Enterprise Data Warehouse Architectures
Dawn 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.
Dawn utilizes the following concepts towards iteratively building the EDW roadmap:
Data Management
- Data Architecture & Modeling
- Master Data Management
- Metadata Management
- Data Quality & Profiling
- Data Governance
Data Integration
- Data Warehouse Implementation
- Data Migration & Integration
Data Delivery
- Information Delivery
- Data Mining
- Analytics and Cube
For large organizations with disparate business processes and methods, Dawn proposes
the Adaptive Approach (Federated Approach). This approach effectively tackles:
- 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,
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,
Dawn 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. Dawn has developed
an EAI Architecture bus using SOA that can be plugged in any off-the-shelf/custom
developed applications.
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 Dawn, 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.
Dawn’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.
Dawn’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.
Dawn’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
Dawn’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.
Dawn’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
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.
ETL and Middleware
Our ETL Offerings include:
Data Warehouse/ Application Integration:
- 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
Platform Migration
- Cross Platform Migration
- Analysis of Source & Target Platforms
- Design Transformation Processes
- Maintain traceability during platform migration
Business Intelligence and Reporting
Dawn’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.
Key Features of Dawn’s Business Intelligence and Reporting Solutions:
