses to access meaningful information faster for timely decision-making.
Start Extracting Data from PDF & Reports with ReportMiner
Astera’s ReportMiner, one of the best data extraction tools, automates unstructured data extraction to generate meaningful information and insights with features like workflow orchestration, email/FTP/folder integration, a built-in job scheduler, automated name, and address parsing, and auto-creation of data extraction patterns. Hence, you can automatically extract data from pdf to excel or any other sources with ease.
The user-friendly interface of ReportMiner simplifies template-based data extraction from PDFs, PDF forms, TXT, PRN, RTF, XLS, XLSX, and COBOL. It enables business users to extract insights from data and build extraction logic in a completely code-free manner.
For a one-time extraction job, there are free data extraction tools that exist. However, if you have unstructured data coming in regularly, it’s best to purchase a data extraction tool for maximum benefits. Astera ReportMiner is surely one of the best data extractor tools, to satisfy your data needs.
Download a 14-day free trial and find out how you can avail yourself of a free extraction program, and streamline transformation, and loading of data trapped in unstructured data files with Astera ReportMiner.