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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
A Modern Approach to Asset Management: Integrating Simcorp
Dimensions with Cloud Data Platforms
Venkat Sunil Kumar Indurthy
Software Developer, Compunnel Software Group Inc, USA
DOI: https://doi.org/10.51583/IJLTEMAS.2026.15020000118
Received: 23 February 2026; Accepted: 28 February 2026; Published: 21 March 2026
ABSTRACT
This paper will describe the way in which UNIFY has successfully integrated multiple technologies, including
SimCorp Dimensions, Informatica PowerCenter ETL, Snowflake Cloud-based Data Warehouse, as well as IDL's
Data Hub orchestration (or ETL), in order to convert a disparate and fragmented Asset Management platform
into a truly cloud-native architecture. Through the use of Phased ETL Strategies and Agile/Scrum governance,
UNIFY addresses many of the common challenges associated with legacy systems, including Fragile
Integrations, Insufficient Data Sources, and High Maintenance Costs. Additionally, the UNIFY design has
standardised data flows, provided for Very High Availability and enabled Seamless Migrations. Performance
Studies conducted by the UNIFY development team indicate a marked improvement in overall efficiency,
including Significant reductions in Query Costs and Increased Cache Hits; additionally, UNIFY has identified
optimization opportunities using its Cost Dashboard. Future efforts will focus on the adoption of advanced
technology, including GraphQL Federation, Real-Time Streaming, and AI-Driven Operations, as well as
additional opportunities to improve scalability and reduce costs. Overall, the design created by UNIFY
establishes a New Industry Standard for IT Transitioning of Asset Management platforms, while ensuring
Compliance with Regulatory Requirements and Eliminating Legacy Silos.
Keywords: Informatica PowerCenter ETL, Snowflake Cloud-based Data Warehouse, Seamless Migrations,
GraphQL Federation, Real-Time Streaming, AI-Driven Operations
INTRODUCTION
Asset management within the financial industry entails managing and growing an individual's or a corporation's
financial assets in a methodical manner to achieve maximum value and return on investment and at the same
time minimize the risks associated with those assets. The process of asset management consists of researching,
acquiring, monitoring, evaluating, managing, and allocating resources, both physical and non-physical, related
to the different asset classes, including IT assets, in the interest of maximizing operational efficiencies. Asset
management offers several advantages, which include the ability to develop diversified portfolios that optimize
returns while minimizing risks; the reduced variability of asset values resulting from professional-level risk
management; and the ability to stimulate innovation by helping companies identify and invest in profitable
projects/technologies with available capital. Nevertheless, there are some disadvantages to asset management,
including higher fees attributable to the use of specialized services; the potential for poor performance due to
poor management decisions or loss of traction due to an unexpected (and unmitigated) change in the market
environment; and significant costs associated with meeting complex regulatory compliance requirements,, which
result in increased operational costs.
The UNIFY (Universalized Framework for Improving Financial Services, Inc.) programme has been created to
address some of the major challenges associated with asset management as a result of excessive redundancies
that have been created within asset-management organizations by using unreliable and outdated databases.
UNIFY has implemented streamlined oversight of each asset class, using shared databases and a unified portfolio
accounting application solution. This eliminates cost, redundancy, and inefficiency, which enables the true
essence of asset management's objectives to be achieved: risk-mitigating frameworks, standardization of
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financial products and services, and maximization of value within the context of the investor's individual needs.
By creating this transformation, UNIFY has taken into account the fragmentation of the asset management
industry in the past and its potential for further improvement and innovation by providing a scalable and low-
risk financial asset management environment [1].
