Your guide to the self-service data platform including a breakdown of key features to look for
There are a lot of self-service data platforms out there. And picking the one that best fits your organization’s needs can be challenging.
In this article, we’ll discuss what you should expect from a self-service data platform and what features make it a good choice.
And since you’ve landed on our blog, it would be foolish of us not to show you how our self-service data operations platform, Keboola, can help you scale data operations by allowing non-technical users to access and analyze data independently.
But before we dive in, let’s look at why this type of platform is worth the investment.
A self-service data platform empowers users to discover, access, create, analyze, and productize datasets irrespective of their technical skills.
This platform simplifies data analytics for non-technical users through an intuitive interface while providing data teams with efficient tools for their tasks throughout the data lifecycle.
A self-serve data platform offers many advantages:
Let’s examine the essential features of a self-service data platform by focusing on diverse use cases to understand their real-world impact and utility.
A data catalog acts as a central reference system, organizing and indexing the available data with explanations, business definitions, and links to other sources. This is crucial in large organizations where the volume and variety of data can be overwhelming.
Data catalog features differ among providers. Keboola, for example, offers one of the most extensive data catalogs with features including:
PRO TIP: BEYOND DATA DISCOVERY
The best tools allow you to discover other data assets, not just your tables. For example, DocsBot in Keboola helps you find the right documentation, email, or support ticket to answer your questions.
The Visual Flow Builder is an essential feature in self-service data platforms designed to construct and manage data pipelines.
It lets users visually map the data journey from various sources to data storage, like data lakes, databases, or data warehouses. Using a visual UI allows users to enjoy several benefits, including faster workflow creation through drag-and-drop functionality, quick identification of dependencies, and easier collaborations between technical and domain teams.
For example, Keboola offers a Visual Flow Builder, where users can quickly map out the journey of data by drag-and-dropping different components in place:
PRO TIP: DATA PIPELINE TEMPLATES
The best self-serve data platforms, like Keboola, offer templates for the most common data pipelines. These templates allow users to set up the most common workflows with a couple of clicks, such as extracting marketing data from different advertising platforms.
Transformations are necessary for cleaning data sets, computing metrics, and preparing data for visualizations and business intelligence dashboards.
Look for no-code and low-code transformations to optimize the data preparation work for your domain experts and the data team.
In Keboola, users can use no-code transformations as a simple UI. This means you can simply pick the data set you want to transform and select the transformation from a drop-down list of possible data transformations (in the example below, we’re removing duplicate rows).
Keboola also offers the flexibility to use low-code transformations with Python, R, Julia, or SQL. These look like a simple workbook where you specify the incoming data, write the code for the transformation, and the location of the output data:
Data engineers often spend a lot of time writing scripts to extract data from their sources and load data into data storage (like a data lake or data warehouse). Pre-built connectors are a game-changer in this case. They eliminate the need for complex scripting and reduce the technical burden on data engineers.
When looking for the right self-service data platform, check if the tool provides existing connectors for your data sources. This is key to ensure smooth implementation post-purchase. These connectors save you time with data integration, sparing you from the task of manual scripting.
Take Keboola as an example: To extract data, you can simply select the suitable connector (like the Facebook Ads extractor) and configure access credentials. This ensures secure and authorized data extraction.
Keboola then seamlessly handles the rest in the background to call the Facebook Ads API, retrieve the data, and save it to the specified data destination.
For effectively managing a regulated data operation, you should track who interacted with what data asset and when.
When selecting a self-service data platform, prioritize these four key data observability features:
Top self-serve data platforms are more than analytics platforms; they empower you to turn your data into products, increasing your competitiveness and improving the ROI of your data operations.
For example, Keboola offers a suite of Data Apps to convert your data sets into interactive customer data applications. With just a few clicks, you can create AI-generated SMS marketing campaigns, build an Online Marketing Dashboard, or compare your Google Analytics UA vs. GA4.
Giving federated data access to all users in your company doesn’t have to compromise your data management control.
The right self-service analytics platforms help you maintain data governance over your data assets. They ensure security and regulatory compliance while preventing data misuse.
Kebooal provides role-based access control for every user to enable this use case. This approach restricts the extent of data operations a user can perform, especially with sensitive data, maintaining a balance between accessibility and control.
When selecting a self-service data platform provider, you need to choose one that adheres to high accreditation and certification standards as set by regulatory compliance bodies.
A recommended practice is picking providers whose platforms comply with GDPR, HIPAA, and SOC 2. By prioritizing providers with these certifications, you ensure higher protection for your organization's sensitive data.
Are you searching for a tool capable of managing large-scale data ingestion efficiently without performance lags or errors?
Look for real-time data streaming or change data capture (CDC) features. These features help you analyze schemas and only push the new and updated data down the data integration pipelines to speed up your processes at scale.
Keboola is a self-service data operations platform that enables all users within organizations to connect data, automate workflows, and handle all their data needs. Its features provide users with complete control of their data and processes:
Keboola offers a free plan with 120 minutes of usage in the first month, followed by 60 free minutes every subsequent month.
For additional usage, the cost is $0.14 per extra minute, providing a flexible and cost-effective solution for your data operations needs.
Even after burning your allocated free credits, you can still access and work on your project. However, you can only run jobs if you buy extra credits.
“What sealed the deal for us was that Keboola offered the flexibility of using both Python and SQL for transformations, the visual flows that simplify the insights into complex data pipelines, and their amazing support.” - Ronnie Persson, CTO at Pincho Nation
“Without Keboola, it would have taken weeks and likely months to get their data ingested because of their source systems. With Keboola, our engineers were ingesting data within hours.” - Daniel Rothamel, Cloud Data Delivery Engineer at North Labs
Investing in a self-service data platform helps you get more value from your organization’s data. But remember, self-serviceable data is just one piece of the puzzle.
An all-in-one data operations platform like Keboola provides a comprehensive solution beyond that. With an entire suite of tools, you can empower your non-technical users while ensuring fully managed and governed data.
Contact us and discover how to handle growing data volumes and user demands without increasing the burden on the technical staff.