Data staging area

Incoming data from operational systems as well as those from external sources, collectively referred to as source systems, are stored in a data staging area. Several modules support the sorting, categorization, transformation, combination, and dereplication of data stored in the staging area to prepare them for use in the data warehouse. The data staging area does not provide any query or visual representation of data. 

The entire process of data transition from the source systems to presentation servers via the data staging area is usually referred to as extract, transform, and load (ETL). 

The data staging area stores the incoming data for subsequent aggregation by an ETF process. 

The data staging area is the data warehouse workbench. It is the place where raw data are brought in, cleaned, combined, archived, and eventually exported to one or more data marts. 

A practical constraint for data collection is the fact that a part of the site is currently used as a staging area for old equipment and is not available for sampling. There are also time constraints for the field season. Budgetary constraints require that the smallest possible volume of soil be removed due to a high cost of incineration of dioxin-contaminated soil. There are no practical constraints for data collection, although budgetary constraints exist. 

Metadata are extracted from the staging area they are used for producing summary tables, for query purposes, and to provide the data categorization to the end-user. 

Figure Bl.18.10. Scaimmg microscope in reflection the laser beam is focused on a spot on the object. The reflected light is collected and received by a broad-area sensor. By moving the stage, the object can be scaimed point by point and the corresponding reflection data used to construct the image. Instead of moving the stage, the illuminating laser beam can be used for scaiming.

Site Conditions. If the licensor s package is at the custom design stage, it is important to review the site conditions to be used in the calculations. Weather data is available for most proposed sites or at least for areas not far away. Decisions are necessary as to how to apply the weather data for example, w hether to use 95% or 99%... 

The main output from this stage is a detailed assessment of the human error problem areas. If possible this should include quantitative data on the incidence of errors and the significance of their consequences. This will provide a valuable baseline against which to evaluate the success of the error management program. 

The purpose for which the analytical data are required may perhaps be related to process control and quality control. In such circumstances the objective is checking that raw materials and finished products conform to specification, and it may also be concerned with monitoring various stages in a manufacturing process. For this kind of determination methods must be employed which are quick and which can be readily adapted for routine work in this area instrumental methods have an important role to play, and in certain cases may lend themselves to automation. On the other hand, the problem may be one which requires detailed consideration and which may be regarded as being more in the nature of a research topic. 

Mechanistic studies are particularly needed for the hydrolysis and polymerization reactions that occur in sol-gel processing. Currently, little is known about these reactions, even in simple systems. A short list of needs includes such rudimentary data as the kinetics of hydrolysis and polymerization of single alkoxide sol-gel systems and identification of the species present at various stages of gel polymerization. A study of the kinetics of hydrolysis and polymerization of double alkoxide sol-gel systems might lead to the production of more homogeneous ceramics by sol-gel routes. Another major area for exploration is the chemistry of sol-gel systems that might lead to nonoxide ceramics. 

---