Finally, Asset management firms in the finance industry provide a high level of management over financial
assets through the collaboration of professional resources to assist clients in building their portfolios. Asset
managers provide clients with access to expert knowledge and investment expertise, which enables them to make
practical decisions and create comprehensive investment strategies.Diversifying investments across asset classes
allows firms to create large portfolios with much lower levels of risk than individual investors would have access
to. In addition, firms can leverage economies of scale to negotiate lower fees and provide unique investment
opportunities. To further promote increased transparency, firms must comply with regulatory requirements and
report on their performance on a regular basis. Finally, firms save time by managing administrative
responsibilities (e.g., portfolio rebalancing, etc.) from a centralized location rather than from each individual
client. Firms use data-driven decision-making processes and adhere to fiduciary standards to help mitigate losses,
identify trends, and protect against undue risks.
The UNIFY initiative is designed to support all of these benefits of professional management by standardizing
data and establishing advanced systems that address prior inefficiencies and poor operational performance in the
area of asset management. UNIFY also provides a comprehensive IT overhaul of your investment management
systems and infrastructure (e.g., all client portfolios) to support the oversight of significant financial assets. The
current state of the investment management industry (i.e., the fragmented IT environment of a large asset
management firm with multiple clients worldwide) is characterized by a lack of integration between many
different platforms for managing various aspects of the investment process. Platforms include trading, portfolio
accounting, performance management, and reporting to clientsand therefore contribute to information
duplication, producing mismatched and erroneous data that subsequently hinder reconciliation efforts.
Analysts experience extended periods of time and significant expenses in verifying their own clients’ reports
because they have to access and navigate through several different platforms to retrieve the same trade execution
data (and reports). Additionally, maintaining the multiple platforms is expensive because of the need for a high
level of specialized technical support and multi-layer complexity in collaborating to maintain and update the
Unify project is intended to provide one comprehensive integrated platform to improve the quality of the data,
standardize the data usage, and reduce the operational risks by consolidating multiple fundamental data
processing functions using the new platforms Simcorp Dimensions and AIM-GAIN. Through this process, we
will be able to enhance client reporting and allow for real-time decisions, while at the same time providing
stability to the company from a cost, time, and technology management perspective due to the ability to easily
adjust to the ever-changing pace of the financial marketplace [3].
The duplication of functions from legacy systems creates the potential for the same tasks to be performed
multiple times, thereby increasing the time and money spent on maintaining these applications by a substantial
amount. Duplicate programs can require teams with specialized training to manage them, thereby increasing the
number of resources required and therefore increasing the cost of ownership and management of these
applications and the number of people in the organization with skills in these legacy programs is diminishing
rapidly.
In addition to this issue of duplication of effort, inconsistent sources of client data can result in duplicate client
records and transactions being stored, leading to significant issues with retrieving accurate data, generating
reports, and complying with regulatory requirements. The limitations of the centralization of client records and
transactions reduce the ease of updating client records and increase the security risks associated with outdated
information. Point-to-point integration creates a fragmented architecture, which makes it difficult to modify and
expand an integrated environment. Due to the nature of today's integrated IT environment, a lack of
standardization will produce inconsistencies in the data and limit the potential for innovation while
simultaneously increasing the costs to maintain compliance [4].
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The integration of the IT platform relies on the use of both the GIM2 (Gensys Integrated Middleware) and the
Integrated Distribution Layer (IDL) in order to facilitate a greater degree of consistency and throughput of data
across all applications. The IDL helps resolve the long-standing problem of dispersed data storage by offering a
single repository to store, convert and send data to all downstream systems.The integration layer aggregates data
from several different sources while applying business rules for integrity and consistency before distributing the
harmonized data to dependent applications. This centralization addresses issues associated with inconsistent or
duplicate data, which is necessary to accurately account portfolios, comply with reporting requirements, and
provide operational decision-making support.
The integration layer reduces the complexity of point-to-point integrations; therefore, simplifying the system
architecture and increasing the maintainability of these integrations. By providing the means to reuse integration
components and standardizing data formatting, the integration layer enables improved transition success as
platforms evolve and systems are onboarded. The integrated solution also aligns with enterprise architectural
practices for scalability, reliability, and agility of IT ecosystems. Ultimately, the goal of UNIFY is to develop an
integrated, cost-effective, and reliable asset management platform utilizing GIM2 and the integration layer to
provide a coordinated and consistent data transition to new portfolio accounting systems such as Simcorp
Dimensions.
