Our team have many years of experience in developing data warehouse applications, with strong understanding of data modelling, data warehouse architectures and database performance.
We work with all our Clients to design, tune and/or manage their data warehouse platform to ensure it delivers the performance and flexibility you need to support the business, regardless of the analytics technology they use.
If you are looking for help in procuring a data warehouse platform, we have access to some of the most advanced data warehousing capability in the industry.
WHY DATA WAREHOUSE:
- Make unstructured data and transforming it into relevant information
- Provide business users by providing the tools required for custom querying, reporting and data extraction
- Better decisions due to quick access to information; trend analysis and support of critical business intelligence initiatives.
- Tighter security and enhance control of the data.
- All reporting manual processes will be moved to the Data Warehouse; allowing resources to focus on analysis rather than transactional issues.
- Elimination of a significant amount of manually created Excel spreadsheets and manual reconciliations
- Establish a “single source” for data that users can access easily.
At RPL, we understand how to develop high performance data warehouse applications, underpinned by a fundamental understanding of data modeling, data warehouse architectures and database performance. We work with our Clients to design, tune and/or manage your data warehouse platform to ensure it delivers the performance and flexibility you need to support the business, regardless of the analytics technology Clients use.
WE ARE EXPERTS AT - COLLECTING, ORGANIZING, AND STORING DATA FOR ANALYTICAL PROCESSING
Data Analysis is one the most important step in data warehousing and how the data flows through the warehouse and integrates with the other data sources. RPL has a proven methodology for data cleansing and building an efficient process to identify the right data sources for integration. Our profiling and data quality solutions specialize and focus on ensuring that the data in the warehouse is accurate and consistent. The following three constitute the backbone of BI:
A business representation of data for end users
- A user-friendly, Web-based environment that gives the customers and corporate employees query, reporting, and analysis capabilities
- A single, server-based data repository—a data warehouse (DW)—that allows centralized analysis, security, and control over the data
THERE ARE 5 MAIN COMPONENTS OF DATA WAREHOUSE ARCHITECTURE:
- Extract-Transform-Load (ETL) tools, brings data from diverse sources together in a single, accessible structure, and load it into the data mart or data warehouse.
- The typical ETL based data warehouse uses staging, data integration, and access layers
- Staging Server: The staging database holds the extracted raw data from the source applications for further processing prior to loading into the data warehouse. Multiple staging databases can be defined and created and split in terms of specific business areas
- Integration Layer: integrates the unrelated data sets by transforming the data from the staging layer and storing this transformed data in an operational data store (ODS) database.
- The integrated data is then loaded into the data warehouse database.
- Each step within the extraction, transformation and load process will include error handling to ensure that errors do not make it down to the data warehouse.
- Data sources
- ETL Tool
- Data Warehouse server
- OLAP CUBES
- Data Mining / Reporting Tools