Warehousing Solutions

On the surface, the storage and organization of data seems like a relatively simple process. However, increasingly massive and diverse amounts of data are being used by companies everyday, and as a result many outdated systems cannot integrate or retrieve their information efficiently. A Data Warehouse is an information databases that holds all or most of the information that a business system uses. The goal of Data Warehousing is to efficiently store, integrate and access a diverse range of business intelligence. We gather collections of data across an entire enterprise designed to support management decision-making by presenting a picture of business conditions at a single point in time. RemoteTech can offer data warehousing solutions that will:

  • Provide on-site business / technical needs assessment
  • Develop onsite systems integrating remote storage systems and local
  • Reduce the time and cost expenditure involved in data retrieval
  • Provide the means for accurate business forecasting by facilitating the access and organization of recorded trends
  • Provide development and integration assistance, including assistance with Legacy Applications and Enterprise Resource Planning
  • Provide Data Mining and Online Analytical Processing

 

 

RemoteTech Standards

At RemoteTech we understand that it's important to supply not only the latest technological advancements, but also the results from that technology. As well as defining specific results as a contract stipulation, RemoteTech uses a systematic archetype to ensure the achievement of CMM level 5 standards. User feedback and participation is a fundamental aspect at all levels of our archetype for Data Warehouse Development. To create a Data Warehouse it is first necessary to compare business requirements with the information it is necessary to extract to meet those requirements. The various sources of all the information required are then mapped, and a model of how the Data Warehouse will analyze, process and reorganize that information is then created. Then after it has been ensured not only that the Data Warehouse can access all necessary information, but that it has mapped all the possible information reference paths to meet your full business requirements is an Operational Data Warehouse model created. Once the Operational Data Warehouse is implemented, all developments in user business requirements, user feedback and application implementation are monitored in anticipation of future updates to the Data Warehouse.

 

Data Mining and OLAP

Data Mining is one of the more advantageous aspects of Data Warehousing. Data Mining consists of finding algorithms and relations between various information sources in the Data Warehouse. In other words, it is locating and cross referencing all relevant relationships between pieces of data in the Data Warehouse. This includes:

•  Documenting events or statistics that predictably lead to another.

•  Identifying and recording similarities in groups of information previously thought to be unrelated

•  Using newly documented information to predict future data trends

 

This massive documentation of all relevant data, and the relationships between that data lead to Online Analytical Processing (OLAP), computer processing that allows the user to access related information. This might allow a user to access and compare sales information from two different months of two different years, or to compare that same sales information with sales trends in different regions.

 
 
 
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