How to maximize Snowflake’s capabilities with Calibo’s self-service platform 

The demand for robust and efficient data platforms is more significant than ever.  

In this video, Marcel Kintscher, Sales Engineering Consultant at Calibo, shares how Calibo, leveraged together with Snowflake, enables organizations to build data platforms faster.

Through an illustrative example of the company “Tasty Bites,” Marcel demonstrates how the seamless integration of Calibo and Snowflake working together can propel companies toward accelerated data and digital transformation. 

Watch the full video here to see the step-by-step process.

Understanding the need for integrated data platforms 

Enterprises like Tasty Bites strive for excellence and innovation in an ecosystem characterized by complexity and diverse stakeholder requirements. These organizations must manage a plethora of different stakeholders, including partners, citizen developers, business leaders, and technologists, each with unique interests and expectations. 

Standardized processes are often lacking in the development cycle, leading to ad-hoc operations and bottlenecks in product delivery.  

Additionally, the vast and complex landscape of SaaS, on-premises, and cloud technologies presents significant challenges in maintaining efficient software delivery processes, exacerbated by the need for robust security and compliance standards. 

Calibo addresses these challenges by fostering a collaborative environment where diverse personas—ranging from business owners to developers and technologists—work together seamlessly. By breaking down silos, Calibo enables faster development of data products and digital applications, empowering organizations to respond swiftly to market demands. 

The role of Calibo’s self-service development platform 

Calibo’s self-service development platform is central to addressing complexities inherent in technology ecosystems and processes. The platform comprises three core components: the Product Release Orchestration engine, the Internal Developer Portal, and the Data Fabric Studio (previously called Data Pipeline Studio).

Together, these components create a unified environment for product development, allowing organizations to move swiftly from ideation through design, development, deployment, and monitoring. 

The orchestration engine integrates with existing technologies across the development cycle, ensuring that each technology’s unique benefits are leveraged. Calibo’s open integration layer connects seamlessly with cloud platforms, CI/CD pipeline automation tools, and various software applications, including Salesforce, ServiceNow, and GitLab, enabling comprehensive management and execution of development activities. 

Streamlining user onboarding and technology integration 

Marcel emphasizes that effective use of Calibo begins with user onboarding and technology integration. By connecting Calibo to Microsoft’s Active Directory or similar solutions, organizations can smoothly onboard users, assign roles, and create development teams.  

Crucially, Calibo’s platform supports integration with multiple cloud platforms, such as AWS and Azure, alongside a diverse array of tools ranging from Jenkins and Kubernetes to source code repositories like GitLab. This enables organizations to leverage both open-source technologies and native functionalities. 

Policy templates within Calibo further streamline the development process by defining the technologies and processes for each stage, ensuring consistent and efficient deployment. These templates automatically provision allowed technologies, significantly reducing setup time and potential errors during development. 

Building the Tasty Bites data platform 

In illustrating Calibo’s capabilities, Marcel walks us through building a data platform for Tasty Bites—a fictional organization aiming to develop internal and external digital applications. The project begins with creating a digital portfolio and setting strategic goals, such as creating a dashboard for truck drivers to track sales performance and predict customer churn using machine learning. 

Creating data pipelines 

Building on this framework, Marcel demonstrates the development of data pipelines using Calibo’s Data Fabric (Pipeline) Studio (as below). Starting with data source identification, Calibo allows users to scrape data from various systems—RDBMS, SaaS applications, or cloud storage—and ingest it into Snowflake. Integration with Databricks further enhances this process, enabling rapid data transfer and transformation tasks without intensive coding. 

Calibo facilitates seamless data workflows by automating configuration steps and selecting appropriate data processing actions, such as append, override, or merge operations, within Snowflake. The platform’s integration capabilities ensure that even complex security tasks, such as storage integration setup, are manageable within a uniform environment. 

A simple way to define, run, and monitor how your data flows.

Ensuring data quality and transformation 

Calibo’s commitment to maintaining high data quality is evident through its use of data analyzers, profilers, and issue resolvers. These tools allow teams to check for data completeness, rectify issues, and ensure data integrity before proceeding with downstream analytics.

With features like deduplication, outlier handling, and data cleansing, Calibo enables effective data preparation without writing extensive SQL code, ensuring consistency and accuracy across data assets. 

Developing applications and dashboards 

After data pipelines are established, attention shifts to developing applications and dashboards. Calibo supports the creation of BI tools like dashboards for sales monitoring and customer-facing applications through its integration with platforms like Qlik Sense.

Users can seamlessly connect Snowflake data to BI applications, enabling dynamic, real-time insights tailored to specific business needs. 

Machine learning and custom application development 

To deliver enhanced predictive capabilities, Marcel highlights how Calibo integrates machine learning models—such as those created using JupyterLab notebooks—into data pipelines.

This integration enables seamless deployment and monitoring of machine learning outputs, enriching data platforms with advanced analytics capabilities. 

Calibo also simplifies custom application development by offering integrated development environments (IDEs) that sync with repositories like GitLab.

Developers can easily configure, deploy, and manage applications using technology stacks that suit their requirements, enhancing efficiency and reducing development cycles. 

Key takeaways 

• Streamlined onboarding and integration: Calibo simplifies user onboarding and technology integration, creating unified development teams equipped with the right tools and environments for rapid project initiation. 

• Unified platform for complex ecosystems: Calibo’s orchestration engine connects a myriad of technologies, ensuring seamless collaboration across stakeholders and enabling efficient data product development. 

• Robust data pipeline development: Through intuitive tools like Data Pipeline Studio, Calibo facilitates fast and effective data pipeline creation, ensuring high data quality and integration with Snowflake. 

• Efficient app and dashboard development: Calibo’s platform supports the end-to-end development of BI tools and custom applications, leveraging existing data for actionable insights. 

• Seamless machine learning integration: Integration with machine learning models enhances predictive capabilities, embedding advanced analytics throughout data pipelines. 

Through comprehensive features and strategic integrations, Calibo, powered by Snowflake, empowers organizations to accelerate their data and digital transformation initiatives.  

By embracing this joint solution, organizations can navigate complex technology ecosystems more effectively, driving productivity, innovation, and competitive advantage. 

Watch the full video here to see all the details and the step-by-step process.