Getting the Most From Your Modern Data Platform

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A robust, modern data platform is the starting point for your organization’s data and analytics vision. At first, you may use your modern data platform as a single source of truth to realize operational gains — but you can realize far greater benefits by adding additional use cases. In this blog, we offer guidance for leveraging Snowflake’s capabilities around data and AI to build apps and unlock innovation. 

A three-phase approach to expanding data platform capabilities

Enterprises may face a slowdown in their data platform maturity journey after migrating their legacy data systems to a cloud-based data platform, especially when using a lift-and-shift approach. 

In contrast, when organizations migrate to Snowflake, they have a wide-ranging set of capabilities to explore. By making full use of these functionalities, they can enable new use cases and drive new data, AI and apps initiatives to enhance the customer experience and expand their data platform for the better.

At LTIMindtree, a key system integrator partner of Snowflake, we believe there is a simple, three-phase approach to help your organization expand its data platform capabilities:

  • Phase 1 – Migrate: Move your legacy platform’s data and analytics functionality to Snowflake. For more info on accelerating your migration, click here.
  • Phase 2 – Modernize: Uplevel your data platform usage with new technical functionalities and business capabilities.
  • Phase 3 – Monetize: Integrate capabilities to increase revenue generation and improve customer experience.
Chart showing value, differentiators, and business impacts for three phases of a data platform maturity journey, which are Migrate, Modernize, and Monetize.
Figure 1: Drivers and success criteria for data platform initiatives.

Phase 1 – Migrate: Move your legacy data system to Snowflake

In the Migrate phase, you’ll move your data and workloads to Snowflake, and thereby resolve the cost concerns and performance bottlenecks associated with your legacy data warehouse. This phase empowers you to establish a foundation to linearly scale your data platform and involves detailed mapping of desired business capabilities to Snowflake technical functionalities and creating an overarching data vision. Focus areas include:

  • Migrating your current data functionalities and KPIs to Snowflake.
  • Determining an architecture and a scalable data model to integrate more source systems in the future. 
  • Finalizing the new business capabilities and use cases to be enabled in the next phases.

The benefits of migrating to Snowflake start with its multi-cluster shared data architecture, which enables scalability and high performance. Features such as auto-suspend and a pay-as-you-go model help you save costs. Additional processing capability with SQL, as well as Snowflake capabilities like Stored Procedures, Snowpark, and Streams and Tasks, help streamline operations.  

LTIMindtree’s PolarSled Accelerator helps migrate existing legacy systems, such as SAP, Teradata and Hadoop, to Snowflake. You can also incorporate Snowflake’s built-in authentication, authorization and security features to enhance governance from the ground up, and enable a basic DataOps setup to implement CI/CD. 

Snowflake Cortex, meanwhile, allows you to experiment with out-of-the-box generative AI (gen AI) capabilities that can enhance your migration and integration experience, such as generating SQL with native language prompts, improving searchability and deriving insights from documents and serverless functions.

Value dimensions for the Migrate phase: 

  • Reducing the operational costs of legacy MPP data platforms
  • Mitigating the risks associated with legacy systems that impede scalability and performance
  • Facilitating timely insights

Phase 2 – Modernize: Embrace new technical functionalities and business capabilities 

The Modernize phase is all about increasing accessibility and agility. You’ll expand upon baseline Snowflake functionalities by exploring new use cases that deliver benefits to both technical and business users. Focus areas for this phase include:

  • Enabling business capabilities in Snowflake by solving for new use cases
  • Optimizing the operationalized Snowflake platform
  • Integrating more source systems and enabling new consumption patterns
  • Leveraging observability capabilities, enabling chargeback and cost optimization
  • Empowering workers through data democratization

Implementing near real-time processing and reporting capabilities is a good initial step in this phase — they enhance your stakeholders’ ability to make timely decisions, which translates into faster time to insights and improved responsiveness. 

From there, you can address more complex use cases, such as creating a 360-degree view of customers by integrating systems across CRM, ERP, marketing applications, social media handles and other data sources. Implementing Snowpipe streaming service enables ingestion of data and messages in near real-time, enhancing the agility of your data processing. Upgrading your daily and weekly batch jobs to operate on an hourly basis or in micro batches allows you to provide more frequent updates and reports to business users. 

With this single view of near real-time, cross-organization data, your marketing teams can deliver better-targeted personalized recommendations and offers at the most relevant moment in the purchase cycle, improving campaign effectiveness and enhancing overall customer experience. To further improve data access and engagement, integrate Streamlit into your data workflows and allow data analysts and scientists to create highly visual and interactive apps that provide a relatable, intuitive data experience for employees and end users alike.

LOB teams aren’t the only ones who will benefit from expanding your use of modern data platform features. Addressing various aspects of observability with tools that offer advanced capabilities for platform cost optimization (such as LTIMindtree’s FinOps and Snowflake Cost Optimization services, available on Snowflake Marketplace), monitoring and data quality tracking empowers your operations team to proactively take action on data pipelines. This smoothes out workflows and helps teams swiftly mitigate potential issues. 