The UNIFY program's transition strategy will gradually move to modern portfolio accounting systems that
consolidate old legacy systems into one integrated solution while maintaining continued data access during
transition, and to achieve the maximum level of data continuity and minimize disruption to the business,
integration solutions such as the integration layer will be utilized. A strategy of centralizing front-to-back
functions through automation will enhance the speed of execution and accuracy of processing and reporting
across asset classes.
As redundant systems are retired, organizations will be able to gain real-time insight during this transitional
period; at the same time, these organizations' operational silos will be reduced and will continue to be in
compliance with regulatory requirements. The initiative will consist of three main applications: 1) Simcorp
Dimensions, a fully integrated multi-asset portfolio and compliance platform; 2) Simcorp IMW, a workflow tool
to improve efficiency of operations through automation; 3) AIM-GAIN, a custom-built application to minimize
human error in the management of corporate actions, thus providing high processing efficiency. Integrating
strong integration components is critical for the success of the UNIFY program by eliminating historical
fragmentation and developing a single-integrated data and information-sharing platform for the updated Asset
Management IT platform, thereby minimizing data downtime and inconsistency and providing scalable
capabilities for asset processing by using the integration layer as a data hub.
In addition, the UNIFY program must implement a carefully planned transition to the target architecture through
a phased decommissioning of the current state, implementation of Simcorp Dimensions, Simcorp IMW, and
AIM-GAIN will be essential to maintain the continuity of operations and data integrity. Proper transition
planning will mitigate disruption to the business in this rapidly changing environment and accelerate the ability
to obtain cost savings, increased performance monitoring and responsiveness, providing a foundational platform
for future sustainable growth to address the challenges facing legacy business operations.
Related Work
Using UNIFY as a guideline, the UNIFY program focuses on providing asset management organizations some
guidance on incorporating integration/consolidation practices to assist in resolving many of the difficulties
associated with updating fragmented asset management systems. Numerous research papers and industry
publications are in agreement with the premise of combining systems that have been previously disparate to
create Unified Managed Accounts (UMA) to enable them to simplify their investment structure through taxation
efficiency and risk alignment through the streamlining of their investment structures. Many case studies are
available on family offices' platforms, and these demonstrate that in terms of standards like IDL for data
harmonization, it is necessary to collect identical or uniform data for compliance and reporting. Additionally,
academic resources that provide insight into challenges related to technology transformation and the legacy
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systems that continue to be used by a significant percentage of asset management organizations indicate that a
unified or coordinated approach to managing these transitions can limit complexity and risks associated with
using legacy systems.
Experts are also advocating for the development of standard application programming interfaces (APIs) and data
centers as part of an organization's overall integration strategy, which would facilitate improved scalability, as
well as an operationally agile solution to managing the assets of its clients and providing consistent data across
the various asset managers in the asset management space. Current analytical tools and dashboards allow for
quicker and easier adjustment to ultra-rapid response requirements for dynamic industries such as Banking, I.T.,
etc., through enhanced analytics and API driven solutions [8]. Studies conducted on legacy IT environments
show many organizations struggling with issues caused by their outdated system, resulting in Functional
Redundancies, high levels of Maintenance Costs (70% to 80% of operating budgets spent), and a web of disparate
systems ("Patchwork System"). Consolidation of these legacy systems will allow for reduced overheads and the
removal of information silos.
The use of a centralised hub, similar to the Statistics Canada industrial data library (IDL), is also encouraged to
gather, store, transform, and distribute large amounts of data. Legacy applications often create problems in terms
of compliance and data duplication when different employees perform their jobs with the same dataset but in
different locations or from different sources. To assist clients during these transitions, the use of Data Hubs like
Technology One Enterprise Asset Management (EAM) or Unify Software instead of point-to-point interfaces
are recommended. Clients that have a coordinated approach to their technology transitions will be able to
successfully phase out legacy applications through the use of staggered rollouts of systems such as those
provided by Simcorp Dimensions, Incentive Management Works (IMW), and AIM-GAIN. Rewards achieved
through these coordinated migrations include improved throughput and better dashboard reporting with the
emphasis on “Integration” and “Rigor” in order to realize cost savings and increased flexibility [9].
