Rouse (n.d.) described data
warehousing as a federated repository for all the data that an enterprise’s
various business systems collect, it emphasizes the capture of data from
diverse sources for useful analysis and access, but does not generally start
from the point-of-view of the end user who may need access to specialized,
sometimes local databases but the latter idea is known as the data mart. In a
discussion of Oracle about Oracle9i Data Warehousing Guide, a data warehouse is
a relational database which is designed for query and analysis rather than for
transaction processing. It contains historical data derived from transaction
data, but it can include data from other sources. It separates analysis
workload from transaction workload and enables an organization to consolidate
data from several sources.
Approach. Sampagar (2016) explained the steps
that are involved in a top-down approach. The first step is to extract the data
from the various source systems then, extracts will be loaded and validated in
the stage area. The validation is required to make sure the extracted data is
accurate and correct. ETL tools can be used to extract and push to the data
warehouse. The second step is to extract the data from the data warehouse on a
regular basis in the stage area. At this step, various aggregations,
summarization techniques should apply to extracted data and loaded back to the
data warehouse. Lastly, once the aggregation and summarization are completed,
data extract from various data marts and apply some more transformation to make
the data structure as defined. Below diagram depicts how the Bottom-up approach
Figure 1. Top-down Warehousing
Approach. Bottom-up Data Warehouse which is
also called dimensional modeling or the Kimball methodology. Sampagar (2016)
also explained the steps that are involved in a bottom-up approach. The first
step is the extraction of data from the different source system into the stage
area where it is processed and loaded into the data marts since the data flow
in the bottom-up approach starts at the source systems. After data marts are
refreshed the current data is extracted once again in the stage area,
transformations are applied to create data into the data mart structure. The data is then extracted from Data Mart to
the staging area then the data will be aggregated, summarize and lastly, loaded
into EDW and then made available for analysis of the end users. The below
diagram depicts how the top-down approach works.
Figure 2. Bottom-up
LogiAnalytics (2017) defined reporting in two things;
reporting is the art of collecting data from various data sources and
presenting it to end-users in a way that is understandable and ready to be
analyzed; the other meaning is presenting data and information allowing
end-users to see and understand the data, as well as act on it.
Akrani (2010) stated the report is a systematic
presentation of ascertained facts about a specific subject; it is also the
summary of findings and recommendations about a particular problem. In similar,
according to Nordquist (2017), it is organized around concisely identifying and
examining or findings from a research investigation.
Report in Business. Perez (n.d.) said that
business reports are an integral part of actively managing any company, the
business uses the reports to track progress toward its various goals, control
expenditures and increase revenue; it also helps to predict trends, and this is
an advantage toward increasing profits.
In stocks and share, trading charting is a tool or system that is
very useful to the investors and money managers, this allows them to chart the
progress of stock or share overtime (SafetyNet Systems Ltd., n.d.) Folger
(2017) said charts are a trader’s window to the markets nowadays, with so much
data available, it is essential to use well-designed charts that enhance, and
not hinder the view of the market.
Control Chart. A control chart is used to monitor a process variable over time.
That variable can be in any type of company or organization – service,
manufacturing, non-profit and, healthcare. It provides a picture of the process
variable over time and visualizes the type of the current situation of
variation as it moves forward with continuous improvement. This understanding
of variation is the key to using control charts effectively (McNeese, 2011).
Structure Chart. Dontigney (2017) explained the purpose of a structure chart; it is
to provide a basic, graphical representation of a more complicated organization
or process. In addition, as a business grows in size, it also grows in
complexity — in terms of both the organization and the types of projects it
undertakes. This increasing complexity makes it progressively more difficult to
convey the organizational structure of the business and to manage project
elements (Dontingney, 2017).