US

Data Warehouse Development for Integrated Banking Data

The appropriate data management in banks ensures information quality and consistency. Data Warehousing helps banks build more effective processes for data collection, processing, storage, exchange, analysis, etc. Gathering information from various sources and converting it to valuable insights are the main objectives of DWH software.

Through the right technology, we help banks use their data as efficiently as possible. Our expertise allows us to build, upgrade, modernize DWH solutions, and make them addressing your current and future organizational needs.

Our data warehouse consulting and development services are focused on overcoming your challenges with data ubiquity, the large volume of information, new customer demands. We also know how to harness predictive analytics and Big Data to help your organization make data-driven decisions and accurate forecasts of future customer behavior and demands.  

DWH Solutions & Services We Offer

By business function

DWH for Reporting & Analysis

DWH solutions reduce the time for preparing financial and managerial information, reporting, cost-benefit analyses. Along with this, they give the following benefits:

  • Minimizing errors in administrative and financial reports
  • Quick access to information
  • Multivariate data analysis
  • Accurate forecasts of competent
  • Cost-benefits analyses of branches, new products, or services
  • Customer profitability segmentation

DWH for Credit Risk Management

DWH software can significantly help banks govern their risks in the following areas:

  • Non-payment monitoring
  • Forecasting of effects on the credit policy
  • Prediction of credit usage structure
  • Direct credits abuse

DWH for Retail Target Marketing

A holistic view of the bank’s clients helps improve customer retention and attraction. DWH solutions offer excellent capabilities to gain a 360-degree view of your customers by gathering in-depth analytics on behavioral patterns, historical and real-time data, and other data pertaining to marketing purposes.

  • New markets analysis
  • Customer behavior analysis
  • Marketing campaigns assessment
  • Client-product matrix
  • Personalized offering
  • Cross and up-selling

Relational Database for Data Warehousing

Banks need relational databases when they plan that their data warehouse will grow. They ensure scalability to support a large volume of data and the following capabilities:

  • Customer segmentation
  • Risk modeling
  • Customer demands identification

By services

Data Warehouse Development

We have experience building DWH solutions for banks, including the development of the following features:

  • Data collection mechanisms
  • Data storage
  • Data aggregation, data marts
  • Analytical data processing
  • User access rights
  • Data visualization
  • Documents flow

Software-Defined Storage (SDS) Development

We design, develop, and implement software solutions for extract, transform, and load (ETL) processes, data quality management (DQM), and data masking.

  • Automated data management
  • APIs for managing, allocating, and releasing resources
  • Virtualization of data access
  • Storage infrastructure
  • Storage resources monitoring and management

Data Warehouse Consulting & Upgrade

We consult our clients on custom and existing DWH solutions and licenses in accordance with your current and future needs and challenges:

  • DWH software upgrade, customization, modernization
  • Consulting on DWH products licensing
  • Business analyses and functional requirements

How We Cooperate

We have a well-established procedure for DWH projects that consists of the following stages.

Business Analysis and Functional Analysis

We gather, formalize, and prioritize high-level requirements from all the stakeholders. Detailed business requirements for data marts, reporting, data migration, and others are further formalized according to the project roadmap.

Development

We build and modernize DWH solutions. First off, we prepare the client’s IT infrastructure for implementing the project, perform data cleansing, enrichment, and quality management procedures. Next, we develop data storage and data marts, and finally, set up the tools for analytics and reporting.

Implementation

The implementation stage includes data migration, testing, data cleansing, enrichment, and the implementation itself. We also provide user training, maintenance, and support.

Once all the requirements are formalized, we create a functional specification and approve it with clients.
Functional specification of a DWH project may include, but is not limited to, the following: data marts, reporting, warehouse data models, procedures and algorithms for data loading and storing, data cleansing procedures, data quality control, and other data-related procedures and algorithms, depending on your specific needs.

What Impacts Your Project Duration

Every DWH differs from another as well as the challenges our customers face differ. Thus, we apply the critical path analysis to calculate the minimum time required to complete it. Combined with a Work Breakdown Structure (WBS), this approach allows us to inform the client about the approximate completion date. However, based on our experience, such projects take from 6 to 18 months.

 

The following factors affect the duration, as well:

 

  • The complexity and scope of the project
  • The type of services you need (development from scratch, modernization, upgrade)
  • The nature of the issues you have
  • The kind of DWH solution you need (ready-made, custom)

What Affects Your Project Costs

The project’s cost depends on many factors. A more accurate price is possible to get when you contact us directly. After a series of sessions with all the stakeholders and understanding of your top-level requirements, we would be more accurate about the price.

 

Here are some factors affecting the estimation:

 

  • The complexity and scope of the project
  • The cost of DWH platform

What We Need from Your Side

Data Warehouse development or modernization requires deep involvement of the bank’s business and IT departments. It is needed to correctly gather all the requirements and understand the real challenges associated with data quality, consistency, and management.

Technologies and Platforms

  • tecnhologies icon Oracle
  • tecnhologies icon Oracle DI
  • tecnhologies icon Oracle BI
  • tecnhologies icon MS SQL
  • tecnhologies icon PostgreSQL
  • tecnhologies icon IBM DataStage
  • tecnhologies icon IBM Spectrum Storage
  • tecnhologies icon QlikView
  • tecnhologies icon IBM Cognos

EXPLORE OUR CASE STUDIES

Banking

Data Warehouse for Bank

  • PL/SQL
  • Oracle
  • Software Architecture
  • System Integration Services
  • Data Migration Services
  • UI/UX Design
  • Data Warehouse & ETL
  • BI & Reporting
Learn more

Banking

Customer 360 System for Bank

  • Oracle
  • Git
  • Jira
  • Software architecture
  • Custom software development
  • Data warehouse & ETL
  • BI & Reporting
  • Data Science
Learn more

Insurance

BenefitNet Claims Management Solution

  • .NET
  • Angular
  • Microsoft Azure Cloud
  • Visual Studio
  • UI/UX design
  • Web app development
  • Custom software development
  • BI & reporting
Learn more

Healthcare

Medical Errors Filing System

  • C#
  • PostgreSQL
  • ReactJS
  • Custom software development
  • System integration services
  • Big Data
  • Healthcare
  • Saudi Arabia
Learn more

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