Self-Service Data Platform: Definition & Must-Have Features
A self-service data platform is the backbone of informed decision-making and a growing SaaS business.
But how do you choose the right data platform for product analytics? What should you look for?
Let’s go over what a data platform is, its importance, and the must-have features you should consider to choose the right platform for you.
What is a self-service data platform?
A self-service data platform is a user-friendly system that empowers non-technical users to access, analyze, and visualize data without needing extensive IT support. It provides intuitive tools and interfaces for data extraction, transformation, data product creation (for domain teams), and loading (ETL), enabling users to generate insights and make data-driven decisions efficiently.
Its goal is to provide a data warehouse that democratizes access, enhances organizational agility, fosters innovation, and reduces the reliance on specialized data teams.
Benefits of using a self-serve data platform
Self-service data platforms empower users at all levels to access and analyze data independently. It ensures that insights are readily available to build good products, improve customer experiences, and optimize business operations.
That said, the benefits of these platforms are multiple, including:
- Enhanced decision-making speed with real-time data access.
- Reduced dependency on IT and data teams.
- Increased productivity through intuitive, user-friendly interfaces.
- Improved customer insights and personalized experiences.
- Greater agility and responsiveness to market changes.
- Cost savings by minimizing the need for specialized data personnel.
Must-have features of self-service data platforms
Now, let’s explore the must-have features that make a data platform valuable for any SaaS business. They include:
Data sources and discovery
When choosing a self-service data platform, it’s important to check where it can pull the data from (including databases, APIs, or third-party apps). As well as how it presents it to users—so the less support from the data engineers is required, the better.
With good data discovery and user-friendly visualization, the platform can ensure that all relevant data can be integrated and accessed from a single platform. And as a result, enabling comprehensive analysis and data-driven decision-making across your company.
Sourcing data from Hubspot with Userpilot.
No-code and low-code data collection
It’s essential for a self-service platform to allow users to gather, manage, and manipulate data lakes without needing extensive programming skills.
This kind of tool often includes drag-and-drop interfaces and pre-built templates, making it easy for non-technical users to collect data. As a result, you can democratize data access and incentivize all team members to participate in data-driven initiatives, improving productivity and collaboration.
Reports and dashboards
Good data products must present data in an easily digestible format, often using graphs, charts, and tables. As well as providing tracking of object dependencies, data lineage, dynamic data masking, and so on.
Reports and dashboards are key so they can provide real-time insights and show key performance indicators (KPIs) at a glance, helping teams monitor progress, identify trends, and make quick, informed decisions.
As a result, your company can enhance transparency and align teams toward common goals.
Security and data governance
When it comes to checking security and data governance, it’s important to consider the measures and policies that protect data integrity, confidentiality, and compliance.
This aspect is more important than it seems. Effective security maintains user trust, complies with regulatory requirements, and prevents data loss or unauthorized access—which would obviously have severe repercussions for the business.
For example, Userpilot adheres to very strict standards that are compliant with GDPR, SOC 2 Type II, and HIPAA rules. And this way, we make sure that our user’s data is completely safe from bad actors.
Bonus: Interactive in-app flows
Interactive in-app flows guide users through various features of the platform directly within the application.
Although they don’t seem to be a must, these guided tours and tutorials are essential for onboarding new users and providing ongoing support. It ensures everyone on the team can quickly grasp and effectively utilize the product (which is the primary goal of choosing a self-service platform).
Furthermore, proper in-app guidance enhances user experience, reduces the learning curve, and promotes widespread adoption of the platform across the organization. Any product that offers in-app guidance will have an advantage.
How to choose the right self-serve data platform
That said, it takes three essential steps to choose the right data platform for your business:
1. Identify your needs and key features
Before exploring data platforms for your business, think first about your needs and what must-have features would satisfy them. This ensures that the chosen platform aligns with your business objectives and operational demands.
For this:
- Conduct a stakeholder survey to gather input on data needs and pain points.
- Define the primary use cases for the data platform (e.g., reporting, data analysis, user tracking).
- List essential features such as data integration, visualization tools, security standards, and user-friendliness.
- Prioritize the features based on their importance to your business processes and goals.
2. Consider compatibility with your current data assets
Now, consider your current tech stack and look for products that feature direct integration with the platforms you already use.
This way, you can ensure that the new data platform can seamlessly source the data you need without requiring technical assistance. It also helps maintain data consistency and avoid disruptions in your workflows.
To do this, follow this checklist:
- Build a data catalog of your existing data sources, including databases, APIs, and third-party applications.
- Check if the data platform supports these data sources and offers easy integration.
- Assess the platform’s ability to handle the volume and complexity of your current data.
- Evaluate the platform’s support for data formats and standards used in your organization.
- Ensure that the platform can scale with your data needs as your business grows.
3. Research the tools and sign up for free trials
Finally, once you’re clear about your needs, must-have features, and the integrations you need to look for, it’s time to research the best tools in the market.
For this, you can perform your own research and look for reviews on G2. But, we strongly recommend signing up for opt-in free trials.
This way, you can evaluate different data platforms hands-on and determine which one best meets your requirements. And as a result, you’ll be able to make informed decisions based on practical experience rather than theoretical features.
Here are some tips for this process:
- Compile a list of potential data platforms based on your identified needs and compatibility requirements.
- Read reviews, case studies, and user testimonials to gauge each platform’s performance and reliability.
- Sign up for free trials or demo versions of shortlisted platforms to test their features.
- Create test scenarios that mimic your actual use cases to assess functionality and ease of use.
- Gather feedback from team members who will be using the platform to ensure it meets their needs.
- Compare trial results and select the platform that best aligns with your business objectives and user preferences.
Userpilot – Best no-code option for your data mesh
Userpilot is a no-code product management tool with robust data analytics features.
This means it not only helps you monitor your data, it also provides multiple ways to collect both behavioral data and user feedback.
To ensure high data quality, Userpilot offers multiple no-code tools:
- Feature tags and event-tracking to monitor user behaviors.
- Built-in tracking features to watch over the performance of your in-app flows, such as tooltips and checklists.
- Goal-based tracking to monitor how many users are achieving specific milestones (influenced by your in-app flows).
- Create and trigger in-app surveys, such as NPS surveys, CES surveys, and CSAT surveys. These can be triggered inside your app automatically so you can collect feedback on your sleep.
As for analyzing data, Userpilot has easy-to-set-up dashboards to:
- Watch over segmented audiences to find common patterns and responses on specific groups of customers.
- Feature analytics for tracking the performance of your products and how customers use them.
- Funnel and path analysis to have a birds-eye view of how users move through the funnel, how they deviate from it, or how they achieve success with your product.
- Get survey data and measure metrics such as NPS and CES. It also allows you to tag qualitative responses to find common keywords among detractors or promoters.
Plus, native integration with other data sources and tools, including:
- Amplitude
- Google Analytics
- Google Tag Manager
- Heap
- Intercom
- Kissmetrics
- Mixpanel
- Segment
- HubSpot
- Salesforce
- Zendesk
Conclusion
As we’ve explored, choosing a self-service data platform is not only useful to include non-technical team members in the decision-making process. It’s also an important step toward cultivating a data-driven culture and centralizing team efforts toward the same goals.
That said, do you need a no-code data platform that can help you empower your product team and increase their productivity? If so, book a Userpilot demo to see how you can collect and analyze product data to grow your business.
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