Data Warehouse
Data Warehouse practice looks at an enterprise level data architecture related issues. Data Warehouse practice looks to find solutions for large scale enterprise wide data storage and retrieval issues.
Bottom line: Are the enterprise stored in a secure and efficient manner and are business users served up the necessary data with ease?
Data Warehouse Lifecycle Services
Many organizations find themselves in need of rapid deployment of a data warehouse system. IBS Data Warehouse experts will provide "end to end" solutions to your BI system needs. Our team will partner with you to closely examine the needs of your business; identify sustainable BI solutions; select and implement appropriate infrastructures, tools and technologies; and design, implement and deploy high impact BI systems. Most importantly, we teach your team, each step of the way, to be self-sufficient in sustaining the system and in building further iterations. As part of IBS Data Warehouse solution we will deliver a successful, sustainable "turn-key" data warehouse project offering, we provide all the elements required for the organization to understand what it needs to accomplish, the known risks, the best route to success and the tools for the team to achieve that goal.
Deliverables
Assessment of your data warehousing readiness and capabilities
Detailed examination of business "pain" through user interviews and analysis
Development and ranking of project/phase candidates
Development of a detailed scope statement
Development of a user training methodology, plan and process
Vendor facilitation to evaluate and select Extraction, Transformation and Load (ETL) and end user Access tools, as well as other required tools and technologies (servers, data quality tools, system monitoring tools, etc.)
High level analysis of source systems and desired targets
Development of logical and physical models to support the transformation from an operational to informational model
Replication and distribution of the data to a subset data mart(s) / incremental architected data mart(s)
Development and implementation of a meta data repository system
Development and implementation of "Worst Case," automated processes to support all data and meta data functions
Implementation of system monitoring tools
Education and mentoring of team members · A library of relevant data warehousing, database and systems administration books
Development and implementation of business value / system success metrics and measurement methodology
Development and implementation of a library/repository of all project documents, processes and methodologies
Implementation Strategy
IBS Data Warehousing practice implements systems via a phased approach, leveraging knowledge transfer to key users, the development of best practices among users, and site-specific end user training. Our implementation methodology includes:
Multi-phase pilot to develop and test all system processes
Site specific training and data sets
Best Practices proliferation & sharing
User driven interaction and support
Robust, scaleable change and growth processes
Documentation
Documentation is provided for all project activities, including, but not limited to:
Readiness assessment
Business "reality check" assessments
Logical models
Physical models
Server scripts
ETL processes
Data replication and distribution processes
"Worst case" data flow processes
End user Access and Analysis systems
Methodologies
Business value metrics/assessments
Data Mining
Data mining practice looks at enterprise level information harvest, repurposing, reporting, and recovery related issues. Data mining practice looks to find solutions for both numeric data mining as well as text mining related problems of an enterprise. Within this practice mainly vendor recommendations, product evaluations as well as trouble shooting, and setting up a mining shop related consultations will be performed.
Bottom line: Are the business decision makers served up the necessary data to run their operations?
