Main principles of effective SaaS data management

Technologies have evolved extensively in sectors related to the management and security of critical data for on-site infrastructure. However, most organizations and businesses are shifting to SaaS, which many find beneficial. For example, 78% of professionals report that there is still a lot that they need to learn about SaaS and its best practices. This is why best data management practices do not exist in the SaaS industry. Read on and learn more about the principles of data management in SaaS.

SaaS data management: the challenges businesses face

When companies get Software as a Service, things like hardware and software are managed by the service provider. They also provide policies to monitor the administration. In addition, the IT department is responsible for using those policies to control the application's administration.

While there are different plans and models of services, data management in SaaS apps is a shared responsibility between an IT department and a service provider. The IT department is responsible for aligning everything in accordance with regulatory requirements. Meanwhile, the service provider works to manage the backend for compliance.

Companies working with SaaS for their backend needs may face several data management issues. These are usually because the data comes at a specific speed, volume, and variety, all of which need to be efficiently managed. So, building data under bad management presents the following issues:

  • Poor accessibility makes it difficult to extract data. Each object has different rules for different functionalities, and different APIs are used to access them.

  • Differences in query languages between different APIs will restrict the same query from working on several APIs used.

  • Higher data storage and opportunity costs because companies load much more data than they need just to retain customers.

  • API roadblocks resulting in a lack of learning and performance capabilities for AI and Machine Learning Systems.

A lack of data management in a SaaS app can result in your company facing these issues, along with many others. Leaving things to the professionals at Dworkz will help you deal with such problems. We create an integrated experience across your web application with our expertise in UI/UX and coding, along with strategic planning and design.

Six effective SaaS data management principles

These six practical SaaS data managing principles can help you establish a strong base for managing data across multiple SaaS apps. These principles include centralization, discoverability, insights, action, automation, delegation, and auditability. By working on these SaaS app data managing principles, every SaaS application can avoid common data management challenges.

1. Centralization

Today, data is sprawled across several SaaS apps because of the lack of homogeneity. SaaS apps provide best-in-class features and experience, and organizations use various SaaS apps. This data sprawl is one of their main challenges, but it can be resolved with centralization.

If IT brings all this data into a central location, intending to have more control over it, different objects can be managed in one place. Currently, all these objects are in different areas within SaaS, so centralization can make it easier to normalize data. With all the various objects in one place, centralization allows IT to view and control them effectively.

2. Discoverability

Organizations can range from a few dozen employees to thousands of them. Having this many employees means that there could be millions of objects in the SaaS environment, such as users, files, folders, third-party apps, and groups.

With discoverability, IT can quickly sort massive data sets and filter them. Discoverability makes your approach to valuable insights about the data better by grouping it and giving you instant insights about users, for example:

  • Users who use 2FA

  • Users publicly sharing files

  • Employees forwarding emails

  • Publicly visible group details, etc.

With quick access to all this information, data management in SaaS applications becomes effective for organizations.

3. Insights

Datasets provide a massive volume of useful and useless information, all bundled together. Real-time insights serve only the most important attributes at the right time to give detail on an activity. This helps organizations ignore vast volumes of alerts containing irrelevant data and only focus on helpful information.

As per a report from 2013, IT department admins ignore several important alerts because most of them are not valuable. This increases the likelihood of a data breach. So, receiving only the most critical insights at the right time can enhance data security and integrity if they indicate a threat.

4. Action

Having huge volumes of SaaS data is good, but at the same time, it brings challenges to the principles of SaaS data management. Centralizing the data is only half of the work; the rest concerns enhancing its discoverability and working on the right insights.

You need to use these insights to make actionable decisions that will help remediate the issue of SaaS data management. Actions taken in bulk can help in saving time and increase productivity. Most of the SaaS applications involve repetitive and manual tasks like:

  • Onboarding and offboarding

  • Lifecycle management

  • File sharing and management

  • User management, etc.

As IT admins take bulk action for these tasks, their focus on value-adding strategies will increase instead of becoming frustrated by repetitive tasks.

5. Automation

Automation is the most important principle for effective data management for SaaS apps. It involves automated policy enforcement and workflows, but it is more complicated than that. Automation takes time for approval, building, testing, and iterating for the best results. While it takes effort, this way you can eradicate the chances of human error, which makes it critical.

Automation also forces the IT department to respond quickly to data breaches using the right insights and actionable decisions. Lacking automation for SaaS app data management means you lack all these factors. In such scenarios, a simple issue can take weeks or months to identify, respond to, and resolve.

6. Delegation and auditability

Delegation means giving admin permissions to others in the organization by creating granular access roles. Instead of giving complete admin control, only the necessary permissions are provided, making the least privileged model for added security.

With SaaS apps being binary, organizations cannot provide super admin access to non-admin employees because of security risks, and delegation solves this issue by guiding them only to the temporarily elevated access for a project.

Auditability increases accountability across SaaS apps, which can be critical for security reasons. With multiple employees working on different projects, keeping track of their roles can be difficult, and going manually through logs can be challenging. Through automation, audits become easier and more effective from a compliance perspective.

Summing up

SaaS is in its early stages, and we will see scope for many future improvements. However, with its increasing usage, efficient data management must maintain data integrity across applications. The main principles of SaaS data management that we discussed here help deal with all sorts of data managing challenges. As organizations adopt SaaS, using these six principles for data management will ensure success in the respective department.

Dworkz helps solve all data management and system architecture issues to offer every user a productive experience. With our expertise in the industry and more than a decade of experience, we can provide you with the most effective solutions. Feel free to get in touch and learn how we can solve your problem.


How is data managed in SaaS?

Data is managed in SaaS as a shared responsibility between the SaaS provider and the IT department at the organization. The IT department must ensure that everything is aligned according to defined controls and regulatory requirements. Meanwhile, the service provider works on SaaS backend data management.

What are the challenges for data management in SaaS?

The main challenges for data management in a SaaS app include data not being in one place like it was previously. Due to this, the whole system lacks homogeneity and management; auditing, problem detection, performance monitoring, and instant problem-solving become difficult.

What are the benefits of data management in SaaS applications?

Good data management practices for SaaS applications bring many benefits, like better AI and ML capabilities for automation, better product integration for your business, the ability to extract the right information through complex queries, and more.

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