<p>A data warehouse is a data collection that integrates large amounts of data from several sources, with the aim to support the decision-making process in a company. Data could be acquired from internal sources within the own organization, as well as from external sources outside the organization.</p><p>The comprehensive aim of this dissertation is to examine the current usage of external data and its sources for integration into DWs, in order to give users of a DW the best possible foundation for decision-making. In order to investigate this problem, we have conducted an interview study with DW developers.</p><p>Based on the interview study, the result shows that it is relative common to integrate external data into DWs. The study also identifies different types of external data that are integrated, and what external sources it is common to acquire data from. In addition, opportunities and pitfalls of integrating external data have also been highlighted.</p>

<p>Data warehouses (DWs) have become one of the largest investments in the past years for organisations, and incorporating external data into a DW can give organisations huge possibilities. Organisations that successfully manage to incorporate external data into a DW have an advantage over those who do not, but there are problems with incorporating data acquired from outside the organisation, and there is a lack of research aimed at these problems. The comprehensive aim of this dissertation is to characterise and categorise problems with incorporating external data. The available literature was scanned to find problems and an interview study was conducted to validate the problems found in the literature. Respondents from five well-known organisations in Sweden participated and the result is a list of problems backed up by both literature and empirical findings</p>

A data warehouse is a data collection that integrates large amounts of data from several sources, with the aim to support the decision-making process in a company. Data could be acquired from internal sources within the own organization, as well as from external sources outside the organization. The comprehensive aim of this dissertation is to examine the current usage of external data and its sources for integration into DWs, in order to give users of a DW the best possible foundation for decision-making. In order to investigate this problem, we have conducted an interview study with DW developers. Based on the interview study, the result shows that it is relative common to integrate external data into DWs. The study also identifies different types of external data that are integrated, and what external sources it is common to acquire data from. In addition, opportunities and pitfalls of integrating external data have also been highlighted.

Organisations today are working in an increasingly competitive environment where business success rests on the ability to make high quality decisions. Consequently, comprehensive knowledge about the organisation itself as well as the market in which it operates is required. Data warehouse (DW)-based business intelligence (BI) solutions can fulfil this need by integrating data from internal and external sources to provide useful insights that will assist organisational key-players in their decision-making. The specific incorporation of syndicate data (which is a type of external data) is particularly important because it enriches data content and maximises its full value. Although previous research strongly indicates that supplementing internal data with SD enhances the decision capabilities of an organisation and gives it a competitive edge in the marketplace, the literature on SD incorporation itself is of a very limited scope. Therefore, the aim of this work is to explore current practices in SD incorporation into DW-based BI solutions. A questionnaire study on the identification, acquisition, integration and usage of SD was conducted with BI consultants. Besides confirming that SD integration into DW-based BI solutions is common, the results also provide insights on how to identify SD suppliers, different data acquisition approaches, data distribution methods, integration approaches, types of SD, and SD application areas that are being used. Propositions for future work, which will extend the findings accounted for in this work, are also included.

Data warehouses (DWs) have become one of the largest investments in the past years for organisations, and incorporating external data into a DW can give organisations huge possibilities. Organisations that successfully manage to incorporate external data into a DW have an advantage over those who do not, but there are problems with incorporating data acquired from outside the organisation, and there is a lack of research aimed at these problems. The comprehensive aim of this dissertation is to characterise and categorise problems with incorporating external data. The available literature was scanned to find problems and an interview study was conducted to validate the problems found in the literature. Respondents from five well-known organisations in Sweden participated and the result is a list of problems backed up by both literature and empirical findings

