Business Intelligence and Data Warehousing
- Data Architecture & Modeling
- Master Data Management
- Metadata Management
- Data Quality & Profiling
- Data Governance
- Data Warehouse Implementation
- Data Migration & Integration
- Information Delivery
- Data Mining
- Analytics and Cube
- Change: Changing market demands create a constant state of flux, thus requiring business processes to remain flexible at all times,
- Diversity: Lack of common information standards and the diverse nature of the information sources create a disconnect within organizations due to conflicting data,
- 'Local' vs. 'global' tensions: Many large organizations are composed of autonomous business units, each with their own 'local' demands. Aligning them to corporate needs and vice versa continues to be a key challenge,
Enterprise Data Warehouse Architectures
BNC leverages the concept of iterative building to align itself with the EDW roadmap through an adaptive & an agile process by driving the results and deliverables in line with the organizational goal, thereby delivering results in a short period of time.
One of the most significant factors in achieving this objective is to define the EDW architecture in order to make it fully compliant with the organizational goal.
BNC utilizes the following concepts towards iteratively building the EDW roadmap:
Data Management
Data Integration
Data Delivery
For large organizations with disparate business processes and methods, BNC proposes the Adaptive Approach (Federated Approach). This approach effectively tackles:
In addition to intelligent data analysis, organizations need to know where exactly is the data that has been processed and what it actually means. To address this, BNC has developed its own customized Meta Data Repository Portal that can be easily plugged into a variety of warehouse implementations.
One of the core needs of implementing an effective EDW roadmap is to expose data points from sources/Enterprise data stores/Analytical cubes. BNC has developed an EAI Architecture bus using SOA that can be plugged in any off-the-shelf/custom developed applications.
- Modular approach for Data Quality Management
- Predefined set of guidelines and standards
- Flexibility to adapt with other DQ methodologies
- Improved data quality for best performance
- Focused approach that provides cost benefits
Master Data Management (MDM)
Enterprise wide master data can be described as the lifeblood of an organization as well as a valuable enterprise asset. It enables organizations to have a golden source for a variety of critical data pertaining to entities such as customers, business partners, third-party service providers, and local and international markets. Implementation of advanced enterprise-wide master data management systems have made it easier for businesses to make critical decisions that have potential to affect customer satisfaction, sales, revenues, profits, and regulatory compliance, among others.
At BNC, we understand that optimal enterprise wide master data management can be achieved through a 5 step process that helps understand the data disparity across applications/ geographies in the organization and proceeds to implement and manage a master data solution as below,
Meta Data Management
Meta data refer to the structured information about "who, what, why, when, where and how" of the organizational data. It helps to link various lines of business and organizations (Mergers & Acquisitions) to a common data definition/description of data. Comprehensive data management efforts need to synchronize with the various systems that are operational throughout the organization. It is necessary that these systems make use of common, lucid descriptors and definitions, to be able to deliver quality performance.
BNC’s Meta data management services are part of a much wider vision to help organizations manage their critical data and information in today's highly competitive business environment that results in efficient information/knowledge sharing, increased productivity and efficiency and helps in Data Stewardship, Data Confidence & Data Governance for the organization.
BNC’s Data Quality Services provide organizations with a full 360 degree review and validation of their data and information management initiatives through the data Lifecycle of transformation from operation to analytical data. Data that is incorrect, inconsistent or poorly presented cannot aid the decision making process. High quality, usable data is that which is complete, accurate, consistent, relevant, well-aligned to the business goals it is meant to achieve, and available in a timely and interpretable format.
BNC’s Data Quality Management framework validates operational data, report errors and inconsistencies, cleanses and standardizes data, and removes redundancy by data matching.
- Modular approach for Data Quality Management
- Predefined set of guidelines and standards
- Flexibility to adapt with other DQ methodologies
- Improved data quality for best performance
- Focused approach that provides cost benefits
Data Quality
BNC’s Data Quality Services provide organizations with a full 360 degree review and validation of their data and information management initiatives through the data Lifecycle of transformation from operation to analytical data. Data that is incorrect, inconsistent or poorly presented cannot aid the decision making process. High quality, usable data is that which is complete, accurate, consistent, relevant, well-aligned to the business goals it is meant to achieve, and available in a timely and interpretable format.
BNC’s Data Quality Management framework validates operational data, report errors and inconsistencies, cleanses and standardizes data, and removes redundancy by data matching.
Our data integration services include Tool Evaluation & Architecture, Data Integration & Migration (ETL Development), Data Quality & Assessment, Independent Validation Service for ETL Solutions, Meta data Management and Master Data Management.
- Solution and ETL Architecture Strategy Design
- Technology/ Vendor/ Product Evaluation & Selection
- System Study & Analysis - Identify usage of customized data transformation and migrate to tool based transformation
- Source Data Quality / Auditing
- ETL Strategy to Load in Staging/ODS/Data Marts from heterogeneous systems
- ETL Accelerators - Common ETL programming patterns for Informatica, SSIS, DataStage, etc
- Development & Maintenance Services
- Performance Engineering
- Real time integration using messaging and Informatica PowerExchange
- Cloud Data Integration
- Administration and Support post deployment
- Cross Platform Migration
- Analysis of Source & Target Platforms
- Design Transformation Processes
- Maintain traceability during platform migration
ETL and Middleware
Our ETL Offerings include:
Data Warehouse/ Application Integration:
Platform Migration
- Comprehensive reports, dashboards, and scorecards
- Highly effective data mining capabilities: Data cubes / Data warehouse
- Seamless integration with legacy as well as the most advanced enterprise systems
- Automated workflows - Report requisition, generation and delivery
- Easily customizable reports available in various formats (PDF, Excel, HTML, Charts) and deliverable online via web.
Business Intelligence and Reporting
BNC’s BI Competency Center offers end-to-end solutions leveraging industry leading tools such as Cognos (IBM), SAP Business Objects, MicroStrategy, Hyperion and SSRS among others offering a perfect blend of technology and domain insight. These solutions, delivered across multiple formats, enable organizations to make more informed and balanced decisions for mobile compatible websites.
Our BI domain practice encompasses areas such as Reporting, Performance Management and Analytics, that are a primary prerequisite for the successful implementation of any Business Intelligence solution.
