Extracting Data from ServiceNow for Business Intelligence

For full visibility into the business, companies replicate ServiceNow data to a data lake, enabling business intelligence, analytics, and machine learning.

At your business, requests for access to that data can come from any number of sources, including company leadership. When you make real-time data available, decision-makers at your business do their jobs better.

Why Extract ServiceNow Data?

But do you really need to extract the data from ServiceNow? What if stakeholders just access the data from within ServiceNow? Companies replicate ITSM data to their data lakes for a variety of reasons.

Seeing the big picture. When you combine ServiceNow data with data from other tools in your business, you get a more complete view of the business. But extracting that data is hard. When you move massive amounts of data, it can create distressing performance slumps on the production instance – which leads to the next point.

Preserving performance. When you report from a database, there are no performance hits on the ServiceNow production instance. Users of ServiceNow throughout the company can continue their activity as usual. Running massive reports on ServiceNow data doesn’t have to touch the ServiceNow instance if that data has already been moved to your data lake.

Using familiar and powerful BI tools. Your BI team is already familiar with their best-of-breed tool – perhaps Tableau or Power BI. Some organizations actually make use of many reporting tools that perform queries on the data lake. You can avoid forcing cultural change by letting departments continue using the tools they love.

How Can I Extract ServiceNow Data?

Many companies start out by building their own integration from ServiceNow to a database. But these web-services integrations don’t let a growing business scale.

They break when the company updates ServiceNow or the integration developer leaves the business – and takes their knowledge with them.
They cause data loss – because web services aren’t usually designed to handle outages.
They often don’t comply with new security and privacy rules.
They cause performance hits on ServiceNow. To avoid interruptions, companies try to schedule data transfers during off hours. But now, you’re conducting BI and analytics on obsolete data. Stakeholders need real-time data.

A growing company may look to a vendor that sells an integration toolkit. But because they use web services as well, they have many of the same problems as building it yourself. And after all, with one of these vendors, you’re still building the integration yourself – just with larger parts.

The best approach is creating automated connections that use “push” data streaming. This method, controlled natively within ServiceNow, has minimal performance impact on ServiceNow. And it allows you to report on massive volumes of data.

Using a message queue, this approach also avoids requiring that data endpoints be online perpetually. So there’s no risk of data loss if one of the endpoints has an outage.

Extraction in Action

After Accenture moved from their on-premise database with Remedy to their ServiceNow cloud solution, they needed a solution for extracting ServiceNow data without impacting the performance of ServiceNow. They also needed to combine data from both ServiceNow and other tools.

“We immediately needed to figure out a way to intelligently, and with as little performance impact as possible, get the data out,” says Jeff Lowenthal, Enterprise Architect for Accenture.

Accenture signed on for an automation solution that lets them offer real-time ServiceNow reporting of over 100 million records per month – without performance impacts on ServiceNow.

Perspectium DataSync lets you move incredible amounts of data without performance impacts on ServiceNow. Learn more about Perspectium DataSync for extracting ServiceNow data.