Demystifying the Path to a Modern Data Platform

February 8, 2024
Read Time: 7 minutes
Unified Data

Building a clear strategy to evaluate and modernize your technical ecosystem

Legacy systems can be a heavy burden on investment firms, hindering their ability to adeptly shift strategies during periods of changing market dynamics. Investing in critical systems and core applications prepares firms to leverage advanced technologies – a rapidly accelerating component necessary to meet stakeholder expectations.

Dated — and dare we say obsolete — financial systems are closely correlated with operational inefficiencies, security vulnerabilities, and limited compatibility. The limitations can impede scalability or even result in missed opportunities. What’s more, complex internal structures and rigid workflows can restrain an organization from embracing emerging technologies, such as real-time data analytics and artificial intelligence.

As firms consider their future, it’s all about embracing digital opportunities. Investment firms looking to create and launch new products, support more diverse complex asset classes, and accommodate evolving reporting demands are turning to cloud-based, scalable data management solutions.

What to consider as you assess your current platform

Evaluating your firm’s business trajectory over the next 5 to 10 years can help determine if your current operating model and infrastructure can deliver on longer-term goals. Several signs can point to when your firm might be ready to modernize.

We recommend that you first look at system vulnerabilities. The fragility when new patches are no longer released for dated systems, updates cannot be applied, or the vendor no longer supports a certain software can compromise databases and applications. Similarly, disjointed applications using outdated technology stacks heighten your infrastructure’s complexity. If you find your firm is upgrading cycles every couple years, it’s a sign to look at how you can modernize the platform.

You may also find that dated systems begin to lag in performance, causing increased resource consumption and higher system failure rates. In addition, dated systems may struggle to connect with more modern applications, external systems, data vendors, and third parties. A patchwork of disparate systems, data models, and sources can add to the magnitude of managing data. Integrating data and establishing connectivity with external providers is paramount for operations, growth, and competitiveness.

Why timing and preparation matters

While the benefits of digitization are well-established, you will need to assess if timing aligns with business priorities. Researching solutions, budgeting, and planning will let you evaluate your current ecosystem and create a smooth pathway for your firm’s eventual migration.

Data is imperative to meeting operational, investor, and regulatory obligations. Prioritizing your data strategy shifts the agenda towards unified, automated, and optimized data accessibility.

What are the benefits of a modern data platform?

  • Cloud-native integration and tools
  • Flexibly integrate data with modern, scalable, and agile technology, advanced functionality, and intuitive interfaces 
  • Unified and accessible data
  • Connect data from disparate sources and enable a synchronized source of truth 
  • Expansive data storage
  • House vast volumes of data with an open, scalable data lake or warehouse 
  • Stronger data management and governance
  • Strengthen and support changing regulatory obligations with validated, accurate data to comply with Form PF, T+1 settlements, SFDR, and multiple other reporting requirements
  • Robust data security and integrity
  • Protect sensitive financial data, client assets, and confidential information with industry-standard cybersecurity frameworks
  • Optimized performance and efficiency
  • Advance automation capabilities, streamline workflows, and integrate processes 
  • Extensive scalability
  • Support business growth and handle data processing requirements to enter new markets and accelerate time to market 
  • Advanced analytics
  • Gain accurate and granular insights into investment performance with detailed analyses of portfolio returns, performance attribution, risk calculations, and complex financial modeling

RELATED READING: A Data-First Approach to Data Governance

So you’re ready to commit to modernization

Did you know that an estimated 80% of technology budgets are devoted to simply ‘keeping the lights on’ and maintaining, repairing, and updating old technology systems.[1] The remainder that’s allocated to modernization is insufficient for firms looking at new tech and expanding integration.

Yet, avoiding disentanglement from legacy infrastructure can affect your firm’s ability to optimize workflows, unify data, remove silos, and ultimately scale and grow.

All too often, organizations rely on multiple disconnected server-based or on-premise systems to support trade confirmation, settlement, reconciliation, and accounting. The risks vary from manual requirements, disparate processes that lead to errors and data inaccuracy, limitations in supporting complex instruments, and failure to integrate with other platforms.

Investment firms prioritizing digital transformation will accelerate their ability to swiftly create and launch new products, support more novel, complex asset classes, and accommodate increased volumes required from their reporting systems.