The benefits of consolidating IT platforms include improved Architectural Management, quicker Deployment
of Applications, and greater Cost Savings (i.e., in excess of 70%-80% of IT budgets). Progressive companies
can realize much higher success from the Digital Transformation process because of enhanced levels of Security,
increased Business Agility, and increased Data Visibility available to them. In addition to these advantages lie
other positive outcomes, such as increased Employee Productivity, Innovativeness, the ability to develop
Scalable systems, and thereby allowing companies in Asset Heavy Industries, such as Banking.
Consolidation can lead to many possibilities and risks such as vendor lock-in and migration complexities leading
to downtime and performance issues like integration latency. The risk of failure is also greater when there is a
loss of customization, when there are compatibility gaps between new and legacy systems, and with an increased
reliance on single-source suppliers. After the merger, companies will face many challenges regarding scalability
due to duplication of platforms, and careful planning will be required to avoid operational disruption during the
transition. The goal of the UNIFY Programme is to mitigate risk related to migration through coordinated
transitions, as well as reduce redundancy costs using IDL's data hubs and applications such as Simcorp
Dimensions. It will also demonstrate that phased integration is essential to maintain agility and enable a seamless
decommissioning process. Proactive strategies such as UNIFY, focusing on flexibility and standardization, can
greatly mitigate risks related to vendor lock-in. Multi-cloud or multi-vendor solutions will allow organizations
to distribute workloads across multiple vendors, increase service quality and improve negotiating power when
negotiating contracts with vendors, creating a competitive advantage. Using open source software, open
standards and APIs also improves interoperability and enables easier transitions between platforms without being
locked into a proprietary platform.
Containerizing applications allows for reduced friction between platforms, ensuring that applications can be
executed consistently across different infrastructures. It is critical to include provisions for short-term returns,
portability of data, transition support and scalability without penalty in negotiated contracts and service level
agreements. Regular data governance procedures, such as migration testing and testing of backups, are necessary
to maintain control over data and continue to have access to data in a format that can be standardized. When
selecting vendors, organizations should perform due diligence to evaluate vendors' solutions based on hardware
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agnosticism, interoperability, innovations, pricing, and exit support. The strategies outlined above are consistent
with the UNIFY programme's strategy to replace legacy systems such as Simcorp Dimensions, IMW and AIM-
GAIN through coordinated integration in order to eliminate vendor lock-in and facilitate a timely and affordable
transition from legacy systems to modernized systems by leveraging IDL's standardized data hubs and open
integration protocols. In addition to the above, the integration of AI, the migration of post-merger systems and
the use of risk management in replacing traditional portfolio accounting systems and replacing the antiquated
with the new is widely discussed in many academic and business publications.
The transition to AI enables the automation of data aggregation and reconciliation processes, thereby eliminating
discrepancies in data. AI will also provide organizations the ability to use predictive analytics in real time and
to enhance their reports on performance and NAV. The focus of post-merger integration is on restructuring to
maintain historical integrity among securities and asset classes. However, post-merger integration can result in
a loss of the former performance data associated with asset classes and securities prior to the merger. In addition,
while in-house systems typically produce better results in terms of the security and reliability when utilizing
vendor solutions; in-house systems also have a tendency to be error-prone due to the scarcity of talent needed to
operate and manage these systems. These advantages of modernized systems through the integration of machine
learning enable organizations to achieve greater efficiency and ultimately achieve folios that are better suited for
the predicted growth of data, while preserving historical performance data during the transitional period. The
above findings are consistent with the UNIFY programme's efforts to implement Simcorp Dimensions, IMW
and AIM-GAIN, to effectively address the legacy systems and their challenges through coordinated integration
[12].
