Data has long been thought of as a key part of business strategy and the day-to-day running of an organisation. You need data in order to set targets, monitor business processes and to motivate new ideas within the company.
Information and data can come from a myriad of sources, from analytics tools to documents to websites and portals. The more useful data a company has, the better the decisions and ideas that can from the employees (note the word ‘useful’).
While data is worth having, collecting the data can be tricky and if done manually, it can be pretty time consuming and not very cost effective, especially when the information is being pulled from websites and portals and when information needs to be filtered out.
Will it automate?
In a word: yes. There have long been tools available to scrape data from websites and other systems, however, these tools aren’t very intelligent and can cause more problems than they solve. For example, you might be able to get a data dump using a web-scraper but the data then needs to be reviewed and someone needs to spend time going through all of the data and sorting it and filtering out unwanted bits.
The unstructured data you receive can also be very messy making the job even harder.
Thankfully, there are much better ways to automate the process that go beyond just the initial data extraction and actually structure and classify the data as well.
A better way to automate data extraction:
By using intelligent software robots, the data extraction process can be automated properly with the right blend of human interaction that ensures accuracy and aides the machine learning element of the automation.
We’re not just talking about RPA here, we’re talking about intelligent automation that goes above and beyond just scraping the data and actually structures the data so it can be tracked, cross checked or verified against internal data.
This next level of data extraction automation further allows for proper analysis and recognition of key insights from the data.
How does it work?
Firstly, it’s key to set rules in regards to the data you need to extract and where from, this way the software robots can automatically interact with and pull data from different websites and sources of data as per the human set rules. The extracted information is then delivered in near real-time and is constantly updated.
The next step involves actually making the data usable - it’s one thing to gather lots of unstructured and potentially useless data, it’s another to make it worthwhile and useful for the business.
Once the data has been extracted and captured by the intelligent software robots, the data can be automatically classified, separated & validated and then structured in a way that makes it easy to access and scrutinise while integrating it with existing business processes.
This whole process provides end-to-end process visibility, discovery and monitoring to drive compliance and increase customer satisfaction.
The features of automating data extraction
Some of the key features and benefits of an intelligent automated data extraction process include:
- Automatically extract data from any website or portal. Eliminate manual efforts or complex scripting.
- Filter, transform, normalise and aggregate precise and complete data.
- Automatically classify, verify and structure the data to make it accessible and visible to the business.
- Integrate external web data with any enterprise system, database or process.
- Gain insight, a competitive edge and ensure compliance and deliver operational excellence.
By automating this time-consuming and potentially expensive process, you can gain valuable business insights from the data extracted while transforming the process and making it more efficient.