Data Platform Implementation: A Sample Timeline from Kickoff to Go-Live
July 14, 2025
Read Time: 3 minutes
Authors: Sourabh Dhawan
Operations & Growth
Inst'l Asset Managers
Authored By
Sourabh Dhawan
With over 16 years of experience at the intersection of finance and technology, Sourabh has held senior engineering and client-facing roles across some of the industry's most sophisticated platforms. At D. E. Shaw, he spent six years developing and managing middle- and back-office systems, rising to lead engineering teams responsible for operational scale and reliability. For the past decade at Arcesium, Sourabh has served as a Forward Deployed Solution Architect and previously as a Technical Relationship Manager, guiding clients through complex implementations and designing tailored solutions across the investment lifecycle.
The successful implementation of a new data platform requires careful preparation, precise execution, and a clear understanding of the steps involved. By understanding what to expect at each stage, you can better navigate the implementation process and achieve your desired outcome.
The duration of an implementation can vary widely depending on your needs and the size of the data transformation project. Most system integrations take a waterfall approach to implementation, but data platform transformations are much better suited for a sprint-based approach. Although the configuration, reporting, and testing stages of an implementation might look like a waterfall from a distance, those stages are broken into smaller sprints to deliver incremental value quickly to our clients.
Sprint Delivery Approach
Arcesium employs an iterative sprint delivery model for the Aquata® data platform, designed to accelerate time to value, ensure high-quality outcomes, and support continuous improvement. The process follows a structured, repeatable cadence across three key stages:
1.Sprint planning: Arcesium collaborates to jointly define clear sprint objectives and finalize scope. Key deliverables include detailed data mapping and alignment on priorities.
2.Sprint execution: Arcesium will develop and configure the agreed-upon functionality within the sprint window, adhering to best practices for quality and traceability.
3.Sprint review: Arcesium will conduct testing and present the completed item to you for validation, with time allotted to incorporate your feedback. Deliverables typically include release notes and a live platform demonstration.
Each sprint is time-boxed and iterative, with planning for the subsequent sprint initiated in parallel with execution. This model allows for agility in delivery, flexibility in scope refinement, and a continuous feedback loop to adapt to evolving business needs.
Implementation Stages
Once contracts are signed, your data platform transformation can begin. The following implementation timeline outlines the key milestones and activities that will guide your project from initiation to completion.
Initiation
The implementation journey starts with the initiation stage, which includes critical steps such as contracting with third-party vendors, setting up the environment, and gathering requirements through deep-dive sessions.
Contracting: Execute Arcesium contracts to kick off the implementation; ensure to finalize commercial agreements with third-party vendors by the second or third week.
Environment setup: The implementation team will create a custom pod, including user credentialing and a dedicated Amazon Web Services (AWS) instance.
Requirements gathering: Conduct deep-dive sessions to discuss key functionality and gather inputs to solidify requirements. Topics may include technical integrations, data vendor integration by asset class, reference data overview, and user permissions and authentication.
Integrate & Configure
During this stage, Arcesium creates the fundamental infrastructure for data and reporting. This includes connecting inbound data, setting up APIs and reporting, data mapping, data egress configurations, and data analytics.
Inbound data connectivity: Implementation of secure, scalable connectors to facilitate data onboarding from a range of upstream systems.
APIs and reporting: Provision API libraries for use across supported languages, deliver training, and configure report managers to optimize report generation and access.
Data mapping: Employ the ingress manager to standardize and transform incoming data into Arcesium normalized data models.
Data egress: Configure outbound data pipelines to facilitate export to external systems or third-party tools.
Data analytics: Create visualization dashboards and analytics tools to enable data-driven decisions.
Data Load & Parallel
This stage focuses on validating data flows in a live environment, onboarding users, and ensuring data integrity through rigorous parallel testing and managed support.
Live connectivity testing: Execute internal testing using production data across internal systems, market data providers, and third-party integrations.
User training: Offer specialized training by Arcesium professionals and platform experts that are familiar with the implementation to boost user proficiency.
Parallel testing: Client parallel testing enables users to engage with the Arcesium platform in real time, compare results across systems, and confirm internal and external data accuracy.
Sample Implementation Timeline
To learn more about how Arcesium can help modernize your data platform and accelerate your time-to-value, please reach out to our team.
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