Business Intelligence and Data Visualization Analysis 2022

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23 September 2022
Business Intelligence and Data Visualization
Task D (20%)
Importance and need for the ETL process
Generally, ETL is defined as the actions taken to extract data from a given source system
and upload it into the data warehouse and it is abbreviated from data extraction,
transformation, and loading. However, ETL also entails transporting datasets.
As much as ETL methods and tasks have been in existence for several years, hence it is
not a unique aspect to data warehouse environments. On this note, ETL borrows a lot
from the IT sector while using several database packages given that data sharing is
between systems or applications by integrating data to give different pictures to the view
of the world.
To enhance business analysis regularly, data responsible persons are expected to ensure
that the data is loaded into the warehouse for it to meets its desired goals in decision-
making processes, (Molina-Solana, et, al, 2017). This is only possible when data from
different sources are extracted and copied in any given data warehouse. However, one of
the limitations that have been witnessed overtime in the warehouse is the integration,
rearrangement and consolidation of large datasets within the systems hence the provision
of information base which is unified for business intelligence.
Besides, extracting data occurs when the data points of interest from several sources are
normally extracted together with the database systems and other applications, (Leskovec,
Rajaraman, & Ullman, 2020). To note, specific data of interest may not be extracted but
instead, several data points are extracted so that the identification of data points desired is
done at a later stage. During data extraction, some data transformation may also take
place in the process, but this is the high dependence of the operating system resources.
Also, based on the business size, extracted data can have a variation in its size ranging
from hundreds of kilobytes up to gigabytes. Similarly, the process of extracting data may
also vary in terms of time taken ranging from days/hours and minutes to near real-time.
On the same, the log files for different Web servers may also increase to hundreds of
megabytes within a short period.
Before data preprocessing can take place, it must be transported after extraction to
systems of the target. Consistently, some data transformation can also occur during data
transportation. For instance, using SQL statement which in one way or the other access
data from a remote target system through different gateways and in the process
concatenates two columns as part of the SELECT statement, (Spyker, Szabo, & Yao,
2019).