System Architecture
An asset management platform designed for today is cloud-based and will allow for scalable integration of
multiple data sources into one 'hub' by employing technology and process standards such as ETL, cloud data
warehousing, and enterprise scheduling to enable comprehensive analytical capabilities, as illustrated below.
This is accomplished by integrating multiple external Data Sources into one singular database, using ETL
Pipelines built using industry-leading ETL Solution Providers, then consolidating that data into Snowflake and
automating the Scheduling Process with Autosys for analytics & reporting using Simcorp Dimensions. The
architecture will pull Data from multiple Database Providers such as Teradata or Oracle and allow for consistent,
accurate Data through the use of industry-leading ETL Providers.
In addition, using Snowflake as the Central Data Warehouse in a Cloud-based environment and Autosys to
automate scheduling processes allows for the timely processing of Data into Simcorp Dimensions, resulting in
a greater ability to manage portfolios efficiently. The primary application in our architecture is Simcorp
Dimensions, which is designed to manage portfolios and incorporate standard APIs that help improve the
efficiency of Asset Management Processes in addition to other applications that support asset management
operations. Furthermore, a Data Hub will enable users easy access to Data and enable easy Data Integration
between Applications, while ongoing Collaboration with Business Teams ensures that ongoing updates will
enable Business Teams to maintain a close relationship to the Technical Development of the Application.
Maintaining Data Pipeline Integrity through Proactive Problem-Solving and Comprehensive Documentation will
facilitate the onboarding process of Customers and with the Global Delivery Model that uses Agile/Scrum
methodology for Efficient Delivery and Customer Engagement, we can assure that the delivery of Technology
will be aligned with Corporate Goals, resulting in Industry Recognition for Innovative Portfolio Operations due
to the advantages cloud technology and features deliver, such as Data Availability and Scalability.
The design of our architecture utilizes Snowflake as the Central Data Hub and comprises a combination of
Informatica PowerCenter to perform Data Transformations and Autosys to automate Orchestration of data into
the Data Hub. The resulting solution will be a Cloud-Native ETL and Data Warehousing Solution that is
Integrated with Simcorp Dimensions to perform Portfolio Accounting, thus enabling Asset Management
Operations to be performed efficiently as shown in the Following Figure 1.
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Figure 1: Architecture for Simcorp Dimensions Data Integration Platform
ETL Layer & Data Ingestion:
ETL layer uses Informatica PowerCenter for cleaning and validating all source data from
Teradata, Oracle, Informix, Sybase and Flat Files.
DIS Team will connect Unix (Operating System) to Databases by having the necessary
Environment Setup to Connect to all databases as well as how PowerCenter transforms the data
and handles errors in the ETL process.
WFE is an Automated Scheduled Process for a Workflow using Autosys JIL Scripts
Data Management & Storage:
Snowflake Data Warehouse provides the capabilities of Scalable Storage, Multi-Currency
Support and Optimized Queries for Simcorp Dimensions through the use of Data from Snowflake.
Custom Schema for the Different Classes of Assets within Snowflake have been developed, as
well as maintenance of all Reconciliation Reference Data
Application Layer / Integration Layer:
Simcorp Dimensions uses Snowflake Data for Accounting, Risk Analytic and Reporting
Functions via a Batch Feed and an API Interface for the system.
The Simcorp IMW (Integrated Management Workbench) Module an Automated suite for
processing; and their AIM-GAIN Module for monitoring Corporate Activities.
The IDL Data Hub reduces SimCorp’s dependency on Snowflake (i.e. the IDL Data Hub can
replicate Snowflake's Data functions).
Operations Layer / Governance Layer:
Monitoring involves Snowflake query tracking, as well as Informatica Workflow log analysis for
Issue Resolution; Decision Support to help connect Business Requirements with Technology.
Agile Delivery Process will be managed via Scrum ceremonies that facilitate Collaboration
between Teams.
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Stakeholder Management will be aligned through working with Clients on aligning UBS
Solutions.
