TICK data is the most granular set of data in the financial services space. It is the largest and arguably the most instrumental set of data when it comes to the objective of market data optimization—spanning over 40 years, more than 500 exchanges, exceeding 6 petabytes of history, and consisting of some 60 billion daily records.
Historically, tick data has been something of a double-edged sword. On one hand, it offers crucial insights that can make or break entire investment strategies. On the other hand, the same granularity that puts it in such a privileged place within the banking, investing, and wealth management ecosystems also introduce a unique set of data management and analytical requirements.
Nevertheless, the growing pressure to drive alpha and outperform competitors in tight markets makes effective TICK data management more important than ever. This means the clock is ticking for financial service providers to dial in on data strategies and architectures equipped to capitalize on TICK data as an asset.

Why Do Financial Services Institutions Struggle with TICK Data?
Before exploring the how and why of Snowflake’s latest, TICK-powered market data optimization capabilities (and Hakkoda’s accelerated pathway to deploying them), it is worth taking a quick look at what makes TICK data so hard to use historically. Some of the biggest obstacles include:
- Costly Storage Overload: TICK data is made up of billions of records and already amounts to petabytes of data. This volume also continues to grow daily along an order of multiple terabytes. Additional challenges are introduced when you consider this data must be fed from third party market providers, either via SFTP or API.
- Slow, Pricey Queries: For banking and investment institutions still locked in legacy data stacks, poor architectures and costly query performance can liken TICK data analytics to searching for a needle in a haystack. These limitations are further exacerbated by timestamp precision issues and TICK data’s granular,millisecond-level detail.
- Data Silos and Special Analysis: TICK data is analyzed with time series functions and needs to be enriched with other datasets to be rendered useful. The duplication and mutation of TICK data, meanwhile, introduces a reputational risk for incorrect reporting.
What Happens When These FSI Institutions Lose Control?
As the market continues to grow and accelerate, meanwhile, institutions are missing new revenue opportunities, increasing costs, and increasing risk. These institutions end up facing issues across the entire enterprise, including:
- Missing Front Office Revenue Opportunities: The inability to generate revenue based on near real-time workflows and decisions, combined with a lack of top-down budget approval.
- Increased Risk in the Middle Office: An increased need for data governance to model risk of assets, liquidity, and portfolio construction, compounded by expanding CDO remits and charges to drive both control and value.
- Suboptimal Back Office Analytics and Higher Costs: Skyrocketing costs of on-premises storage and duplication, made worse by a lack of automation and consistency in compliance reporting and time expended reconciling settlements and trades.

How the Snowflake AI Data Cloud Addresses TICK Data’s Biggest Pain Points
Fortunately for institutions teetering on that precipice, Snowflake’s market data optimization capabilities are uniquely tailored to meet the aforementioned demands of TICK data, providing the scalability and performance necessary for handling high-frequency financial information.
Recent enhancements and features around vectorization, growing support for time-series functions, and additions to the Snowflake Marketplace have further expanded on these capabilities and introduced new opportunities, including:
- Unlocking the Doors to the Front Office: The largest online analytical processing (OLAP) workloads are in a business’s Front Office. Snowflake’s ability to support time series functionality provides these Front Office stakeholders with enriched insights accessible in near real-time.
- Centralization of Data: Remember, TICK data relies on being enriched by other data sources. Snowflake excels in this space, and supports the ability to streamline ELT pipelines through its Marketplace and act as a centralized hub for data collaboration.
- A Single Platform to Address All Needs: Snowflake doesn’t just bring data sources together. Rather, it draws a comprehensive range of functions and capabilities together in one unified platform, with tools like the Snowflake Marketplace, Snowpark, Cortex, Polaris, Horizon, and Datavolo all on deck to address a diverse set of data management, analytics, and AI needs.
Accelerating Market Data Optimization with Hakkōda
Now that we’ve articulated a handful of the ways Snowflake is transforming the way businesses work with TICK data, it’s time to address the elephant in the room—migrating TICK data to Snowflake in the first place.
To this end, Hakkoda is uniquely positioned to accelerate and ensure success in migrating TICK data to Snowflake.
- Comprehensive Data Strategy: Hakkoda brings not just technical expertise but also industry depth to our data modernization engagements, resulting in tailored migrations that align with industry requirements and outcomes with minimal disruption to everyday operations.
- Modern Data Pipelines: Hakkoda’s AI-enabled migration approach streamlines traditional data assessment and ETL processes. This means a shorter time-to-value and a reduction in human error when compared to other migration methods.
- A Unified Transaction Analytics Platform: Hakkoda’s Modern Asset Management & Business Analytics (MAMBA) accelerator offers an end-to-end asset management solution, including a built-in data model that eliminates silos and improves time-series analysis.
- Optimization & Security: Hakkoda steps beyond lift-and-shift migration approach, empowering our customers with performance tuning, encryption, role-based access to ensure ongoing success.

Partnering to Unlock TICK Data’s Full Potential
By bringing together modern data solutions with deep industry expertise and experienced, AI-enabled consulting, Snowflake and Hakkoda offer a robust solution for overcoming the challenges associated with TICK data and unlocking new opportunities for financial services firms to drive alpha.
Snowflake’s scalable, cloud-native platform efficiently handles high-frequency data, ensuring quick, reliable processing that supports informed decision-making in volatile markets. Meanwhile, Hakkoda’s expertise in migrating TICK data to Snowflake and MAMBA’s host of time-series analytics offerings work to accelerate returns on your Snowflake and TICK data investments.
Ready to unlock the full potential of TICK data, with faster time-to-value across your entire organization? Talk to one of our experts today.