Data Management

Release 25.04

Ability to write User Mart Execution Meta Data to Azure Service Bus for Integration ETL STP

As of version 25.04, clients now have the option to write User Mart Trigger messages to an Azure Service Bus Queue or Topic in order to enable the initiation of ETL processes downstream of SimCorp Dimension.

When User Mart data files are written to an Azure Blob Storage Container, a trigger message can also be generated at the time of execution. This message contains various meta data elements related to the execution of the User Mart and corresponding data file. Information in the file includes, but is not limited to, the location of the data file on the Blob Storage Container, the time it was generated, the number of records. For user marts executed as part of a Portfolio or Fund STP-initiated Data Warehouse load, the corresponding Fund and/or Portfolio Identifiers are also included.

Prior to 25.04, clients only had the ability to write this trigger data into a file on the same Blob Storage Container as the Result File.However, as of 25.04, this information can now be written to an Azure Service Bus Queue or Topic. This allows clients to read the trigger file information and begin loading the data from the Results File as part of an automated flow.
The User Mart Trigger Messages can be included in any execution user marts within a Data Warehouse Load Plan where the resulting data is being written to an Azure Blob Storage Container:

This includes:

Via Portfolio/Fund STP where loads are restricted to data related to a specific Fund and/or Portfolio
Manually executed from within the Data Warehouse Manager on all SimCorp Dimension (Not Fund/Portfolio-specific)
Execution via batch job

Benefits

Enhanced automation with Azure Service Bus: Utilizing Azure Service Bus Queue or Topic for User Mart Trigger messages enables the automated initiation of ETL processes, significantly reducing manual intervention and boosting operational efficiency.
Reliable and scalable messaging: Azure Service Bus provides a robust and scalable messaging platform, ensuring that trigger messages are reliably delivered and processed, enhancing overall data integration and processing workflow.
Flexible and decoupled architecture: Writing trigger data to Azure Service Bus allows for a more flexible and decoupled architecture, enabling clients to manage and initiate downstream processes independently of the storage solution, thus enhancing overall system flexibility and maintainability.

User Mart Trigger messages can be optionally included as part of the User Mart Execution in Data Warehouse

Example of user mart trigger message in JSON format which is written to Azure Service Bus Queue or Topic

Users have the option to write either to a Queue or Topic in Azure Service Bus

View Messages on Queue or Topic in Azure

The contents of the message can be viewed directly in Azure Service Bus from the Queue/Topic

Subscription based licensing

Data Warehouse Manager

Sales module dependency

Snowflake Extension for Data Warehouse

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Previous releases

Release 25.01 Data Management

New Extended Event Added for loading Data Warehouse by Fund or Portfolio

As of version 25.01, clients can include a new Portfolio or Fund STP event, which executes a load of the data warehouse for the fund or portfolio(s) forming part of that STP flow.

This new feature works by configuring a Data Warehouse Load Plan to be executed as part of that Portfolio or Fund STP flow.

When executed in this way:

Any Fact, Dimension, Base Mart, or User Mart definitions containing the relevant Portfolio or Fund ID columns will only be loaded for the specified fund or portfolio.

Multiple Portfolio or Fund STP processes can be executed in parallel in this way.

User marts that use a load trigger file will have details of the fund or portfolios included in the load.

The Data Warehouse Monitor has been updated to include the load time (Normal/Portfolio/Fund along with a column identifying the relevant entity that was included in the load, ie Portfolio ID/Fund ID or “Normal”.

Portfolio and Fund STP Flow Status is updated upon completion of the Data Warehouse load.

This feature is available exclusively in the Cloud Data Warehouse.

Benefits

Allows business event-driven updates to the Data Warehouse.
Allows clients to update the Data Warehouse and any downstream data recipients in a targeted way, breaking the “all-or-none” batch process that previously existed.
Fund and Portfolio loads to the Data Warehouse can be managed independently, as needed, without dependencies on other funds or portfolios being completed.
Integrates business processes and Data Warehouse flow as part of the same STP process, rather than treating them as separate processes.

Fund administration manager containing event for Loading Data Warehouse

Data Warehouse Load Monitor showing Load Scope Type and Scope

Subscription based licensing

Data Warehouse Manager

Sales module dependency

Snowflake extension to DWH

New Data Subject Area for Order Management added to SimCorpIMW

As of version 25.01, a new Data Subject Area has been added to the SimCorpIMW called “Order Management”. This Data Subject Area consists of a set of Fact and Dimension tables which access data from all of the major tables which make up the New Order Manager. Clients can use this Data Subject area to report on all stages of the Order Lifecycle in SimCorp Dimension.

Benefits

Provides clients the ability to report on all aspects of the order lifecycle through the data warehouse without accessing the system directly.

Data from New Order Manager is joined with all other relevant SimCorp Dimension data in the Data Warehouse with key relationships.

Order Management Data Subject Area in Data Warehouse Manager

Subscription based licensing

Data Warehouse Manager

Sales module dependency

Snowflake and Oracle Data Warehouse

Release 24.10 Data Management

Content Analytics

Analytics is created to enable admin users to understand how clients are interacting with the News page and with what content they most engage. The audit table provides the raw data, however, summarizing the information in an engaging way for users to quickly gain insights and greater understanding is key. This is the purpose of the Analytics page.

The chart area

Here, three charts and one table summarize various aspects of user’s navigation of content for the Role(s) and Type(s) you have selected via the filter for the last 28 days before and including your selected Date.

They are:

User engagements where two charts are available, select:
10 most interactive to display the top ten users that have navigated to the most content from their News page.
10 least interactive to display ten users that have navigated to the least content from their News page.
Top content types and tags where two charts are available, select:
Top types to reveal a breakdown of the number of times a certain content type has been accessed.
Top tags to reveal a breakdown of the number of times certain tagged content has been accessed.
Content navigation that displays the number of times news pages have been accessed, plus the total number of items vs unique content that has been navigated to from the news page.
Top 25 articles table. This table lists up to a maximum of 25 of the topmost news items users have accessed over the last 28 days before and including the date selected in the filter area.

Benefits

The whole analytics for Content usage in one place
Presented in charts and table

Subscription based licensing

Digital Engagement Platform

Sales module dependency

N/A

Ability to import data to Data Warehouse from a REST API Endpoint

Clients using the Snowflake Data Warehouse can now create a REST Web API integration that allows them to use data that is retrieved through Web API requests (using OAuth 2.0 authentication) as the data source for a fact or dimension table.

To support the process of configuring an API integration, a new API Editor has been introduced, which allows users to:

Configure the various combinations of API requests parameters to be sent to the desired endpoint using the Cottle templating language
Specify how the resulting payload should be transformed
Preview the resulting JSON to be sent to the API
Preview individual API requests against the API
View the resulting API data payload and the transformed result

As part of the introduction of this feature, a new standard IMW Fact table with a supporting Cottle template has been introduced for retrieving data from the SimCorp Investment Analytics Platform. This table is populated from the Single Day Calculation Endpoint and captures performance analytics by portfolio. Additional standard endpoint integrations with the Investment Analytics Platform will be rolled out over subsequent releases.

Benefits

Expands on the Data Warehouse’s integrated coverage to allow clients to import data from a range of external sources that provide API functionality for data retrieval
Flexible framework in which to configure and test API requests from inside Data Warehouse Manager prior to loading
Load process fully integrated into existing load plan functionality
Configuration transportable with Data Warehouse Model between environments

Fact table with Web API specified as data source. Different configurations can be defined for inclusion in the DWH Load Plan.

Different API configurations specified on Fact or Dimension table definition are executable as separate loads on the Data Warehouse Load Plan.

API requests can be configured using Cottle templating language in API Editor. The resulting JSON requests can be viewed in the panel below.

Individual API Requests can be selected in the editor and tested against the API.

Preview transformed API result directly in API Editor as it will appear in fact or dimension table.

Subscription based licensing

Data Warehouse Manager

Sales module dependency

Snowflake extension to DWH

Release 24.07 Data Management

Cloud Data Warehouse – Snowflake Source Schema for importing external data

Cloud (Snowflake) Data Warehouse clients will now have the ability to create their own Snowflake Source Schema, within the same database as the SimCorp Data Warehouse. Tables on this schema can act as a Data Source to a table in the SimCorp Data Warehouse.