In order to migrate SimCorp Dimensions with minimal downtime and Historical Data accuracy, implement a
Phased Hybrid Migration Strategy consisting of a Big Bang Cutover of all Non-Critical Data followed by
Incremental (Phased) Cutover(s) for all Critical Portfolio Related Data.There will be 4 phases during migration.
For the first phase, there will be a 2-week period to load a basis reference file. For the second phase, over the
next 4 weeks, there will be a delta load of historical transactions dating back 12-24 months. For the third phase,
over another 4-week period, there will be a step-by-step reconciliation with previous system(s) in real-time. The
Cutover will occur in one weekend. The architecture for the ETL Pipeline has several Source Systems (i.e.
Oracle, Informix, Sybase, Teradata, etc.) and Flat Files that will be used as sources for the Informatica
PowerCenter layer; these systems feed into the Informatica PowerCenter ETL Layer. The Snowflake Core Zone
is where data transformation occurs; the Raw Zone is where the data is staged prior to being made available in
the SimCorp Dimensions Feed. The primary mappings of the ETL Process will accommodate extraction from
the Source backup, data cleansing, and the standardisation of currency and Instrument Codes.
Data Quality and Reconciliation are essential; there will be checks for Row Counts, NAV Reconciliation and,
Referential Integrity. During migration, key considerations regarding SimCorp Dimensions include the
following: Data Model Alignment, Multi-Currency Synchronisation of NAVs, and Batch/API integration. Risk
reduction strategies will include rollback plans in the event of data loss, as well as data discrepancies, with
specific triggers for a rollback action. Validation and Go-Live Checklists will verify that all Reference Data,
Historical NAVs have been transferred successfully, and User Acceptance has taken place. The Migrations will
follow overall Informatica - Snowflake Principles to ensure there will be 0% Data Loss, Minimal Downtime and
Full Traceability throughout the Deployment of SimCorp Dimensions.
The Implementation of SimCorp Dimensions is broken into sequential steps. This process will include data
migration, ETL design, implementation, testing, governance and post-go-live operational support. An important
aspect during the entire project is to have clearly defined Data Management Governance surrounding a RACI
matrix for data management definition, data quality, and auditor compliance through audit trails and data
purification processes. To ensure a successful implementation, it is pivotal to have a strong testing strategy
developed with multiple phases, where each phase entails; information mapping, integration testing, user
acceptance with historical reference data, comparative analysis of the legacy NAV and stress testing for peak
conditions.
The Execution Phase consists of having a very detailed go-live runbook with a checklist, having dual-write
validation during cutover weekend, and supporting Hypercare for the next few weeks after the go-live of
SimCorp Dimensions. Post-migration, there is a focus on optimizing the performance of Snowflake’s Queries
and validating the batch settings and refining data loading options after migration. Also in the Operations phase,
we continue to monitor Data Quality through Dashboard Monitoring, Breach Alerts within the capacity planning
for Snowflake. The priority of Tasks should focus on immediate tasks including Testing Methodology, Go-live
Preparations, and medium and low priority tasks relating to Cost Optimization, Performance Tuning, and
Advanced Analytics after Hypercare.
The Testing Strategy is critical in ensuring a smooth transition from Legacy to SimCorp and relies heavily on
the use of Actual Data Migration verified through User Acceptance Testing (UAT) prior to cutover. Additionally,
The Document strongly supports the use of Agile/Scrum methodologies in managing complex data migration
projects and specifically mentions using this approach during a SimCorp Migrations. The primary benefits of
the agile/scrum methodologies are predictability of your delivery through direct stakeholder alignment and
iterative validation throughout the project timeframe.It outlines a thorough approach to project planning with
processes such as JAD sessions for converting legacy data into a new system, as well as a 12-week plan for the
multiple phases of migration (Foundation, Historical Migration, Parallel Run/Cutover) on what and who needs
to be done first (data modeling) with trained experts and how operational efficiencies can be achieved through
daily standup meetings. In addition, it describes how sprint ceremonies (review/retrospective) are structured for
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the various multiple migration phases (Foundation, Historical Migration, Parallel Run/Cutover) with the goal of
having all ETL jobs validated 100% as well as tracking the SLA (Service Level Agreement) for each ETL job.
