Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Things to Consider when Evaluating Options for Web Data Extraction


Published on

Here is a detailed overview of different ways by which you can extract data from the web. This could help you make the final call while evaluating different options for web data extraction.

Published in: Data & Analytics
  • Be the first to comment

Things to Consider when Evaluating Options for Web Data Extraction

  1. 1. Things to Consider When Evaluating Options for Web Data Extraction
  2. 2. Data Extraction Extracting massive amounts of data from the web is still a major roadblock for many companies, more so because the optimal route is not clear. Here is a detailed overview of different ways by which you can extract data from the web.
  3. 3. Different methods of Data Extraction 1. Build it In-House 2. DIY Web Scraping Tool 3. Vertical-Specific Solution 4. Data-as-a-Service
  4. 4. In-House Crawling If your company is technically rich, meaning you have a good technical team that can build and maintain a web scraping setup, it makes sense to build a crawler setup in- house. Pros: •Total ownership and control over the process •Ideal for simpler requirements Cons: •Maintenance of crawlers is a headache •Increased cost •Hiring, training and managing a team might be hectic •Might hog on the company resources •Could affect the core focus of the organisation •Infrastructure is costly
  5. 5. DIY Web Scraping Tool If you don’t want to maintain a technical team that can build an in-house crawling setup and infrastructure, DIY scraping tools can be of help. Pros: • Full control over the process • Prebuilt solution • You can avail support for the tools • Easier to configure and use Cons: •They get outdated often •More noise in the data •Less customisation options •Learning curve can be high •Maintenance
  6. 6. Vertical-Specific Solution Vertical specific data providers can give you data that is comprehensive in nature. This also improves the overall quality of the project. Pros: • Comprehensive data from the industry • Faster access to data • No need to handle the complicated aspects of extraction Cons: •Lack of customisation options •Data is not exclusive •Not sufficient to get a big picture of the market
  7. 7. Data-as-a-Service Getting the required data from a DaaS provider is by far the best way to extract data from the web. Pros: • Completely customisable for your requirement • Takes complete ownership of the process • Quality checks to ensure high quality data • Can handle dynamic and complicated websites • More time to focus on your core business Cons: •Might need to enter a long-term contract •Slightly costlier than DIY tools
  8. 8. Factors to consider while choosing a data extraction solution Considering how crucial data is in the present business scenario, extra care must be taken while choosing a data extraction solution for your organization. Following are some things to consider:
  9. 9. Customization options You should consider how flexible the solution is when it comes to changing the data points or schema as and when required. This is to make sure that the solution you choose is future-proof in case your requirements vary depending on the focus of your business.
  10. 10. Cost Cost can be associated with IT overheads, infrastructure, paid software and subscription to the data provider. You will have to evaluate what option really does the trick for you at a reasonable cost.
  11. 11. Data delivery speed Depending on the solution you choose, the speed of data delivery might vary hugely. If your business or industry demands faster access to data, you must choose a managed service that can meet your speed expectations.
  12. 12. Dedicated solution Are you depending on a service provider whose sole focus is data extraction? There are companies that venture into anything and everything to try their luck. For example, if your data provider is also into web designing, you are better off staying away from them.
  13. 13. Reliability Low quality data and lack of consistency can take a toll on your data project. When going with a data extraction solution to serve your business intelligence needs, it’s critical to evaluate the reliability of the solution you are going with.
  14. 14. Scalability If your data requirements are likely to increase over time, you should find a solution that’s made to handle large scale requirements. A DaaS provider is the best option when you want a solution that’s scalable depending on your increasing data needs.
  15. 15. Got Questions? Connect with us at: