For most businesses, data collection is not an issue but putting the data to use and getting valuable insight which drives better decisions. The solution to this challenge lies in finding a data integration tool which can manage and analyze different types of data from diverse sources. However, before data analysis, it is important to focus on data extraction.

Today, we will focus on the data extraction and how it can help you make the right decision. So, let us begin.

What is Data Extraction?

It is the process of getting raw data from the source and using that data somewhere else. You can extract data from PDF, excel spreadsheet, database, SaaS platform, web scraping, and more. It can then be stored at a destination such as data warehouse that is designed for supporting analytical processing. It consists of different types of data, unstructured data, and data that is poorly organized.

After consolidation, processing, and refinement with data extraction services, the data can be stored at a central location in cloud storage, on-site, or a hybrid for further processing and transformation.

Use Cases of Data Extraction

For example, an organization A wishes to monitor its reputation in the market. It might need different sources of data which consist of web pages, online reviews, social media mentions, online transactions, and more. With data extraction tools a business can extract data from various sources and upload it into a data warehouse where it is further analyzed and mined to get insight into a brand’s reputation.

Other examples where a business can benefit from data extraction consist of collecting different types of customer data to get a clear picture of donors, customers, financial data and more. It will allow a business to track performance and adjust its strategy accordingly. It further helps improve the process and monitor various tasks.

Process of Data Extraction

A business can extract data and benefit in several ways. But is important to understand the process of extraction and how it is done. Whether the source of data extraction is web scraping, Excel spreadsheet, SAAS platform, database, etc, the process of data extraction consists of the following steps:

• The first step is to look for changes in the structure of data- it includes the addition of new tables and columns. The changed data structures need to be dealt programmatically.
• The next step is to retrieve the target tables and fields from the records which are specified by the integration’s replication scheme.
• The next step is to extract the appropriate data.

The extracted data is loaded into a destination such as a cloud data warehouse which acts as a platform for BI reporting. The loading process must be specific to the destination.

Data Extraction vs Data Mining

1. Data mining is also known as knowledge discovery, knowledge extraction, and information harvesting. Data extraction, on the other hand, is known as web data extraction, web crawling, web scraping, and data harvesting.
2. Data mining is performed on structured data while extraction retrieves data from poorly structured or unstructured data.
3. The aim of data mining is to make the data useful for deriving insights. Data extraction is performed with the aim to collect data and store them well to be processed further.
4. The data mining process is based on mathematical methods for revealing trends and patterns. The data extraction process is based on programming languages or extraction tools for crawling various data sources.

Types of Data Extraction

The job of data extraction might be scheduled automatically, or an analyst might extract the data on demand as needed by the business. There are three main types of data extraction processes ranging from basic to complex. Here’s a look at them:

1. Update Notification

The simplest way of extracting data from a source is to have the system issue a notification when there is a change in the record. Most databases have automated mechanisms for the same so that they enable database replication. There are SaaS applications that offer webhooks to offer the same functionality. The most important aspect of change data capture is that it offers the ability to analyze data in real-time.

2. Incremental Extraction

Some data sources are not able to offer notification about an update but they can very well identify the records that have been modified and offer an extract of those records. During further extraction steps, the data extraction code requires identifying and propagating changes. A probable drawback of incremental extraction is that it might fail to detect the deleted records in the source data as there is no way it can see a record which no longer exists.

3. Full Extraction

The first time a source is replicated, it is important to perform full extraction. Some data resources don’t have a way of identifying the data which has been changed. Reloading the entire table might be the only solution for data extraction from that source. Full extraction often includes high volumes of data so it can put a load on the network. Thus, it is not the best option and one can avoid it.

Data Extraction Tools

Earlier, developers used to write their own ETL tools for data extraction and replication. It only works when there is a single or a few data resources. However, when there are complex or numerous resources, the approach can prove to be time-consuming and might not scale well. With more data sources, the likelihood of some or other needing maintenance increases. So, here expert companies like WebDataGuru can help scale your business with the power of data in the most efficient manner.

It can be difficult to deal with the changing APIs, when a source changes its format, or when the script has an error which goes unnoticed leading to poor decisions. All this might become a maintenance challenge.

A ray of hope for businesses is the data extraction tools. The process of data extraction doesn’t need to be painful. Cloud-based ETL enables a business to connect structured and unstructured sources of data to the destinations without any code and without any stress of compromise with data extraction or loading. Extraction tool makes it easy for anyone to get access to the data who needs it for analytics. These tools offer more control, simplified sharing, accuracy, and increased agility.

Unlock, Load, and Stay Ahead with Powerful Data Extraction

Data is not just a key but a stepping stone for every business in today’s era. Everything has its pros and cons but with data, you can get more benefits than anything else. Data brings in the best possibilities with its historical analysis and study. WebDataGuru’s extraction tools always provide the competitive edge that you need according to your particular business.

So, why are you still waiting? Get a free demo today!