The techniques used to identify the project’s requirements (workshops, prototypes, etc.) are key to improving
the data model’s accuracy and enhancing the visibility of project stakeholders throughout the entire system
implementation process. A proactive risk management strategy is supported by established project readiness
(Definition of Ready) and Definition of Done) criteria, along with an impediment backlog to resolve any
adversely impacting performance issues. The safety net rollback strategy allows for each sprint to create value;
the parallel run serves as a final validation method prior to cutover.
The document also states that there are metrics to determine the impact of defects and budget variances due to
using Agile leadership to convert data migrations from high-risk, big bang events into manageable, incremental
steps, which have historically reduced timelines by 30-50% in past projects. By linking various Agile artifacts,
ceremonies, roles, and technologies systematically to the various phases of the migration and the key
deliverables, we will be able to better understand how the implementation of Agile/Scrum management will
influence the success of the SimCorp Dimensions migration project.An extensive implementation plan utilizing
Scrum and Agile methodologies for Migration.
The scopes of the prioritization of the product backlog are comprehensive Epic requirements of migration of
Reference Data, Loading Historic Positions and Transactions, Consolidation and Parallel Runs, and the
Execution of Go-Live and Cutover. The User Stories for each Epic contain specific Tasks and Acceptance
Criteria to ensure successful delivery of results associated with those Epics. The Sprint capacity/team makes
evaluation of its workload and provides Story Points with assigned Complexity to determine the Sprint capacity
based on each task. The initial Sprints focus on Prototypes and Profiling Data. The final Sprints, focus on User
Acceptance Testing and Performance Testing of the System.
Daily Standups allow for assessments of ETL Task updates, and Sprint Reviews present preliminary results and
demonstrations to stakeholders. Retrospectives review the issues with Data, with the intent to develop further
tools to improve the Data. Backlog Refinement Sessions allow for the modification of User Stories based upon
newly found Data Anomalies or changes in the Business Processes. The key roles are identified as Product
Owner, who is responsible for prioritizing Migration Requirements, Scrum Master, managing Agile Processes,
and Development Team, who is responsible for technical aspects of Migration. Business Analysts assure the
Data is accurate, and they provide oversight of the Cutover logistics.
Risk Management is included in Agile Artifacts, including Testing of Edge Scenarios and additional Research
on API integrations. The Definition of Done includes Automation Testing Pass Rate, and Stakeholder Approval,
and an Impediments Backlog provides a central location for documenting items that impede Data Availability.
The Technical Integration Strategy will link Informatica Mapping Development to User Story Development,
create Monitoring Dashboards for Autosys, and have Routine Validation of Snowflake Tables and Query
Performance, as part of the Narrative Approval Process.
The Architectural Opportunities of SimCorp Dimensions include high availability (HA) of at or above 99.9%
availability for the critical components, Snowflake, Informatica, Autosys, and SimCorp Dimensions' Feed. The
HA design approach will have Redundancy and Failover Capability around the critical components, and thus
reduce the amount of downtime across the various Systems. Snowflake uses Virtual Warehouses that support
Replication and Auto-Scaling of Workload, while Informatica utilizes a Grid Configuration of Nodes and a Load
Balancer approach to improve processing of Data. Autosys employs Dual Event Servers to improve Scheduling
Reliability. Kafka/SQS provides Buffers and Retry Logic to maintain Data Integrity after Failures. The
Architecture is designed around the two primary regions and DR Regions and provides detailed configurations
on each component to allow for quick Failover and Recovery Times to keep Data available during Failures. Best
Practices will include Multi-Cluster Setups of Snowflake, a Shared Repository of Informatica, and Robust
Monitoring and Auto-Recovery.
