|
Enterprise Data Strategy and Architecture
Since 1993, the leadership team has been engaged in data strategy and architecture with numerous corporate clients, and received consecutive Gold Application Development Partner Awards from Sybase in the 1990's for delivering functional application designs.
Subsequently, data modeling as well as ETL/ELT experience has consisted of several OLTP, OLAP, ROLAP, MOLAP, MPP, AMPP, Discrete Models for Stats based Predictive Analysis as well as big data based (i.e., high volume and high density) Web Analytics. As a result, we are uniquely qualified to align technology executed via data models with business environments to guarantee success of a project, and to derive enterprise data strategy.
Based on our background in IT and business, we are uniquely able to develop conceptual models to align technology with business for database applications where the interface is the data model. As a result, we do not deploy theoretical models based on inherent data which ultimately fail to satisfy the business environment, but rather work with stakeholders to derive practical structures and derive optimal solutions to satisfy the business environment via direct or indirect interfaces.
The physical data model is the interface between business and technology. The interface with business maybe direct as in Decision Sciences or Business Intelligence environments or indirect via Java custom class objects as in web applications. We not only have extensive experience deriving entity relationships as well as aligning the bits (i.e., physical data model) with the business interface, but also defining and communicating domains via conceptual models with business stakeholders to guarantee success of a project. We rely on an iterative design approach to deploy a series of test-oriented designs to quickly meet the needs of the end user community.
Tools for success include Netezza, Oracle, SQLServer, DB2, DataStage, Informatica, SSIS/SSAS, Micro Strategies, Cognos, Business Objects.
IT Process Derivation, Implementation, and Management
We derive processes to make data work. We use an architectural framework to align business strategy with technologies, and provide continuous improvement to maintain the dynamic needs of business.
Business Process Management (BPM)
We use a model driven business analysis approach to visualize, construct, and document artifacts, and to derive patterns as well as feedback loops to drive application architecture and modeling.
Data Model Management Process
We define enterprise model repositories consisting of sub-models, standard naming domains, model change merging, capacity planning projections, data lineage exhibits, and metadata reporting to empower multiple architects to simultaneously build models based on a consistent standard approach.
Governance
We align data governance to proper BPM and Model Management processes to enforce corporate compliance requirements such as Basel or SOX, internal audit or legal, service quality measures and manage changes to the above as well as provide safeguards to protect corporate assets and proprietary processes.
Infrastructure Roadmap
We derive and manage infrastructure roadmaps relative to application delivery, system architecture, security, environment management, release management, SLA delivery, disaster recovery, pilot preparation, benchmarking, and business-as-usual transition.
Risk Adverse Engagement Methodology
We implement and iterative implementation process, baby-step approach, reduces risks and includes managing expectations, scope, communications, and education relative to design/deployment realities. Furthermore, define development / production transitions, release control, and service level agreement strategy.
|
|
|