Prior to 24.07, clients could only import external (Non-SimCorp Dimension) Data via Files placed directly onto the Azure blob storage. The new Snowflake Source schema provides a new means by which clients can import external data, leveraging native Snowflake functionality.

Benefits

Allows clients to leverage native Snowflake functionality for importing external data directly into the database for use as a data source to the SimCorp Data Warehouse.
Provides a means of staging data in Snowflake Source Schema enabling clients to manage and validate external data within the Snowflake environment before integrating it with the SimCorp Data Warehouse
Enables a greater level of governance around defining how external data is mapped to corresponding Data Warehouse table.

Snowflake Data Warehouse Database model with Source Schema Included

Tables can now specify Snowflake Source Schema as a data source

Tables with Snowflake Schema as a source can be executed within a load plan. Data is loaded from the source schema table to the staging and target table in the SimCorp Data Warehouse

Please note: there may be implications to increased Snowflake consumption in terms of storage and credits. Also for the SimCorp SaaS clients where this is to be implemented there needs to be consideration for SaaS configuration to enable firewalls and whitelisting where specific connectivity to Snowflake is required thus please contact your CX to provide additional information and dependencies.

Subscription based licensing

Data Warehouse Manager

Sales module dependency

Snowflake extension to DWH

Release 24.01 Data Management

Release 23.10 Data Management

SimCorp BI Cloud

As part of our solutions capabilities we are extending our capabilities to complement our on-premise deployment with our new offer. SimCorp BI cloud is a cloud-based BI and Analytics tool that is powered by Qlik®

It allows you to gain unique insights into all data domains and meta information (processing / SLA details). For end users they can self server and navigate dashboards, publish and schedule content.

In addition, for power users we provide a designer environment that enables clients to add additional dashboards and reports as they see the need. So all currently available dashboards can be seen as template that can be further extended and tailored.

Benefits

Enable business users to get visual insights to their data with flexible self-serve intuitive capabilities, including leveraging embedded NLP and NLG for natural language conversational analytics to enable actionable insights, all delivered within a native cloud application.
Optimize your reporting and analytics environment with single pane of discovery in our SimCorp BI, by accessing all your data at your fingerprints. Changes can be done with no dependency on IT developers.
Save on having multiple solutions resulting in complex data reporting pipelines which can be automated for direct access to your business data.

SimCorp BI Cloud Analytics Hub is a new way to navigate content inside SimCorp BI Cloud tenant. You can browse, search and navigate across all the datasets which SimCorp BI Cloud user have access to.

The hub is split into seven sections (Getting Started, Home, Favorites, Catalog, Collections, Alerts, Subscriptions). Each representing an unique way to organize the content and access new features.
SimCorp BI Cloud user can easily organize and customize the Home section – to view only desired Qlik content.
Catalog section provides an access to Spaces and it’s all content.
There is both a Global and Catalog filters where spaces, terms, charts, apps, automations, data, notes, owners, creators, and tags can be found by name.
Qlik content can be arranged and the sorted alphabetically, by the date it was modified and by the creation date.
In Collections section, you can view and group apps, charts, notes, automations and links into various collection groups. It can be achieved by simply clicking “Add to collection” icon on any content type.

Subscription based licensing

SimCorp BI Cloud

Sales module dependency

Data Warehouse Manager or Data Integration Layer for BI

Release 22.10 Data Management

Two additional Vizlib Qlik extension bundles

Two additional Vizlib Qlik extension bundles, increasing the collaboration options and Financial reporting capabilities of SimCorp BI

VizLib Finance Report. Allows for visualizing data in a professional P&L or Balance sheet. Fully customizable and enables both a professional look and feel as well as an extended range of options and customizations when visualizing tabular data.
Vizlib Collaboration. Enables users to communicate with dashboards in context of the data and filters they are seeing and applying. Further enables writeback functionality for end users to input data through the dashboards, opening for a wide range of use cases.

