Load

toward combining the information into the information stockroom from different sources is to be thought of. Extract Transform Load (ETL) procedures are basic in the achievement of the Data Warehousing ventures. The way toward extricating information from one source (extract), changing it as per the outline of the data warehouse(transform) and stacking it into data warehouse (load) constitute ETL. As it were, ETL is the way toward extracting information from different information sources, changes it according

This means that, by applying load shedding, damage to power systems is prevented. Load shedding restores power system stability (Feng, Ajjarapu & Maratukulam 1998). Disadvantages of Load Shedding If a load shedding program is poorly designed, it will be ineffective and can even worsen the stress load exerted on the supply leading to cascading disruptions (Concordia, Fink & Poullikkas 1995). Load shedding results in unsatisfied customers and loss of revenue for

increase in the number of terrorist attacks especially in the last few years has shown that the effect of blast loads on buildings is a serious matter that should be taken into consideration in the design process. Although these kinds of attacks are exceptional cases, man-made disasters; blast loads are in fact dynamic loads that need to be carefully calculated just like earthquake and wind loads. The use of bombs to attack the cities by terrorist organizations around the world. A bomb explosion within

Real-time PCR detection of HIV viral load Introduction: HIV, the Human Immunodeficiency Virus is a lentivirus which is responsible for HIV infection and eventually causes AIDS. It’s assumed that the virus has been in existence since 1930 but it’s still unclear that how the virus came into existence. There are two kinds of HIV virus, HIV-1 which causes more severe disease and the source of transmission is a chimpanzee species Pan troglodytes whereas HIV-2 is transmitted by Cercocebus atys, a monkey

Cognitive load theory intersects with human cognitive architecture by addressing working memory as limited to three to seven elements of information when the learning of new information is a requirement (Blissett, Cavalcanti, & Sibbald, 2012). Yet, where there is familiarity of information, both capacity and duration limits of working memory are eliminated (Paas & Ayres, 2014). Cognitive load theory introduces the prominence of cognitive schemas as a strategic approach toward the organizing and

bring the meaning that YSlow analyzes Groupon web pages is slow than ZALORA web page and why they're slow based on Yahoo!'s rules for high performance web sites. Then, page load for ZALORA website is 4.3 second which is faster than Groupon website which at 5.1 second. So that, ZALORA have higher ranking than Groupon because fast load times equal higher rankings and higher rankings also lead to more traffic. The total page size of ZALORA also less Groupon. The larger the the page size to download, the

• Various alternatives to load huge amount of data without ETL tool • Which type of skillset needed to work in organization as an ETL developer? Author will explore from Microsoft, Informatica and Oracle websites for more enhancements of the features. Spending quality time for this

for a data warehouse are: 1. Source Systems 2. Data Staging Area 3. Presentation servers The data travels from source systems to presentation servers via the data staging area. The entire process is popularly known as ETL (extract, transform, and load) or ETT (extract, transform, and transfer). Oracle’s ETL tool is called Oracle Warehouse Builder (OWB) and MS SQL Server’s ETL tool is called Data Transformation Services (DTS). A typical architecture of a data warehouse is shown below:

Improved system performance monitoring. • Data profiling enhancements. • Updated Look and Feel for Pentaho Data Integration. • Easily add new plugins. • Deliver data from multiple data sources. • New Embedded Analytics APIs for Analyzer. • Data movement load balancing. •

perspective. In previous versions of our software, we often stored the data relationally in Access, SQL Server, or Oracle. This forced us to have to execute expensive queries across large numbers of records that didn 't really relate to one another, load the data in some form of hierarchial structure either with ADO or COM object trees, work with the data, and then run expensive updates across myriads of records with varying data types. In a desktop environment, you can get away with the extra overhead