Architecture Design
Data Modeling
Destiny Corporation’s Data Modeling service provides your organization with customized, business-specific solutions and will create effective data models that meet your current and evolving needs. Our experts employ both tool-based and manual methodologies to customize existing models or build new ones for enhanced business performance.
We build the following types of Data Models:
- Entity Relationship (ER) Modeling: Modeling services designed for OLTP databases.
- Dimensional Modeling: Modeling services designed for star schema and analytics.
- Data Vault Modeling: Modeling services that can reflect the dynamic relationships within the data over time.
- Business Modeling: Modeling services that incorporate BI tools and KPI driven dashboards for better business understanding. These models use open bus architecture to support future business needs.
Our Data Modeling services include:
- Development Services: Our consultants actively work on the data models while providing education and knowledge to your organization’s participating team members.
- Mentoring Services: We lend advice and support when you need it.
- Quality Assurance Services: We review your models and make best practice recommendations
Data Warehousing
Regardless of whether you are searching for a Data Warehouse to support your entire enterprise or a smaller department within your organization, Destiny Corporation’s data architects will help conceptualize, design and implement your data warehouse solution.
OUR COLLECTIVE DATA WAREHOUSE EXPERIENCE COVERS ALL THE MAJOR DATABASE VENDORS, INCLUDING:
- Cloud Offerings
- Columnar Databases
- Data Marts
- Data Warehouse Appliances
- In-Database Processing
- In-Memory Databases
- Legacy Databases
- Massively Parallel Processing (MPP)
- On Premises
- Scalability
- Security
- Storage
- Stored Procedures
- User Defined Functions
ETL/Data Integration
Data Integration is fundamental to enterprise information management/data warehousing initiatives. An effective data integration strategy, architecture and supporting infrastructure and processes are vital components in the delivery of analytic solutions. While Extract, Transform and Load (ETL) is still a commonly used technique for a data warehouse focused data integration, the evolution of technology coupled with the growing sophistication of data consumers has driven the increasingly complex nature of data integration. Moreover, rising end-user requirements for “real-time” data intensifies the demands on a data integration infrastructure, while scorecards and dashboards enhance the expectation of seamless visibility into data.
As the capabilities of technical infrastructure have expanded, initiatives like Enterprise Information Integration (EII), Enterprise Application Integration (EAI), Master Data Management (MDM) and Product/Customer Data Integration (PDI/CDI) are viable components of EIM. Destiny Corporation provides expertise spanning the continuum of data integration.
OUR CONSULTING SERVICES ADDRESS THE WHOLE LIFE CYCLE OF ENTERPRISE DATA MANAGEMENT SOLUTIONS, INCLUDING:
- Data Architecture– Optimizing database availability and usage based on an understanding of business information needs, logical and physical data modeling and other activities
- Data Governance– Maintaining principles, policies, procedures and standards for the effective use of data
- Data Integration– Using ETL/ELT processes to create a consistent, relevant and trusted view of data across business units and subject areas
- Data Quality– Assessing whether current data assets are fit for their intended use
- Data Security and Privacy– Ensuring regulatory compliance across data subject areas, including monitoring and audit capabilities
- Data Stewardship– Orchestrating the day-to-day activities of creating, using and retiring data
- Master Data Management– Creating consistency in reference and relationship data regarding product, customer, supplier and organizational issues
- Metadata Management– Organizing the people, processes, and technical components needed to ensure that metadata is easily accessible, consistent, current, accurate and complete
- Unstructured Data Integration– Extracting meaning from text using various linguistic techniques, adding structure and blending it with numerical data for analysis