New York USALondon UKMunich GermanyZug Switzerland

• Compliance

• Risk management

• Operational efficiency

• Faster & more accurate customer insight

• Regulatory reporting

Non-technical challenges

• It is hard to evaluate data warehouse adoption ROI

• A lot of implementation and deployment efforts, long-

term perspective

• Considerable time is required for business users training

and support during the initial stage

• The platform should be evolving together with the

company growth and the platform should be

enhancement accordingly

Technical challenges

• Big volume of data for analysis, sometimes the need to

have a whole suite of federated data warehouses

• Real time updates from data sources support

• Data quality from various data sources

• Complexity of the source data and ETL processes

• Availability, stability and scalability for data growth

• Enhance data quality and consistency

• Single view of customer

• Streamlined regulatory compliance reporting

• Data governance for decision making

• Consolidate different data sources across multiple

channels and products

• Enhanced business & historical intelligence

• Flexible reporting with rich analytics and visualization

• Establishing business process management

• Single point of truth & data model; reliable and accessible for

anyone

• Higher ROI, lower risk & time to value

• Self-service for business users

• Save time

Planning Implementation Maintenance and

Enhancement

Assessment and

Improvements

• Requirements gathering

• Architecture design

• Estimating the efforts for

implementations, planning

the deployment strategy

• Calculation of ROI, costs

analysis

• Project prototyping

• Architecture and risks

validation

• Use of in-house application

blocks for third party

systems and data vendors

integration

• Automated testing of

existing reports and new

implementation

• Smooth iterative

deployment

• Users education and

support

• Data quality / governance

framework

• Integration with new data

sources

• Adding new dimensions

into existing data

warehouse

• Building new reports

• Health check monitoring &

maintainability

• Current state analysis

• Building a roadmap of

improvements

• Planning smooth

transition to newer

version of data

warehouse

• Identify, analyze, solve critical business problems with the help of technology

• Consult about technology options, platforms, and design techniques across product and project lifecycle

• Design & develop multidimensional cubes

• Tuning technological stack

• Develop ETL scripts and procedures; analysis and design of data extraction, transformation, and loading strategy

• Provide UI/UX services

• Data validation, system integration services

• Performance & user acceptance testing

Data storages Data integration BI & Analytics Platforms

Portfolio Management

Trading

RiskOperations

Terms & Conditions

Investor Reporting

Compliance

Reconciliation

Market Data

Data

Warehouse

Regulatory Reporting

CRM Contacts

Highlights

• Data management, data imports, granular data security, automated ETL workflows, reporting

engine, scenario creation and analysis

• Fast and easy way to sign up and support new businesses / new LoBs, as well as operational

creation of a DWH (new domain) for a particular LoB. Federated system with a single

management, functional, and reporting layers across different LoBs and DWHs

• Self-service reporting for middle and back office to create custom reports ad-hoc without IT

department involvement. Flexible reporting with the ability to choose data for viewing and

analytics. Reports and books are available for automatic and recurrent generation

• Needed data about transactions ‘points’/data can be downloaded in real-time onto a

separate sheet in an excel spreadsheet

• Reporting is available via a custom plug-in that converts users requests into a request to

OLAP cube

• Data traceability. Drill downs into ETL calculations

• Ability to customize and limit user permissions and access to data and operations performed

• Log of all tasks initiated by users (data imports, cube reprocessing, reports runs, and data

changes)

• Generic model engine, standard financial models for revenues, expenses, hedge fund

allocation and compensation, dashboards

• Rules and scenarios application for data transformation into data models according to

business requirements

The client is a large investment management group with

approx. $70B AUM, with a focus on undervalued and

distressed assets.

Challenge

• The system supports 18 departments / lines of

businesses

• Rich incoming data with various structures and formats

• New counterparties / departments are added frequently

• Presentation-quality reports that are highly format

intensive

• Fragmentation of existing data across silos

Case study

Operations

• Import

• Report

• Validate

• Reprocess Cube

• Data Changes

Database

DocumentRepository

Model Cube

Report Cube

Excel Plug-In

• Data Imports

• Reports

Web Applications

• Data Management

• Case Management

• Publishing Books

• Models Management

• Security Management

Client Applications ApplicationServices

Data Warehouse

Case study

The client is a global investment management firm.

Challenge

• Building comprehensive data management solutions to

provide various types of regulatory reporting, investor

reporting or data visualization for internal and external

use

Highlights

• Easy to use, intuitive front-end reporting tool

• Data warehouse aggregates data from client’s systems

or other data sources and serves as a “single source of

truth”

• Raw data aggregation or pre-aggregated data import

• Flexible reporting data persistence (local DB, file system,

external system or Cloud)

• SEC/ESMA files visualization

• Building pre-calculated summary values to speed up

report generation

Portfolios Data Source

Data

Warehouse

AccountingData Source

Risk / Stress Testing Engine

Credit / Liquidity /

Market Risk Data Source

Aggregation Process

Compliance reporting

web portal (fund

admin, fund

manager)

Functional / Presentation

Layer Style

Executing clients web

portal– Compliance

portal (fund admin)

Desktop Compliance

reporting application

(fund admin, fund

manager)

Internal reporting /

data visualisation

portal (fund

manager)

Case study

The solution is designed for investment management companies.