IN CASE YOU MISSED IT: Arcesium Launches AquataTM

Start with a phased approach

A phased approach can make the migration more manageable as you seek to optimize systems, storage, and processes. Consider the following practices for system and data migration and implementation:

Phase 1: Initiate

After you transition from signed contracts to migration planning, your selected vendor will set up a dedicated instance in the cloud and hold requirements-gathering discussions to learn about your data sources and create an inventory of your systems.

Phase 2: Integrate and configure

Once the environment is available, your vendor will establish data connectivity and integrations to ingress data, map incoming datasets, and establish egress configurations for outbound data. This phase will include data visualizations for analysis and representation and rules to ensure the platform stores only clean, accurate, and validated data.

Phase 3: Load data and run parallel testing

After your vendor establishes data connectivity, data will flow from your designated sources and then be transformed and captured within the data platform. Training will empower your teams to use the platform’s interface and understand the workflows pertinent to their role. One month before go-live, parallel testing will begin running in the cloud environment.

Ready to migrate? The execution essentials

During implementation and migration, a strong project plan and project governance is imperative:

  • Build a detailed strategy
  • Create a clear roadmap outlining steps, tasks, key dependencies, and timelines 
  • Siphon scope creep
  • Restrict changes to stay on track with budget, timelines, and deliverable quality
  • Swiftly address data quality issues
  • Partner with a data platform provider experienced in multiple file formats
  • Manage differences in data structure, modeling, and formats
  • Ensure your data platform provider has the expertise to handle data structuring

YOU MAY ALSO ENJOY: Leaving Legacy Management Platforms Behind

Plan for a successful platform migration

Consider Arcesium’s checklist as you’re building your migration plan:

  • Outline your migration sequence, timelines, resource allocation, and potential risks
  • Prioritize applications based on criticality, complexity, and potential business impact
  • Consider a phased approach starting with low-risk or non-critical systems
  • Discuss and align on the scope and procedures for changes
  • Anticipate risks and have a plan of action in place
  • Keep an open mind and agile approach
  • Maintain positive vendor relationships for smooth resolutions
  • Map out a data migration strategy to avoid data loss, formatting challenges, and data quality issues

It’s go time

Once you’ve mapped out your migration strategy and successfully implemented a phased approach with your trusted partner, moving from parallel to production should be seamless. In the parallel phase, your vendor will run the new system, applications, and processes in a business-as-usual manner. At this stage, you’ll also work with your partner to resolve any issues before your organization is officially ‘live’ on the new system.

To ensure a positive go-live, aligning with your cloud-based data platform vendor on a criteria list focusing on business-as-usual activities is good practice.

Determining milestones and dependencies for go-live helps to align project participants. Ensuring a smooth transition from your vendor’s project team to your ongoing relationship management team, especially in the early stages, offers the reassurance that you have a reliable partner by your side.

Best practices for migrating your data platform

We’ve assembled our practices based on the successful migration of multiple clients over the last several years at Arcesium.

A common theme we’ve found is that institutions prepared to undergo digital transformation are strategically positioned to support new investment products, meet rising customer demands, and deliver scalable, superior customer experiences. To enhance efficiency and foster growth, hedge funds must transition beyond defensively managing technology debt. Firms willing to embrace a mindset focused on building technical wealth open the door to greater opportunities for advancement.

For a comprehensive perspective on migrating your systems, read Arcesium’s Best Practice Guide: Migration to Modern Technology Platforms.


[1] Tech debt: The vicious cycle of legacy tech in asset management, AIMA, September 20, 2021

Dmitry (Mitya) Miller
Dmitry (Mitya) MillerSenior Vice President, General Manager, Aquata™

Dmitry (Mitya) Miller is a Senior Vice President and General Manager of Aquata, Arcesium’s comprehensive self-service data platform purpose built for the investment management industry. Mitya is responsible for overseeing all aspects of the Aquata business, including P&L ownership, customer base growth, customer delivery and engagement, and product roadmap.

Previously, Mitya was the head of Arcesium’s Technical Relationship Management and Forward Deployed Teams where he led global teams of solution architects, software engineers, project managers, and data specialists delivering solutions to our clients’ most complex business and technology challenges.

Mitya has over 20 years of experience building software platforms for portfolio management, valuation, security and reference data mastering, and enterprise data management. In addition, he is an expert in investment management technology, cloud architecture, and the data landscape in asset management.

Education & Credentials

  • Master’s Degree in Computer Science, Saint Petersburg State University

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