Your ops team can also automate and streamline DataOps, helping to boost productivity and accelerate time-to-market for new initiatives. Snowflake governance capabilities help you uphold and enforce data integrity, compliance and security policies.

As you take on new use cases, you may find that you need additional data to add context to and deepen your analysis initiatives. Incorporating third-party data products from Snowflake Marketplace allows you to add new dimensions to your insights. And because Snowflake Marketplace offers apps and services in addition to data sets, you can access new functionalities and incorporate them into your workflows to unlock additional forms of insights. 

In today’s market, modernization also means AI, and many companies are focusing on building AI teams and growing AI capabilities to meet business demands for generative AI functionality. Snowflake Cortex provides gen AI capabilities out-of-the-box as a managed service to accelerate everyday analytics and AI app development. 

Serverless AI/ML functions put ML models and LLMs into the hands of all Snowflake users, regardless of their level of expertise, so they can quickly and securely tap into the power of AI. For developers, Snowpark ML acts as a toolkit to help you train, develop and deploy customized AI/ML models, empowering your organization to derive deeper and more tailored insights from enterprise data.

Value dimensions for the Modernization phase:

  • Further cost reduction with a focus on FinOps
  • Cost optimization and risk reduction due to the ability to better operationalize the data platform
  • Improved governance
  • Shift toward a more data-driven culture and greater use of AI, along with new and varied sources of data and applications

Phase 3 – Monetize: Generate revenue from data and improve customer experience 

Now that you’ve expanded and modernized use of your data platform, you can turn it into a revenue-generation channel. This phase empowers you with multiple streams to obtain quantifiable economic benefits, such as direct sales of data sets or introducing “insights-as-a-service” offerings that sell derived insights and trends to interested consumers. 

Boosting revenue is just one element of monetization, however; you can also improve several facets of the user experience by making data and apps easily available. Focus areas for this phase include:

  • Monetizing data products and services, while improving data and insights accessibility for end users
  • Driving innovation among stakeholders by enabling advanced business capabilities 
  • Improving stakeholder and consumer experiences 
  • Adopting and deploying AI- and gen AI-driven capabilities
  • Building new analytical and gen AI apps and data products

The path to monetizing your data, services and apps involves Snowflake Collaboration capabilities and Snowflake Marketplace. Snowflake Secure Data Sharing and cross-cloud Snowgrid functionality make it possible to share data and exchange real-time insights with partners, vendors and suppliers across clouds and regions in a privacy-protected manner. Snowflake Marketplace is the “storefront” for your third-party data sets and Snowflake Native Apps, making them available to your customers or to the entire Snowflake AI Data Cloud. Integrated Marketplace Monetization capabilities can manage maintenance and billing, simplifying the process for both you and your customers. 

With data, AI and apps on the Snowflake data platform, you can address AI and gen AI use cases and explore new business capabilities. For example, you can add near real-time personalization to your web portal to deliver tailored pages aligned to your customers’ interests and improve conversion rates. Adding gen AI capabilities to chatbots so they can answer natural-language questions helps internal stakeholders find the materials and expertise they need faster, not to mention improving online customer service. 

Empower your developers, analysts and data engineers with Snowflake AI services, such as Snowpark ML, Cortex and Snowflake Native Apps with Snowpark Container Services, to inspire innovation and expand use of your data platform’s capabilities. Developers can build and package apps/UI in any programming language (C/C++, Node.js, Python, R, React, etc.) and host apps in Snowpark Container Services. Not only does this benefit your own organization, but you can turn that hard work into a new revenue stream by listing your Snowflake Native Apps in Snowflake Marketplace.

Value dimensions for the Monetization phase:

  • Increased revenue from data, services and applications listed on Snowflake Marketplace 
  • New business capabilities utilizing AI and apps
  • Improved customer experience and satisfaction

Putting the three maturation phases into action

Snowflake’s robust data, AI and apps capabilities make it easier for your organization to “grow up” on your data platform. You can expedite this maturation journey with a clear, phased approach, focused on delivering business value, enabling tangible revenue contributions to the organization and improving customer experience. Organizations take the first step with migration; once the right foundation is in place, they can increase the value derived from their data as they adopt advanced Snowflake features (see figure below). 

Figure 2: Value realization in the Snowflake journey

The three-phase journey represents a logical and proven approach adopted by many organizations, but it is not a strict mandate. You do not need to completely align with the phases or enable all mentioned functionalities within a phase before moving to the next. Snowflake’s architecture is flexible and doesn’t enforce excessive technical dependencies, allowing your enterprise to address business use cases based on its goals, vision and changing needs. 

Next steps

Check out LTIMindtree’s PolarSled FinOps cost optimization framework on Snowflake Marketplace. For more on migrating to Snowflake, check out our on-demand webinars and read our ebook “5 Questions to Ask When Considering a Migration to Snowflake.” top modernizing your data lake with Snowflake, watch our on demand webinar. If you’re interested in turning your data and apps into a revenue stream, read this blog or download the “Modern Data Monetization Strategies” ebook.