Highlights

• Data management, import, security, publishing, workflow, scenario creation and analysis, and a reporting engine

• Uses a staging environment for data load from multiple external data sources

• Applies rules, scenarios and the associations between them for data transformation into data models according to business requirements

• Complex dashboards and reports that can be scheduled to run recurringly in the future

Data warehousing activities

• Implementing the Enterprise Data Warehouse Platform

• Creating an efficient reporting and distribution system for finance data

• Mining the Finance Data Warehouse to prioritize improvement initiatives

The client is a major US data provider

Challenge

• Highly developed risk data infrastructures for replacing semi-

manual workarounds

• Providing a flexible platform for ad-hoc and management

reporting

Highlights

• Data Management layer including Data Warehouse integrated

with existing Risk Management System

• ETL processes for scheduled loading data from various data

sources

• Ability to onboard and access new data sources in a federated

manner

• Quick data linking and enrichment in order to enable new

business opportunities with better reference data, text mining

and data analytics

• Interactive visualization with built-in data drill-down and filtering

using QlikView

Use case

Traders

Product Control

Risk Managers

Desktop Presentation

WebPresentation

QlikView Publisher

QlikView Server

Distributed in-memory

caches

Grid Analytics

Data Sources

Reference Data Providers

Market Data Providers

Internal Data Sources

External Data Sources

Data Warehouse

Meta Data

Raw Data

Summary Data

Historical Data

AggregatedData

We

b S

erv

ice

s

Su

b /

Pu

b

Ba

tch

/ F

TP

Initially the client needed to improve systems development and support processes. Building on the success of the initial consulting engagement, DataArt

successfully executed a critical Data Warehouse re-engineering project.

Case Study

Highlights:

• Staging data schema supports a variety

of data sources and preliminary data

preparation

• Enterprise data warehouse provides

aggregated view on company assets

and rich associated analytics

• Data is consumed by the fund

management tool that supports daily

operations of the firm

• Dedicated reporting facility for all types

of reporting (compliance, investor,

executive); secure, flexible and

controllable solution for report design,

generation, and distribution.

CRM Data

Valuations, Risks, Management, Performance

Market Data Feeds

Funds, Investments, Vehicles, Deals, Transactions

ETL / Data Load Service

Staging Database• Time Series Aggregation• Data Governance

Reporting

Master Database• KPI’s• Company-Wide Aggregation• Analytical Cubes / OLAP

ETL / Data Load Service

Compliance Reporting Investor Reporting Executive Reporting

Fund Management Tool

A global B2B supplier of online hotel bookings and inbound travel

services to the tourism sector. The client offers its customers access

to more than 12,000 properties around the world.

Challenge

After acquisition of an online hotel reservation company, the client

faced a problem of gathering and analyzing data from two booking

platforms – iVector and Travel Studio.

Solution

The DataArt team delivered the solution that enables the client to

consolidate and analyze statistical data on hotel bookings from two

different reservation platforms.

Functionality

• Consolidates statistical data that have different structure,

granularity and attribution

• Checks the aggregated booking data for duplicates and cleans it

• The transformed stats can be consumed via Excel, or any other BI

tool

Use Case: Analytics / BI

Data Warehouse

Multidimensional DB

Excel

iVector Travel Studio

Cognos BI Tools

The DataArt – Nasdaq combination is great for

what we were trying to accomplish with our

trading floor. The new system has been amazing

in terms of performance; it is lightning fast,

compliant, and handles the workflow for our

brokers in a tremendous way.

Kevin Kennedy

SVP and Head of U.S. Options Nasdaq

DataArt is an invaluable strategic partner for Monex

Europe. We trust DataArt to deliver all of our business

systems developments and to ensure reliable, secure

delivery of our IT based products and services internally

and to our clients. We also rely on DataArt for their

industry knowledge, advice and support at all times.

Shelton Fray

Director and Co-founder Monex Europe

All trademarks are the property of their respective owners

Our decision to work with DataArt was based on

their understanding of our sector, depth of

technical capabilities, and real drive for creating a

true partnership model. They are a great

organization to work with and are helping us to

deliver on the vision of our technical roadmap.

Neil Patel

IT Director Apax Partners

With DataArt’s support, Valphi can now bring to

market a platform that merges the latest

developments in financial services data with a

visualized user experience that enables and

encourages the human brain to identify and

exploit trends.

Emmanuel Dayan

Managing PartnerValphi

All trademarks are the property of their respective owners

All trademarks are the property of their respective owners