Hakkōda’s Composable Architecture, Part 1: Laying a Strong Foundation for the Data Innovation Journey

How Hakkoda’s flexible, composable architecture improves operational efficiency, opens the path to data innovation, and drives positive business outcomes.
September 5, 2023
composable architecture

Architecture plays a crucial role in shaping business outcomes by ensuring efficient data management, accessibility, and analysis. At Hakkoda, our focus has always been creating business impact while driving a composable and iterative approach to standing up architecture. The main components of a well-thought-out architecture are infrastructure, integration, data, security, and change management. The sole purpose of a robust architecture is to deliver improved capabilities for the business that are resilient and future-proof. 

We believe architecture is a technical canvas where our seasoned architects stand up services to deliver a data platform as a service to enable a store front of data products like semantic layer, curated dashboards, AI/ML models, and native applications. Hakkoda is purpose-built around Snowflake, and we leverage Snowflake’s Data Cloud plus native cloud platform capabilities to fuel our customers’ data innovation journeys.

To enable this data innovation journey, we drive strategic initiatives around Snowflake and the modern data stack. Hakkoda believes the data innovation journey reduces technical debt, improves data accuracy, increases the velocity of data product delivery, reduces data redundancy, and brings economies of scale. Our innovation journey, standard frameworks, and accelerators, aided by a flexible, composable architecture enable proactive support and drive governed end-user adoption.

The Data Innovation Journey with Hakkōda

At Hakkoda, we believe that data maturity can be assessed and categorized across four discrete stages: from chaos, to order, to insight, to innovation. We work with clients to understand where their organizations stand in the modern data landscape, then help them modernize their data stack, architecture, and processes to achieve what comes next. Your organization’s Data Innovation Score helps us to put together custom recipes, improve the delivery of our services, and mitigate risks so that you can overcome whatever data obstacles stand between you and your next desired business outcomes. 

Calculate your organization’s Data Innovation Score.

Building Data Innovation Roadmaps with Composable Architecture

A current state assessment coupled with a future state recommendation paves the roadmap for data innovation. At the core of these strategic initiatives are the following foundational design and architectural concepts: 

  • Cloud Engineering Guidance for the Modern Data Stack Addresses:
    • Cloud foundations and native cloud services which are stood up to enable the data platform as a service
    • Infrastructure as code and automation (cloud formation, scripts monitoring, notifications, and alarms)
    • Tenancy, scale, infrastructure governance, spend optimization
    • Repository management and configuration
  • Data Engineering and Data Design Standards Address:
    • Engineering for data topologies (lakes, warehouses, and vaults)
    • Data migrations and modernization around Snowflake.
    • Addressing patterns – data integration, data ingestion, transformations, semantic layer, metric store, native apps and headless BI
    • Event- and metadata-driven continuous data pipelines 
    • Data lineage and governance
    • Testing and audit framework 
    • Data operations and DevOps 
    • High availability and disaster recovery in accordance with Snowflake’s platform tiers (enterprise, business critical and multiple workloads)
    • Automation and DAG strategy.
  • Regulatory Compliance, Data Security and Access Management Address:
    • Snowflake and platform security
    • Data Shares, encryption, masking and obfuscation
  • Modern Data Stack – Platform Recommendations:
    • Business architecture, capability matrix and persona mapping
    • Hakkoda’s cloud-first point of view on enablement and adoption 

Addressing Data & Security Governance and Anchoring Around It

By implementing appropriate data governance practices and security measures, businesses can protect sensitive data, maintain customer trust, and comply with legal and industry regulations. Prime focus of this approach from the beginning should be mitigating data risks. Ensuring data privacy can prevent costly breaches, reputation damage, and legal consequences, positively impacting business outcomes.

Think of architecture through the lens of a Wardley Map. The biggest impact happens with user adoption across the various capabilities. That is dictated by the value chain on the y-axis. The implementation and execution of the architecture is the evolution in a composable manner. We are enabling various capabilities around data for enterprise customers and the evolution of the architecture addressing the data innovation journey drives visible increased impact with respect to the value chain.

