HISTORICAL TICK DATA ANALYSIS

Tick History Workbench

A cloud-based analytics environment for high-precision historical tick data, enabling scalable analysis using familiar tools – without the complexity of managing infrastructure.

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  1. Overview
  2. Features & benefits
  3. Insights
  4. FAQs
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Analyse high-precision market data without the complexity

Analysing large-scale historical tick data requires significant infrastructure, specialist tooling, and engineering effort. For many firms, accessing and working with high-volume datasets can be complex, limiting the ability to explore data, test strategies, and iterate quickly across quantitative workflows.

Tick History Workbench simplifies access to high-precision historical market data by combining scalable cloud infrastructure, integrated analytics tools, and pre-configured analytical environments.

With SQL-based access to hundreds of petabytes of data (including Level 1, Level 2, and Level 3 feeds across global exchanges), it supports scalable analysis, visualisation, and model development using familiar tools and workflows – allowing teams to focus on extracting insights rather than building and managing data infrastructure.

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Features & benefits

Functionality to query and visualise capital markets data using tools you already know

Work with familiar tools and environments

Use SQL, Python and R within pre-configured Jupyter notebooks to analyse market data using the tools you already know, supported by a curated ecosystem of trusted analytics libraries.

Analyse Tick History – PCAP and more directly in the cloud

Query and explore Tick History – PCAP and other LSEG datasets without moving or replicating large datasets, accelerating access to packet-level market data analysis.

Run flexible analytical workflows

Perform ad-hoc analyses or schedule batch jobs using an integrated orchestration environment.

Visualise and explore market behaviour

Build dashboards and visualisations to analyse market activity, including advanced charting and 3D visual representations.

Accelerate development with Springboards

Leverage interactive examples, queries, and walkthroughs to develop and refine analysis more quickly.

Scale performance with distributed compute

Execute workloads across distributed compute using optimised cluster parallelisation. Built on a Dask-based architecture, Workbench enables scalable processing across multiple nodes, with secure deployment via SSO or within your own environment.

Insights

The new low latency equation: Speed, scale, and certainty

Explore how low latency strategies are being redefined by data scale, cloud delivery, and advanced capture technologies. In this article with The Trade, we uncover why speed alone is no longer enough to compete in today’s increasingly complex, data-driven global markets.
Download Read the article
PDF • 1.7MB

Market data normalisation for low latency environments: Addressing fragmentation challenges at scale

Fragmented market data continues to create hidden cost, risk and operational complexity in trading. In this expert talk we explore how firms are tackling market data fragmentation – and why LSEG treats a robust normalisation layer as core infrastructure rather than a downstream transformation step.
Download Read the expert talk
PDF • 590.1KB

FAQs

    • Workbench provides multiple ways to access and analyse licensed data, including SQL, APIs, notebooks, DuckDB, cloud storage and integrated data catalogues. Depending on your environment, you can also connect to enterprise data sources, data lakes and other approved datasets.
    • Yes. Workbench provides direct access to Tick History – PCAP and other LSEG datasets, enabling users to query, explore and analyse packet-level market data without moving or replicating large datasets.
    • Workbench supports popular analytics and development tools, including Python, R, SQL, Jupyter Notebooks, Visual Studio Code and Git integration, allowing users to work with familiar tools and open-source libraries.
    • Yes. Workbench combines cloud-based infrastructure with distributed compute capabilities, enabling users to analyse large volumes of historical market data and execute workloads at scale.
    • Workbench supports a broad range of workflows, including quantitative research, market microstructure analysis, historical market replay, strategy development, execution analysis, transaction cost analysis (TCA), data exploration and visualisation.
    • Workbench is designed for quantitative researchers, data scientists, analysts and developers who need to analyse large-scale historical market data, build models and applications, and collaborate in a secure cloud environment.
    • No problem. Workbench includes intuitive, point-and-click tools for querying data, creating visualisations and exploring datasets without writing code. For more advanced analysis, users can also work with Python, R, SQL and APIs within the same environment.
    • Start with one of Workbench's Springboards, pre-built starting points that guide users through common tasks such as querying data, creating visualisations and launching development tools.

Related solutions

Find out more about related LSEG solutions

Tick History – PCAP

Lossless historical packet capture data – captured directly at the source, with GPS-synchronised, nanosecond precision timestamps for the highest levels of fidelity.

Tick History

With over 30 years of historical tick data, our archive offers unmatched depth and breadth. Cleaned, structured and normalised, our high-quality data supports fast, consistent analysis – helping you uncover patterns, inform trading strategies, and act with confidence.

Real-Time – Ultra Direct

Unlock direct access to exchange-native feeds with our ultra-low-latency software feed handler library – delivering single-digit microsecond processing.

Real-Time – Direct

Achieve speed, scale, and consistency with our full-depth, exchange-sourced low latency market data feed – fully managed with flexible deployment options and seamless integration.

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