A Viable Solution For Improving It Response

Published Date: 02 Nov 2017

As a result of increasing volume of information needs of organizations the need to handle accurate information that could be retrieved at the time of need has become a necessity.

Enterprise quality improvement requires information from many departments within an organization, such as production, quality assurance, customer service, accounts, and purchasing (Klenz & Fulenwider, 1999).

The information must be made available at anytime it is required for management decision making. All the various functions of an organization generate information in their respective business processes and such information is not only needed by them but also other departments as well. For example, information generated by Accounts is not only needed by the accounts manager and his staff but also all the other functions who may need such information for decision making.

To ensure better and faster decisions, management must have access to all information needed on time. Untimely retrieving of information affects the quality or value of such information.

To constantly provide information to management for decision making, Data Warehouse is presented as a key technology for continued quality improvement.

This paper discuses the improvement in the response of Information Technology (I.T.) in providing strategic information for management decision through a Data Warehouse.

Reasons for the problems

Organizations have large volumes of data which constantly collected when every transaction is made. The data generated is at the core of the systems that run the organization and this ensures databases to be designed to process such data as efficient as possible. These transactional systems are not without challenges.

According to the white paper; the benefits of data modelling in data warehousing (2008) by CA technologies, the following challenges are associated with using transactional systems for business reporting:

The database design that is required for reporting is very different from the design that is required to optimize the performance of transactional systems.

Running reports against mission-critical transactional systems slows their performance, negatively affecting the systems that run the organization.

Data that is stored in a transactional database system is not centralized; there is no single source of information against which reports can be generated.

A way to solve these problems is create a data warehouse that is designed specifically with business reporting in mind, and contains all of the relevant information for reporting.

Data Warehouse

Data Warehouse is a technology that is designed to facility analytical processing on data from disparate sources (Klenz & Fulenwider, 1999).

Data Warehouse concept is the notion of creating a permanent storage space for the data needed to support reporting, analysis, and other Business Intelligence (BI) functions (Guerra & Andrews, 2011).

Data warehouses (DW) are centralized data repositories that integrate data from various transactional, legacy, or external systems, applications, and sources. The data warehouse provides an environment separate from the operational systems and is completely designed for decision-support, analytical-reporting, ad-hoc queries, and data mining (Bi-Insider.com, 2011)

In challenging times good decision-making becomes critical. The best decisions are made when all the relevant data available is taken into consideration. The best possible source for that data is a well-designed data warehouse. Having immediate access to current, actionable information can make a huge difference.

Data warehouse store all of the organization’s data in a form that prioritizes query performance, rather than transactional performance or storage volumes. Through data warehouse, information about any part of the organization, and how these entities relate to performance metrics or other entities can be accessed.

According to Guerra and Andrews (2011), the following are the key features of data warehouse:

It resides on computers dedicated to this function

Runs on a database management systems (DBMS) such as those from Oracle, Microsoft, or IBM.

Retain data for long periods of time.

Consolidate data obtained from many sources.

Are built around a carefully designed data model that transforms production data from a high speed data entry design to one that supports high speed retrieval.

Data is obtained from each appropriate source by the tool called an Extract, Transform, and Load (ETL) software. These ETL tools read data from each source application, edit it, assign easy-to-understand names to each field, and then organize the data in a way that facilitates analysis.

Data Warehouse and Business Intelligence (BI) have some connections. The Data Warehousing Institute defines business intelligence as:

The process, technologies, and tools needed to turn data into information, information into knowledge, and knowledge into plans that drive profitable business action. Business intelligence encompasses data warehousing, business analytic tools, and content/knowledge management.

Benefits of Data Warehouse

Data Warehouse Enhances Business Intelligence

Data Warehouse makes managers free from making decisions based on limited data. Thus, decisions that affect the strategy and operations of organisations will be based upon credible facts and will be backed by evidence and actual data of the organisation. Decision makers are able to query actual data well, retrieve information based on their personal needs. Also data warehouse and its related business intelligence can be used to apply directly to business processes including marketing segmentation, inventory management, financial management and sales.

Ad hoc reporting and analysis

Since the data warehouse eliminates the need for BI tools to compete with transaction processing, users can analyse data faster and generate reports more easily. The tools that come with BI systems also tend to vastly improve the analysis function.

Support for operational processes

The creation of sound BI infrastructure is often the best way to meet certain ongoing business needs. The most common example is to facilitate the consolidation of financial results within complex organisations, especially those who divisions use different software systems.

Timely Access to Data

The data warehouse enables businesses and decision makers to have access to data from many different sources as they need to have access to such data. Little time is spent in the data retrieval process. The system uses scheduled data integration routines known as ETL which is leveraged within a data warehouse environment to consolidate data from multiple source systems and transform the data into a useful format.

Drill down capability

The leading BI systems all allow users to drill down into the details underlying the summaries in reports and dashboards. The presence of a data warehouse makes it practical to use this capability as much as needed. Without one, places the burden on user’s access to application data.