
Data Warehousing – Advantages and Disadvantages
Data Warehousing
A
data warehouse is a collection of data aimed at a specific area
(company, organization, etc.), integrated, non – volatile and variable
over time, which helps decision making in the entity in which it is
used. It is used for reporting and data analysis and is
considered a fundamental component of business intelligence . It
is, above all, a complete file of an organization, beyond transactional and
operational information, stored in a database designed to favor the efficient
analysis and dissemination of data (especially OLAP , online
analytical processing ). The storage of the data should not be used
with current usage data. Data warehouses often contain large amounts of
information that are sometimes subdivided into smaller logical units depending
on the subsystem of the entity they come from or for which they are needed.
Function of a data warehouse
In
a data warehouse what is wanted is to contain data that are necessary or useful
for an organization, that is, that is used as a repository of data to
later transform them into useful information for the user. A data
warehouse must deliver the correct information to the right people at the right
time and in the right format. The data warehouse responds to the needs of
expert users, using Decision Support
Systems ( DSS ), Executive Information
Systems ( EIS ) or tools to make queries or reports. End
users can easily make inquiries about their data warehouses without touching or
affecting the operation of the system.
Data
warehouses are relational databases that act as data analysis tools,
aggregating data from multiple departments of a business into one data store.
Data warehouses are typically updated as an end-of-day batch job, rather than
being churned by real time transactional data. Their primary benefits are
giving managers better and timelier data to make strategic decisions for the
company. However, they have some drawbacks as well. Being a subject-oriented,
integrated, time-variant and volatile, data warehousing caters several
advantages to enterprises and users when implemented for business purposes. The
successful application of DWH delivers great results and improves the overall
functioning of every organization.
Periodically,
data is imported into the data warehouse of the different resource planning
systems of the entity ( ERP ) and other software systems related to the
business for further processing. It is common practice to normalize the data
before combining it in the data warehouse using extraction, transformation and
loading ( ETL ) tools . These tools read the primary data (often OLTP databases
of a business), perform the transformation process to the data warehouse
(filtering, adaptation, format changes, etc.) and write to the warehouse.
Advantages
of Data Warehouse
Delivers Enhanced
Business Intelligence: With data
warehousing techniques and processes, data can be accessed and
analyzed from multiple sources. Thus, the data is not limited to any specific
section, which benefits business people to make improved and intelligent
business decisions. The data warehouse and related BI processes can also be
directly implemented in inventory management, financial management, sales and
marketing.
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Ensures Data
Quality and Consistency: Data Warehousing supports
data conversion into a common and standard format. The standardization of data
and output lets multiple departments of an organization to produce commensurate
and well-formed results with no discrepancy from any end. Hence, businesses can
run with higher accuracy and consistency, generating persistent and dependable
employment decisions.
Saves Time and
Money:
Keeping all the data in one place certainly saves user’s time to access a
specific set of data. They can make rapid decisions on key enterprise actions
as enterprises do not spend extra time in analyzing the unordered data from
multiple sources.
A data warehouse execution does not require much of IT support and does not
even involve a higher number of channels , thereby ensuring cost-effectiveness.
Similarly, the business executives interested in querying data won’t wait for
the other IT processes to work before any data retrieval. The business continue
to run every time and anytime, without any time lag or reliance on external
sources.
Tracks
Historically Intelligent Data: Since DWH is known for storing
historical data, it keeps users and enterprises updated about the conventional
customs and trends changing with time. So businesses can track data in
different time periods and proceed likewise in the future. This also allows
organizations to gain a competitive edge over others.
Generates high ROI: As per reports
by IDC, companies that have invested in data warehousing implementation
and related BI systems generated a higher revenue and saved incredibly on
each of the business models and processes.
Disadvantages
of Data Warehousing
Extra Report Work:
Unquestionably, the bigger the organization, the more data it holds and the
extra time and load the data warehouse runs. The data generated by DWH requires
the involvement of each department in the organization and thus, bothers with
extra report work. Many times, it also involves data from consumers and
clients, which again causes annoyance and trouble of entering excessive data.
Inflexibility and
homogenization of data: As discussed above in the benefits section,
sometime the similarity and standardization in the data formats lead to
inflexibility and homogenization of data. This further limits the data in terms
of establishing relations during aggregation and difficult to tune for query
speed. Meanwhile, the homogenization also causes loss of data.
Ownership Concerns: While
warehousing is all about centralizing data at one place for the ease of
analysis and access. It sometimes causes issues to different departments as
they hesitate to share their personal data within a central repository. This
also raises security and ownership concerns for few departments. In this case,
organizations must ensure that the analysis of data is given to trusted
individuals within the enterprise.
Demands for large
amounts of resources: If not IT support, but data warehousing
implementation certainly requires large
amounts of data resources
to manage and handle data from multiple sources. This, in turn, raises cost
concerns and cost/benefit ratio for the companies. Nonetheless, businesses can
choose to execute it wisely by optimizing their costs yet generating best
results.
Hidden issues
consume time:
Sometimes, internal sources fueling the data warehouses keep bundling issues
that are undetected for years. For instance, while entering customer data, some
values field accept null values, which may result in incomplete customer data
in the future, even if the data is available.
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