Resolving the Data Extraction Services v/s DIY Tools Debate

From eCommerce websites and social media platforms to smart devices and financial transactions—businesses of varying sizes and scopes collect data from multiple resources. Why so? It is because data has become the most valued business commodity today. Leaders leverage data to gain intelligent insights and make informed decisions to fuel their growth.

In almost all instances, data is gathered through a process called data extraction. This article helps you understand the process and challenges associated with their solution. Further, it helps you resolve the DIY tools v/s data extraction services debate.

Data Extraction Process

In practice, data extraction is the process of gauging information from a source such as social media platforms, eCommerce websites, and financial or legal documents to name a few, and processing it to get useful information. It forms a crucial part of the ETP (Extract Translate Load) process. Enterprises leverage data extraction as an activity to establish the groundwork for successful analysis as well as enhance their decision-making.

Data extraction is often used while mining large databases or websites. Data mining firms can extract useful information from these sources via analysis and find what patterns exist within them.

Overall, the data extraction process involves majorly two steps—extracting and formatting. Raw data is taken from its original form and put into a more usable form in the first step. In the second step, the format of this extracted information is changed. If you want to mine tweets from Twitter, let’s say, you’ll have to extract individual tweets before analyzing them for trends.

Challenges in Data Extraction

The data extraction process is easier said than done. You need to invest a dedicated amount of time and effort to scrap out quality data from various resources. Any errors while extracting data or formatting can deviate you from the desired outcomes and might impede all your efforts. Some of the major obstacles that businesses face are listed here:

• Poor Quality Data

Erroneous or incomplete data can hinder data analysis as well as decision-making processes for businesses. For example, if an organization has incorrect information about what services its customers want, it won’t be able to target its marketing campaigns effectively or predict future customer behavior.‍

Or take another case in point: if a sales manager doesn't know how much inventory is there on hand, s/he might make decisions on the basis of incorrect assumptions about their current stock levels. Hence, poor data quality can negatively impact business strategies.

• Non-Standardized Formats

As obvious, there's no standard format to work when data is extracted from multiple sources. This is because different sources have multiple data in different formats. It is up to the management to figure out what these formats are and how to use them in the best possible way. This might take time and dedicated effort, especially when you are unfamiliar with the source material or if it is time-consuming or difficult to access.

• ‍Lack of Information Access

‍Data is generally stored in PDFs and other such documents that cannot be searched easily, making it difficult to find the needed information in a timely manner. Moreover, data can be stored in multiple locations which makes it challenging to locate all the information as and when you need it.

Besides, it’s not always easy to tell what is missing. Often, the only way to figure this out is to try extracting it. However, the problem here is that there’s a chance that you could fail in your attempt, resulting in wasted time and resources.

Solution: DIY Tools or Data Extraction Services?

A DIY data extraction tool is either a web browser extension, plug-in or add-on, or software that can be used after it is installed into the system. Such tools are best suited for companies that do not have technology as their core competency for ad-hoc projects or small data requirements.

On the contrary, a data mining service is when you outsource an organization's data requirements to professionals for a fee. This way, you can better focus on your core business competencies while the specialists take care of your data extraction project needs. These outsourcing companies are committed to solving your exact pain point by offering customized services and solutions.

If you need data quickly from simple and well-structured resources, then a data extraction tool is a cost-effective option. Most tools offer trial plans as well as limited monthly volumes free of cost, which are often enough for low-scale extraction jobs. And if you have crossed the limits of these DIY tools, a subscription plan is usually not that expensive.

Data mining companies, on the other hand, have all the necessary infrastructure and the right capabilities already in place to manage even the most complex of extraction jobs. Having the right blend of skills and experience, these specialists deliver high-quality results within the stipulated time and budget. They have a dedicated QA team to assess the quality of outcomes and ensure that it is up to the mark. Most importantly, all their practices are legally conformant and according to the set industry standards.

Final Words

In many cases where data is extracted from online resources, websites block crawlers by placing various challenges and obstacles to being able to access their data. A DIY tool or software would fail each time as it isn’t capable enough to encounter such a blockage.

On the other hand, outsourcing data extraction companies are seasoned pros who encounter such issues regularly as part of their core competencies. These experts are well-equipped with all provisions in place to fix each kind of problem efficiently so that businesses get a constant stream of quality data.

Even though DIY data extraction tools have their merits when it comes to enterprise-level data requirements, they cannot stand up to the might of a professionally managed extraction service. So, if your organizational growth is dependent on analytical insights retrieved from the latest data, trusting and partnering with an outsourced service provider is the best way forward.