Unlocking Revenue with Embedded Analytics
We are pioneering the realisation of embedded analytics solutions for software companies. Let us be your travel guide on the journey to transforming how your customers and partners experience data.
Why Embedding Analytics Into Your Product?
20% upsell opportunity
80% Cost Reduction
Competitive Advantage
Analytics Journey-as-a-Service
Claudy exists to serve you as an experienced guide on the embedded analytics journey. Our Journey-as-a-Service offering is built from packages that help you overcoming any obstacle and any peak with certainty.
Join us at any stage in the journey.
Data Cloud Evaluator
Time: 3-4 weeks
Avoid wasting resources on manual data handling and start the analytics journey with the Snowflake Data Cloud. We partner with you to proof Snowflake’s market-leading performance and build a first case, completely customised to your specific needs.
Data Cloud Kickstarter
Time: 3-4 days
Convinced about Snowflake and ready to climb the next mountain? Prevent long-term cost of a bad foundation and trust us with the setup of your scalable data platform. Be ready to deliver on your analytics roadmap in days instead of weeks.
Intelligence Suite Builder
Time: 2-4 months
Understanding and making sense of all your data can seem like the longest and steepest hike on this journey. Keep cool, we’ve got your back! This package is filled with service components that help you to get any analytics project off the ground and build your intelligence suite in no time.
Embedded Evaluator
Time: 3-4 weeks
Ready to see the return on analytics? Let’s tackle the last mile on this journey together. We help you selecting the right technology and build your first embedded analytics product to test out with your customers.
Embedded Realiser
Time: 1-2 months
Your customers love it and want more? We partner up with you to bring your complete embedded analytics product to life. Every mountain you’ve climbed so far, will be worth the view you get from this one. Together, we turn analytics into a profit center for your company.
Partners And Technologies
We work with carefully selected partners and cloud-agnostic technology vendors to help you succeed on the analytics journey.
We partner with Snowflake to build the backbone of the world’s future data and AI applications together.
Our local, Swiss consulting partner for any legal matters in technology and data.
The leading cloud data platform provider, providing unlimited scalability for any data analytics and AI needs.
Awarded Snowflake’s Data Integration Partner of the Year. The best tool to build data models faster and automate data governance strategy execution.
The simplest, open-source application framework. Natively available in Snowflake. Best for prototyping and testing of data apps.
The classic under the analytics platforms. Leader for enterprise, self-service analytics. Broadest visual capabilities.
Microsoft’s Business Intelligence platform. A price-competitive choice, especially if you’re an existing Microsoft customer.
The open-source alternative for any ELT job. Great for prototyping. Good choice if you’re on a tight budget.
Enablers for state-of-the-art embedded analytics apps. Maximum customisability at minimum cost.
Great challenger in the BI market. ‘Ask data’ at its core. Good for internal and embedded analytics.
Frequently Asked Questions.
Looking for quick guidance on your analytics journey? Get some fast answers on the most frequently asked questions of our customers.
Embedded analytics is the integration of data analysis and reporting directly into your software or platform. It empowers users to access real-time insights and visualizations without leaving your application, enhancing user engagement and informed decision-making. Ultimately, it is the most powerful tool software companies have to proof their value to customers.
To nurture a data-driven culture:
- Lead by example, prioritize data in decision-making.
- Provide access to data and analytics tools.
- Foster data literacy through training and workshops.
- Encourage data sharing and collaboration.
- Recognize and reward data-driven achievements.
- Continuously communicate the value of data-driven insights.
- Cloud Data Warehouse: You can start with Amazon Redshift, Google BigQuery, or Snowflake for scalable data storage and compute for data processing.
- ELT Tools: You can use ELT tools like Apache NiFi, Talend, or Apache Spark for simple data integration.
- Data Streaming: Implement Apache Kafka or Apache Flink for real-time data ingestion.
- Data Visualization and Analytics: Leverage Tableau, Power BI, or Looker for insights and Python with Pandas, NumPy, or machine learning for advanced analytics.
- Embedded Analytics: Consider ThoughtSpot, GoodData or Streamlit for embedded analytics apps.
This stack provides a strong foundation for data-driven decision-making and growth.
To choose the right technology for your data analytics tech stack:
- Define your goals and requirements.
- Assess your data needs, scalability, and budget.
- Consider compatibility, performance, and security.
- Prioritize user-friendliness and support.
- Conduct a proof of concept.
- Research vendor reputation and future-proofing.
Involving stakeholders and careful evaluation will guide you to the best-fit technology for your analytics needs.
To ensure a high ROI on data analytics:
- Define clear business objectives.
- Focus on actionable insights that drive decisions.
- Continuously measure and evaluate ROI.
- Optimize analytics processes for efficiency.
- Invest in training and upskilling for your team.
- Stay agile and adapt to changing business needs.
- EMBED valuable analytics apps into your product to monetise your data with your customers and partners.
To visualize and share data effectively:
- Use a BI tool to create interactive dashboards.
- Create clear, audience-specific visuals.
- Ensure data accuracy and privacy to build trust in data.
- Leverage collaboration tools and seek feedback for improvement.
- Share via email, direct sharing in the warehouse, or embeds in your applications.
- Tell compelling data stories to make insights actionable.
These practices enhance data-driven decision-making and collaboration with your stakeholders, partners, and customers.
The level of programming involved in embedded analytics varies. It can require basic configuration and integration skills, such as using APIs or SDKs provided by analytics platforms. In more advanced cases, customization and coding expertise in languages like JavaScript, Python, or SQL may be necessary to tailor analytics components to your software application’s unique requirements.
If you don’t have a dedicated data analytics team, you can still leverage analytics effectively. Consider outsourcing analytics tasks to specialized firms or using user-friendly analytics tools that require minimal coding. Additionally, cloud-based analytics platforms often offer built-in features to simplify data analysis for non-technical users.
For a cost-effective data analytics stack on a limited budget, consider using open-source tools like PostgreSQL or MySQL for data storage, Apache Spark for data processing, Streamlit for data apps or tools like Metabase or Redash for visualization. Cloud providers like AWS, Google Cloud, or Azure also offer budget-friendly options with pay-as-you-go pricing.
To ensure scalability of your analytics tech stack:
- Use cloud services for elastic scaling.
- Opt for scalable data warehouses like Snowflake.
- Implement containerized applications with Kubernetes.
- Monitor performance and scale resources as needed.
If analytics queries strain your production databases too much:
- Consider query optimization techniques.
- If no success, implement a data warehouse for analytics.
- Use ETL processes to offload data overnight.
- Consider data historization options to keep track of changes in the production database
Offshore outsourcing is a great way to get affordable resources for the implementation of specific data analytics projects. However, typically these resources are lacking the strategic and cultural transformation capabilities to get your organisation from manual data processing to actually adopting modern embedded analytics solutions. Claudy offers you time and expertise from subject matter experts with deep industry know-how. We don’t provide time for money. We provide value for money.
To adhere to evolving data privacy regulations:
- Stay informed about new regulations.
- Conduct regular data audits and risk assessments.
- Implement strong data encryption and access controls.
- Appoint a Data Protection Officer (DPO) if required.
- Document data processing activities for compliance.
- Keep a data breach response plan ready.
- Train employees on data privacy practices.