What are the questions to ask before outsourcing data extraction?

What are the questions to ask before outsourcing data extraction?

The impact of the internet on our lives is immense. A lot has changed within the past few decades with the internet coming into power. We use the internet for almost everything from shopping to solving queries.

In recent times the marketing and tech companies have seen the potential in online information to be a great source of data that can be used for analytics trends and patterns.

Today many organizations value analyzing the humongous amount of data that is published every day online.

You might want to consider these questions before jumping into the process of data extraction.

It’s an unsaid rule that data analysis starts with questions that you want to answer.

The questions are as follows:

  • Which products am I delivering?
  • Who is your audience that will consume my data?
  • What kind of analysis reports do I want to generate?

The next set of questions relates to websites you want the data to get extracted from and what kind of data you want to search. Some sites can be easily accessed with open APIs or manual crawling, while some websites are difficult to get crawled by web crawlers to access the data or might even be illegal to do so.

You would also want to know how often the data is updated on the site. The requirement of data depends on where you want to use the data. For example, you want to feed data in an AI. Then you need the data in a massive amount. But if you want the latest news about a particular profession, you may require current data that is relevant to the time.

The question that you can ask related to searching your data can be as follows:

  • What type of information I am interested in i.e., text, image or video.
  • How often are the websites updated and how new should the data be?
  • Where is the information usually published?
  • Are some legal or technical aspects restricting me to access the data?

When you want the answers to a case or have to do research, you require to understand the technical scheme of things. You would need how you want the data to be structured and how you will incorporate the data in the existing pile.

Some analytic queries you want to run would be required to be addressed in advance due to the prerequisites that can be created in terms of data structure. The limitations are in the form of file formats, databases that arise from data visualization tools that are to be used. A NoSQL database is more beneficial for text analytics and Neurology, Language and Programming (NLP) sampling, while a SQL database would be suitable for business intelligence analysis.

The questions you need to ask for defining the technical requirements are as follows: