How to Get Data Out of ServiceNow

The ability to get data out of ServiceNow quickly, consistently and accurately helps organizations get more value out of ServiceNow, and the insight the platform generates. 

ServiceNow data is a great source of insightful information that can shape better business decisions, help identify trends, and improve operational resilience. 

Organizations can leverage ServiceNow data for various use cases, including data lake building, reporting, data analytics and BI, AI and ML, and more. 

However, extracting ServiceNow data without the appropriate tools is notoriously difficult. 

With that in mind, organizations need a consistent method for extracting ServiceNow data and maximizing the value of the platform’s data and insight. 

The most reliable and efficient way to achieve this is via integrations with an external data repositories such as a database.

Integrating ServiceNow data with external data repositories allows organizations to improve the manageability and availability of data, without compromising its security. 

Why Extract ServiceNow Data?

Business leaders extract and replicate ServiceNow data into external repositories to support a wide range of day-to-day needs: 

1. Data backups & archiving

Many organizations require more advanced capabilities for data backups and archiving than ServiceNow provides out-of-the box. The platform creates a full backup, direct to disk, every seven days, but only retains it for 28 days. This makes it unsuitable for meeting archiving needs. 

Additionally, ServiceNow data backups and the restoration process can take some time and while the restoration process is running, the instance is unavailable. And there are other limitations to ServiceNow data backups to note.

In contrast, the right integration approach can create and restore data backups, extract large amounts of ServiceNow data and replicate it to an external database for archiving. Typically, such integration technologies are automated, meaning the process has little-to-no impact on developers or development resources – depending on the type of integration. 

• See also: Choosing the Right Integration Approach

2. Visualizing the bigger picture

Extracting ServiceNow data via well-planned integrations allows organizations to merge it with data from other sources to create a holistic and complete view of internal operations. 

Organizations can democratize ServiceNow data and enable secure, self-service access to the platform’s data.

Any team member/stakeholder can access the extracted data for their needs without a ServiceNow license or platform experience. 

It supports eBonding by automating the transfer of information supporting ServiceNow workflows to other solutions, creating dynamic synchronization between multiple ServiceNow instances and between ServiceNow and third-party platforms/solutions.

Such dynamic synchronizations enable inter-application workflows, allowing employees to continue using their preferred software – letting the integrations dynamically update connected systems. Team leaders get increased visibility into task statuses across systems.

3. Business intelligence

Extracting ServiceNow data significantly enhances Business Intelligence (BI) operations by automating the transfer of ServiceNow data to BI solutions. 

Business intelligence solutions generate insight based on the data fed into them. With ServiceNow integrations that support massive throughput and dynamically triggered data transfers, organizations can maximize the value of BI insight, by feeding large amounts of quality data into the BI solution. 

The BI team can analyze business data from combined sources, including ServiceNow and other app data, delivering a detailed overview for business analysts, business owners, and C-suite executives who must have a clear picture of business performance. 

4. Analytics

Organizations with a means to get data out of ServiceNow are better able to combine ServiceNow data with other sources, and analyze data via purpose-built solutions for analytics.

For example, Predictive Analytics solutions use data to identify trends for informed decision-making. Via high-throughput ServiceNow integrations, organizations can dynamically feed data into Predictive Analytics solutions. 

Since the insight generated is improved by the volume and quality of data fed into the platform, high-throughput integrations allow for faster optimization of insight. 

5. Advanced Reporting

Although ServiceNow reports are an excellent source of insights on the Now Platform’s apps and features, it has limited capabilities and can only deliver reports on ServiceNow data. Large-scale organizations need in-depth data insights that only best-in-class reporting tools can offer. 

Replicating ServiceNow data into an external database allows teams to expand their reporting capabilities. While they still use their preferred reporting solution, they can combine ServiceNow data with data from other sources for more comprehensive reports.

6. Preserving SN performance

As companies scale, running large data volumes in ServiceNow hinders platform performance significantly, slowing down queries, reports, and enterprise operations. When teams directly query ServiceNow for bulk data extraction, it puts a strain on the Platform. 

The best way to avoid this issue is to extract and replicate the data to an external database. 

Running reports from an external database prevents performance impacts on the ServiceNow production instance, allowing users to continue their activities without complications. 

Organizations with extensive reporting needs can ensure that ServiceNow instances perform optimally, by replicating the data to a data lake.

ServiceNow Integrations for Data Extraction and Replication

ServiceNow integrations are the best way to extract and replicate data. Organizations can choose from different integration methods, depending on their specific needs. But its important to choose the right type of integration.

Many traditional integration methods – from manual to API-based integrations – can suffice for short-term use cases, but can fail to meet the demands for throughput and high-instance performance that enterprise-scale organizations require. 

• See also: Why You Should Avoid API-based ServiceNow Integrations

Conversely, modern, particularly native automated integration solutions can replicate massive amounts of ServiceNow data without impacting performance, and scaling as usage increases. 

Below we list the types of integration that can be used for extracting ServiceNow data, and the caveats that are associated.

1. DIY or custom integrations

Large organizations with expansive IT teams often choose the DIY way as they think creating custom integrations or hiring consultants might seem cost-effective initially.

However, teams that have implemented custom or point-to-point integration can vouch for their inefficiency and expense in the long term. 

Integration development should not be the primary focus of IT developers – their efforts must be directed at value-adding tasks. 

The bottom line is, DIY integrations are better suited for smaller, low-volume, and one-time integrations.

2. Swivel chair/manual integrations

Manual – or swivel chair – integrations involve manually copying data from one system and entering it into another. Besides being time-consuming, this integration approach is highly prone to errors and can jeopardize response and resolution SLAs. 

Swivel chair integration can be transactional (e.g., replicating an incident to create a development request) or batch-based (e.g., copying a CMDB snapshot to a database) and is ideal only for small-scale, occasional data transfers only.

Organizations with a consistent requirement for ServiceNow data extraction require automated integration solutions. 

3. iPaaS integration

iPaaS providers offer packaged, cloud-based, third-party integration solutions that typically use web services or API calls to facilitate data transfers.

Unfortunately, web services/API calls drain ServiceNow’s bandwidth to operate, thereby causing performance degradation. 

And while the packaged nature of iPaaS solutions can speed up time-to-implementation, the integration provider delivers the platform only.

Meaning the implementation and subsequent maintenance of the solution require significant internal resources to manage. 

4. ServiceNow-Native Integrations-as-a-Service

For organizations with a consistent need for extracting ServiceNow data, requiring high-throughput and high-instance performance should explore ServiceNow-native integration technologies. 

ServiceNow-native technologies are purpose built to work with the architecture of ServiceNow for the highest performance.

Since they function within the ServiceNow platform, Web-services/API calls from external applications are not required. This means ServiceNow-native integrations can subvert the performance impact associated with traditional integration approaches. 

When delivered as-a-service, ServiceNow-native integration applications also save organizations considerably, in terms of development resources and time. Implementation is fast – delivered by ServiceNow integration experts – and subsequent maintenance is also handled by the integration provider. 

With ServiceNow-native integrations, organizations can achieve massive throughput when transferring data, without impacting performance. 

Extract ServiceNow Data Without Impacting Performance with Perspectium

Perspectium is a fully-managed, ServiceNow-native integration solution and service for ServiceNow that operates within your current ServiceNow interface. 

The Perspectium DataSync tool is a reliable integration option many ServiceNow users leverage to extract ServiceNow data.

Unmatched by custom-built and manual integrations, DataSync boasts the fast data transfer rates with no impact on application performance.

Instead of using web services/API calls, DataSync features a highly scalable, cloud-based message-bus architecture and “Push” technology to extract ServiceNow data and replicate it to external systems. 

This means the target system retrieves the data from the MBS rather than directly from ServiceNow itself. 

As well as preserving performance, this approach prevents data loss, preserving extracted data even in the case of an outage at the target system. Instead of being lost, the data securely waits in the queue until the target system is back online.

Want to learn more about ServiceNow-native integrations? Click here.