There are several options for extracting web data: building tools in-house, using do-it-yourself scraping tools, relying on vertical-specific solutions, or using a data-as-a-service provider. The best option is typically a data-as-a-service provider as they take ownership of the entire process, ensure high quality data, and allow companies to focus on their core business rather than web data extraction. However, companies should consider factors like customization needs, costs, data delivery speed, reliability, scalability, and the dedication of the solution provider to web data extraction when choosing a solution.

1. Things to Consider When
Evaluating Options for
Web Data Extraction

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. 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. 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. 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•They get outdated often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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Got Questions? Connect
with us at:
www.promptcloud.com
sales@promptcloud.com