<p>Most organizations are exposed to increasing competition and must be able to orient themselves in their environment. Therefore, they need comprehensive systems that are able to present a holistic view of the organization and its business. A data warehouse (DW) may support such tasks, due to its abilities to integrate and aggregate data from organizationally internal, as well as external sources and present the data in formats that support strategic and tactical decision-makers.</p><p>Traditionally, DW development projects have focused on data originating from internal systems, whereas the benefits of data acquired external to the organization, i.e. external data, have been neglected. However, as it has become increasingly important to keep track of the competitive forces influencing an organization, external data is gaining more attention. Still, organizations are experiencing problems when incorporating external data and these hinder the organizations from exploiting the potential of external data and prevent them to achieving return on their investments. In addition, current literature fails to assist organizations in avoiding or solving common problems.</p><p>Therefore, in order to support organizations in their external data incorporation initiatives, a set of guidelines have been developed and contextualized. The guidelines are also complemented with a state of practice description, as a means of taking one step towards a cohesive body of knowledge regarding external data incorporation into DWs. The development of the guidelines, as well as the establishment of a state of practice description, was based upon the material from two literature reviews and four interview studies. The interview studies were conducted with the most important stakeholders when incorporating external data, i.e. the user organizations (2 studies), the DW consultants, and the suppliers of the external data. Additionally, in order to further ground the guidelines, interviews with a second set of DW consultants were conducted.</p>

Most organizations are exposed to increasing competition and must be able to orient themselves in their environment. Therefore, they need comprehensive systems that are able to present a holistic view of the organization and its business. A data warehouse (DW) may support such tasks, due to its abilities to integrate and aggregate data from organizationally internal, as well as external sources and present the data in formats that support strategic and tactical decision-makers. Traditionally, DW development projects have focused on data originating from internal systems, whereas the benefits of data acquired external to the organization, i.e. external data, have been neglected. However, as it has become increasingly important to keep track of the competitive forces influencing an organization, external data is gaining more attention. Still, organizations are experiencing problems when incorporating external data and these hinder the organizations from exploiting the potential of external data and prevent them to achieving return on their investments. In addition, current literature fails to assist organizations in avoiding or solving common problems. Therefore, in order to support organizations in their external data incorporation initiatives, a set of guidelines have been developed and contextualized. The guidelines are also complemented with a state of practice description, as a means of taking one step towards a cohesive body of knowledge regarding external data incorporation into DWs. The development of the guidelines, as well as the establishment of a state of practice description, was based upon the material from two literature reviews and four interview studies. The interview studies were conducted with the most important stakeholders when incorporating external data, i.e. the user organizations (2 studies), the DW consultants, and the suppliers of the external data. Additionally, in order to further ground the guidelines, interviews with a second set of DW consultants were conducted.

<p>External data is data that a company could acquire outside their internal systems. This external data could bring another dimension for the companies, and allow them to further understand the environment. External data incorporated into a data warehouse makes it possible to exploit a number of application areas. The comprehensive aim of this dissertation is to outline what application areas that companies exploits today and what the future will bring. To achieve this, an interview study among people working with external data and DWs have been conducted.</p><p>Based on the information gathered through the study, the most common application areas are address updates, credit information, and marketing. Some smaller application areas have also been identified. A discussion on what application areas that will come in the future, are also to be found.</p>

External data is data that a company could acquire outside their internal systems. This external data could bring another dimension for the companies, and allow them to further understand the environment. External data incorporated into a data warehouse makes it possible to exploit a number of application areas. The comprehensive aim of this dissertation is to outline what application areas that companies exploits today and what the future will bring. To achieve this, an interview study among people working with external data and DWs have been conducted. Based on the information gathered through the study, the most common application areas are address updates, credit information, and marketing. Some smaller application areas have also been identified. A discussion on what application areas that will come in the future, are also to be found.

Information is the key for managers to make well-informed decisions. In recent years, technological advancements have been developed which made it possible for organizations to store and manage large quantities of data. Business intelligence is used to structure and narrow down data in order to acquire relevant information which could assist managers. BI is formed by a variety of systems and concepts which are interconnected and can work simultaneously. Furthermore, it was found that there are claims implying that BI can assist in the decision making of an organization. The following research will focus on how does business intelligence does that, with a specific emphasis on marketing managers working on large business-to-business organizations. Following a qualitative research with an exploratory approach, comparing relevant literature with the results obtained from ten performed interviews. Where it was observed how BI helps managers through providing useful and selected information.