Unleashing the Power of Self-Service Analytics with Snowflake-native Kubit

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Travis Strickland
Principal Solutions Engineer
In this article


Kubit offers the market-leading self-service analytics platform that runs natively on Snowflake.

In today’s data-centric world, the ability to sift through large amounts of information and extract actionable insights quickly is not just an advantage—it’s a necessity. With IDC predicting that global data volume will surpass 160 zettabytes by 2025, a tenfold increase from 2017, having the ability to quickly access, analyze, and act on company data that you can trust will be a competitive differentiation point that organizations will not be able to ignore.

The Rise of Snowflake

This explosion of data has led to the creation of an entirely new generation of cloud data warehousing technologies, all positioned to help organizations have more flexibility and control of their data with a scalable cost model. Among these companies, Snowflake is a trusted leader of thousands of organizations, realizing the value and necessity of data for their business.

While there are numerous ways customers can derive value from Snowflake, this article, 8 Reasons to Build Your Cloud Data Lake on Snowflake, highlights several reasons why organizations turn to Snowflake to enable a more robust data practice in their organizations. The critical takeaway from this article is that when you store data in Snowflake, your experience is drastically simplified because many storage management functionalities are handled automatically. Yet, there are still some challenges and limitations in accessing and activating that data, which we will discuss here.

The biggest challenge and most common question is:
How do non-technical (non-Snowflake) users access and use the data that is relevant to them?

The reality is that this question persisted long before cloud data warehousing was around. Company data was still held directly in databases, and any analysis required a database administrator or engineer to access it for the business. This is where product analytics was born.

The Birth of Self-Service Product Analytics

Product analytics emerged from the frustration of traditional data analysis methods. While querying databases for insights was possible, the process was slow and cumbersome, requiring significant technical expertise. Business intelligence (BI) tools offered some relief but were often rigid and pre-configured for specific reports. This meant limited flexibility for stakeholders who needed to explore data independently and answer unforeseen questions quickly. The rise of product analytics addressed this need for speed and exploration. It provided user-friendly interfaces and intuitive data visualizations specifically designed to analyze user behavior within digital products rapidly. This empowered stakeholders to delve deeper into user data, identify trends and pain points, and ultimately make data-driven decisions to optimize the product and user experience.

Product analytics has always been pivotal to understanding customer behaviors, enhancing product offerings, and driving user engagement. However, the landscape of data analytics has undergone a seismic shift with the advent of Big Data, escalating both the opportunities and challenges it brings.

Traditional product analytics tools, while offering some level of self-service analytics, essentially create data silos. This situation conflicts with the organizational drive and investment toward cloud data warehousing. The core issue with this setup is that data residing outside the warehouse leads to concerns about trust and integrity. Moreover, organizations find themselves duplicating efforts and squandering resources to manage and reconcile data across disparate locations.

Enter Kubit’s Snowflake-native Product Analytics

Kubit is the first Snowflake-native product analytics platform purpose-built to address the limitations and challenges inherent in traditional product analytics approaches. Specifically, providing a self-service analytics platform native to Snowflake allows organizations to access their complete dataset with flexibility, agility, and trust. There are other value drivers as well including but not limited to:


  1. Self-Service Analytics
    Self-service analytics refers to the ability for non-technical users to access and analyze data without needing assistance from data engineers and analysts. This is made possible by Kubit’s intuitive and easy to use business interface that allows users to directly query and manipulate their data in real-time, without the need for SQL knowledge or complex ETL jobs.
  2. Flexibility
    Kubit empowers organizations to analyze ALL of their data within Snowflake, going beyond mere clickstream analysis to encompass a wide array of sources including marketing, product, customer success, sales, finance, and operations. By aggregating this diverse data, organizations are equipped to delve into one of the most vital inquiries – why? It’s only through a holistic overview of all data points that teams can begin to unravel this question, paving the way for more informed decision-making.
  3. Data Integrity
    The abundance and completeness of data for analysis becomes irrelevant if there’s a lack of trust in the data itself. Hence, it’s imperative that Kubit can directly access Snowflake, serving as the ‘single source of truth,’ to guarantee the accuracy and reliability of data throughout its lifecycle. This ensures compliance, operational excellence, and builds trust within any data-driven environment.
  4. Total Cost of Ownership
    Gartner’s research indicates that organizations can reduce their Total Cost of Ownership (TCO) by up to 30% through migrating to cloud data warehouses. Kubit further enhances this advantage by assisting organizations in streamlining their analytics technology stack. This enables the reallocation of valuable resources, which are currently underutilized in efforts to create, manage, measure, and validate data and analytics with tools not designed for these tasks. Kubit also cuts down on double paying for storage and compute of data residing in yet another repository for analytics purposes.
  5. The Real-world Impact
    The advantage of adopting a Snowflake-native strategy for self-service analytics lies in the ability of organizations to be operational within days, not weeks or months. This rapid realization of value empowers companies to immediately concentrate on their most crucial and impactful areas. For instance, this TelevisaUnivision case study illustrates how they focused on boosting retention rates for their ViX streaming service, showcasing just one of many successes where Kubit has facilitated the achievement of significant outcomes.
  6. Implementation Insights
    Kubit offers far more than just self-service analytics software; it boasts a world-class team dedicated to ensuring customer success through comprehensive onboarding, enablement, training, and support. Our commitment goes beyond just providing technology; we actively lean in with our customers to help create value and success.

The immediate advantages of leveraging Snowflake-native product analytics are evident, including improved decision-making capabilities and more profound insight into customer behaviors. Moreover, the long-term benefits herald a continuous shift towards predictive and prescriptive analytics, fundamentally transforming the future of business data interaction.

Get Started Today

What are you waiting for? Are you a Snowflake user ready to try Snowflake-native Kubit? Feel free to Take a Tour or Contact Us to discuss your specific goals and how Kubit can help you achieve them. Our team is here to provide personalized support and ensure a smooth onboarding experience.

If you want more information about our offering, including detailed features and implementation guidelines, check out our technical documentation. Whether you’re an experienced data analyst or a Product Manager just starting out, our resources are tailored to meet your needs and help you maximize the potential of your data.

Travis Strickland
Principal Solutions Engineer

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