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Overall, the Design Focuses on High Resilience and Fast Recovery Times to help Businesses operate their
respective Portfolios even if there is a failure. The Components are also discussed relative to the Recovery Time
Objective (RTO) and Recovery Point Objective (RPO) associated with a Data Pipeline. A Snowflake ETL
Process will be delivered to meet the target Pipeline Completion Time of Sixty (60) Seconds, as well as scheduled
for Five (5) Minutes, to provide more flexibility to the Users about their Pipeline Scheduling Options: 5 Minutes,
15 Minutes, and 2 Minutes. Lastly, a SimCorp Feed can complete in One Minute. The importance of having at
least Four Nines (99.99%) end-to-end availability is highlighted, to continue operations and processes of the
Portfolio [13].
Component
RTO (Recovery Time)
RPO (Recovery Point)
Snowflake
60 seconds
5 minutes
ETL Pipeline
5 minutes
15 minutes
Scheduling
2 minutes
None (resumable)
SimCorp Feed
30 seconds
1 minute
Table 1: RTO/RPO Targets
The SimCorp Dimension Architecture High Availability Metrics Dashboard highlights the most important
metrics and thresholds associated with ensuring a high level of availability (HA), including a target Service
Level Agreement (SLA) of 99.99% between SimCorp Dimension and the Snowflake Data Warehouse
environments. The metrics also identify key HA measures including an expected warehouse availability of
99.99% with an alerting threshold of <99.9% for any 24-hour period, as well as an Informatica Job Success Rate
of at least 99.9% with alerts for job failures and Autosys provides 100% schedule completion with all applicable
job and workflow events logged. The Dashboard provides access to additional metrics for evaluating
performance such as an average Snowflake Query Time of 2.1 seconds and a cache hit rate of 85% and a Job
Success Rate of 99.9% (no Job Failures) for Informatica and no NAV Errors (acceptable NAV variance).
Furthermore, there are established monitoring rules for alerts where critical alerts are given for any outages
below 99.9% availability, and performance warnings for cache hit rate(s) below 70% and similar performance
thresholds [14].
Monitoring of queries is performed in areas including Credit Usage, Cache Performance, and Warehouse Load.
The success criteria proposed for the purpose of preparing for Go-Live include maintaining above 99.8%
Snowflake availability; ETL Success Rate(s) of >98%; and NAV Accuracy approaching 100%(referenceable
values) with acceptable variance. Data visualization tools such as Snowsight, Grafana, etc. are utilized for
visualization of trend tracking and Performance Monitoring, along with Slack and Teams for alert and
communication channels and to support proactive mitigations of HA interruptions, the below Figure 2 illustrates
the proactive Monitoring Strategy to assure the continuous Availability of HA, Minimize Interruption and
Maintain and Comply with Compliant Protocols.
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INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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Figure 2: Snowflake Cost Evaluation
CONCLUSION
The Asset Management IT platform has evolved through the transformation of UNIFY into a cloud-native
architecture using SimCorp Dimensions, Informatica ETL and Snowflake. Improvements include a 61%
reduction of spill, a 31% increase in cache hits, and a 46% decrease in credits per query due to the increased
level of data engineering experience. Data governance during the movement of assets to this new architecture
was done using Agile, providing evidence of data integrity through dashboards allowing for process efficiencies
of 30% to 70%. The architectural metrics convey the resiliency of the architecture by providing solid metrics
indicating Critical Support with an RTO of less than 60 seconds. On the Technical Roadmap, the next stage will
incorporate AI/ML capabilities to increase ETL performance with real-time updates using advanced APIs, along
with continued development opportunities for an additional 25% cost savings. Additionally, the roadmap
indicates a planned multi-region HA deployment along with emerging technologies (e.g., blockchain) to further
enhance the position of the UNIFY program as an innovator of asset management technologies while moving
toward the delivery of AI-driven operations that minimize NAV volatility, maximize efficiency, and optimize
resources.
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INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue II, February 2026
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