See generic examples below:

Subscription based licensing

SimCorp BI

Sales module dependency

Dependency on SimCorp BI Core

Release 22.01 Data Management

Data Warehouse on Snowflake

This module enables SimCorp Data Warehouse to be deployed on Snowflake. For clients that want to run their reporting and analytics data on a native cloud data warehouse. Snowflake (a market leading Cloud RDBMS platform) has the unique capabilities of offering a data cloud service where they manage the overhead of maintaining platform as well as flexibility in offering a consumption-based usage model.

The SimCorp Cloud Data Warehouse is provided with an Investment Management Warehouse Model (IMW) which a best practice data model based on Ralph Kimball methodology.

It allows clients to load data from SimCorp Dimension as well as external data sources. It’s easily extendible with new tables, new fields and adding additional data sources via the provided intuitive tool called Data Warehouse Manager.

For our existing SimCorp Data Warehouse users, the user and dataflows are similar thus easily transferable to a Snowflake Cloud target.

For new users to SimCorp Data Warehouse, our cloud offering provides an intuitive interface i.e. Data Warehouse Manager for deploying our standard Investment Management Warehouse model as well as providing governance for structural changes such as adding new fields or new tables or new data sources.

The Investment Management Warehouse is available with the following content

Benefits

Enables easy access to your investment data for reporting and analytics
Optimizes your data landscape with a single view of truth for your data
Reduces operational overhead and achieves a governed self-service environment to support your digital journey

Subscription based licensing

No subscription package. Pilot release

Sales module dependency

Data Warehouse Manager for subscription clients.
Data Warehouse Manager
Investment Management Warehouse (and additional data subject areas)

Data Warehouse on SCDaaS (Powered by Snowflake)

This module enables the delivery of Cloud Data Warehouse as a Service.

For clients that want to run their reporting and analytics data on a native cloud data warehouse. Snowflake (a market leading Cloud RDBMS platform) has the unique capabilities of offering a data cloud service where they manage the overhead of maintaining platform as well as flexibility in offering a consumption-based usage model.

The SimCorp Cloud Data Warehouse is provided with an Investment Management Warehouse Model (IMW) which a best practice data model based on Ralph Kimball methodology.

For our existing SimCorp Data Warehouse users, the user and dataflows are similar thus easily transferable to a Snowflake Cloud target.

The Investment Management Warehouse is available with the following content:

Benefits

Fully managed Data Warehouse as a Service enables you to outsource the operation overhead of maintaining and managing the data warehouse
Enables easy access to your investment data for reporting and analytics
Optimizes your data landscape with a single view of truth for your data
Achieves a governed self-service environment to support your digital journey

Subscription based licensing

No subscription package. Pilot release

Sales module dependency

Data Warehouse Manager for subscription clients.
Data Warehouse Manager
Investment Management Warehouse (and additional data subject areas)

SFDR DWH Reporting

For -those not using the Data Warehouse Manager this module enables you to leverage our supported and maintained reporting structure for SFDR reporting. Then this restricted use Data Warehouse Manager allows you to build reports using the data provided in this structure and leverage the features of the DWH Manager for the sole purpose of SFDR reporting only.

This product covers the following

Use the permitted data subject areas of Strategic investment Analysis Data Subject area and specifically the Concentration Aggregation Results Fact table
Creation of data marts where data is sourced from the above subject area and fact table
Sourcing data from SimCorp Dimension for the purpose of supporting SFDR reporting
Extensions to Concentration Aggregation Results Fact table for the sole purpose of supporting SFDR reporting

Benefits

Standard Data Warehouse with reporting data content for SFDR reporting eliminates the need for clients to build custom extractions
Enables faster implementation of SFDR reporting
With add on modules, ability to extend Data Warehouse use to other data subject areas and consumers

Subscription based licensing

SFDR - Sustainable Finance Disclosure Regulation

Sales module dependency

Data Warehouse Manager for subscription clients.
Data Warehouse Manager
Investment Management Warehouse
strategic investment analysis DSA
Standard Platform DSA
SFDR - Sustainable Finance Disclosure Regulation