Hakkoda - blog - composable architecture

Composable Architecture Means Adaptive Scalability

As the architecture evolves and starts delivering various capabilities, the sentiment around it moves from reactive, to stabilized and consistent, to actionable, to visionary. At Hakkoda, we strive for innovation within the architecture’s evolution but approach both infrastructure and data with situational awareness. 

As businesses grow, their data requirements also increase. A robust data architecture enables scalability, allowing organizations to handle larger volumes of data without compromising performance. Additionally, an agile composable data architecture can adapt to evolving business needs and changing technologies, ensuring that data infrastructure remains flexible and responsive to new requirements.

data innovation journey

Composable Architecture Blends Rapid Innovation with Change Management

A composable architecture can be rapidly deployed and can quickly fuel insights and innovation with industry-standard security in place. The modern data stack brings velocity, rigor and standardization to the capabilities being delivered. This enables Hakkoda to drive pre-identified patterns around the data innovation journey and mitigating risks along the way. 

Snowflake data cloud’s abstraction of various data engineering concepts makes the platform revolutionary. The technology partner landscape around Snowflake drives rapid innovation. We are able to move from infrastructure and services provisioning, to data ingestion, to data transformations, validations, and deployment in a very reasonable timeframe that works for our clientele’s change management needs. Knowledge graphs drive lineage from data products to transformations to data sources. 

Agility is key in the data innovation journey. Fail fast and iterate while proving out use cases with purpose built architecture. Always account for cloud-first, self-managed, fully-hosted services.  It is Hakkoda’s recommendation that we preempt a few Infosec reviews with our clients to complete a preliminary walkthrough of the composable architecture we bring to the table. This makes onboarding services for a client a risk-free exercise with proper assumptions and responsibilities called out. From there, we can embark on the data innovation journey with a change management construct in place for both technology and people.

Building a Composable Architecture in the Snowflake Data Cloud

Ingestion as a Service: This is where Fivetran comes in with its fully managed enterprise-grade connectors to Saas and on-premise applications. Fivetran’s out of the box staged schemas for Snowflake enable rapid staging and ingestion into Snowflake. The ingestion service is continuous, self-healing, and accounts for change data capture and schema drift. 

Transformation as a Service: Once the data is in Snowflake Colalesce’s column aware transformation capabilities brings speed to data transformations. It’s fully managed and scalable. Coalesce is a GUI based Transformation platform which code generates SQL and does efficient push down into Snowflake to deliver a dimensional model or a Data Vault. Coalesce comes with pre configured Dimensional and Fact nodes and a Data Vault package that can be enabled rapidly with a testing node framework in place.

Orchestration as a Service: Leverage fully managed Airflow or any other automation service on the cloud that integrates via APIs to Fivetran and Coalesce. This establishes a knowledge graph of the flow of the architecture. 

By surrounding the above with infrastructure, cost monitoring, and a notification service for active Tier 1 triage, we have now rapidly established an agile composable architecture that enables data as a service in the Snowflake Data Cloud. A well-designed architecture in this vein enables businesses to efficiently manage, access, and analyze data. This, in turn, leads to better decision making, improved operational efficiency, enhanced customer experiences, and ultimately, positive business outcomes.

Partnering with Hakkōda for the Data Innovation Journey

At Hakkoda, we bring the power of the Snowflake Data Cloud together with expertise across the modern data stack to solve our customers’ most menacing data problems while guiding them through the data innovation journey. With a focus on improving operational efficiency and driving positive business outcomes, Hakkoda’s approach is centered on a flexible and iterative model that spans infrastructure, integration, security, and change management to help your organization harness the full power of its data while building for what comes next. 

Ready to see how Hakkoda’s composable architecture can help catapult your organization along the path to innovation? Let’s talk.


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