<p>Ett datalager är ett beslutstödssystem som integrerar stora mängder data från interna och externa källor. Dessutom är datalagret subjektorienterat, vilket innebär att det är organsierat kring ett antal betydelsefulla affärsdomäner som företaget lagrar data om. Många menar att det börjar bli allt viktigare för företag att söka information utanför verksamheten. Detta kan göras genom att de externa affärsdomänerna skannas av på information.</p><p>Syftet med detta arbete är att ta reda på i vilken utsträckning i nuläget som organisationer lagrar data om affärsdomäner i sitt datalager. För att ta reda på detta har företag som använder datalager kontaktats och intervjuats.</p><p>Resultatet visar att företag lagrar data om externa affärsdomäner, fast i ganska liten utsträckning. Däremot visar resultatet att intresset för att lagra information om dessa externa affärsdomäner håller på att öka bland företag.</p>

<p>Integration of internal data is often mentioned in literature as the most demanding task when building or maintaining a DW. There is no literature that outlines the approach for the integration of external data into a DW. The integration of external data has increased during the last years enabling corporations to understand the opportunities in the market and to be able to better plan for future success of the corporation. The aim of this work is to exploratory outline current approaches for acquiring and integrating external data into DW and to give a brief overview of the future trends for external data integration. This aim was researched using an interview study. The results show that how to integrate external data is depending on what the corporations purpose with the external data is. Additional results show that how to integrate external data also depends on how the data is acquired.</p>

<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>

This thesis is written at the department of Business Studies at Uppsala University. The study addresses the differences in possibilities and difficulties of implementing business intelligence (BI)-systems among small IT-enterprises. BI-systems support enterprises in decision-making. To answer the aim of this thesis, theories regarding organizational factors determining a successful implementation of a BI-system were used. Theories regarding components of BI- systems, data warehouse (DW) and online analytical processing (OLAP) were also used. These components enable the decision-support provided by a BI-system. A qualitative study was performed, at four different IT-enterprises, to gather the empirical material. Interviews were performed with CEOs and additional employees at the enterprises. After the empirical material was gathered an analysis was performed to draw conclusion regarding the research topic. The study has concluded that there are differences in possibilities and difficulties of implementing BI-systems among small IT-enterprises. A difference among the enterprises is the perceived ability to finance an implementation. Another difference is in the managerial- and organizational support of an implementation, but also in the business need of using a BI- system in decision-making. There are also differences in how the enterprises use a DW. Not all enterprises benefits from the ability of a DW to manage complex and large amounts of data, neither from the advanced analysis performed by OLAP. The enterprises thus need to examine further if the use of a BI-system is beneficial and would be used successfully in their company.

Every day Internet sites collect and store lots of user data. For effective usage of that data, special tools are required. Online Analytical Processing (OLAP) tools are suggested for that purpose. Usage of these tools is related to usage of Data Warehousing tools. Therefore issues of Data Warehouse design, data transformation and transferring to data warehouses were discussed. In the present years there are new trends in business computer systems industry – WEB Data Warehouses. New characteristics of such systems were analyzed. OLAP tools usage is not possible without multidimensional data model. Main entities and operations with these entities were reviewed and mathematical definitions given. Data transformation process was proposed. This process flow shows how transformations can be used for transferring data from WEB site to multidimensional database. OLAP tools of Microsoft SQL server and Oracle database server (the most popular database management systems in Lithuania) were analyzed in experimental part of work. Data transformation and reviewing in desktop applications, WEB systems and office applications tools were compared and recommendations given.

This graduation paper researches the principles of Electronic collaboration systems. It overlooks what technologies ant methods may be used for better collaboration between business entities. Here is discovered the benefit of international classification of economic activities, products and services. This method of international classification is used in system we made-up and it’s defining the structure of catalogs. Also we overlooked the possibility to use data warehouse system which may by applied for direct customers data bases integration with confederate system. System project was build using two CASE technologies. User requirements and demands represented using UML specifications, final systems specifications phase was build using Oracle Case tools.

Growing amount of data and needs of data analysis starts needs of data warehouses. A lot of organizations operational data cumulates in OLTP DBMS databases. Organization historical data are cumulating in data warehouses. These data are adjusted for data analysis. DBMS ETL tools don’t have good data warehouse building opportunities. Created ETL tool for MS SQL Server makes data warehouse building process easier and speedier.

Šis darbas apima vaistinių tinklo klientų duomenų analizės modelio sudarymą ir sukūrimą. Kuriant ir projektuojant duomenų saugyklas, susiduriama su įvairiomis problemomis. Viena didžiausių ir daugiausia laiko užimančių duomenų saugyklų projektavimo ir kūrimo problemų – tai duomenų išgavimas iš esamų sistemų ir jų perkėlimas į analizės sistemas (ETL procesas). Analizuojamoje įmonėje naudojama Oracle duomenų bazė darbiniams duomenims saugoti. Tačiau kuriant duomenų saugyklą, buvo palygintos technologijos ir pačiai saugyklai realizuoti pasirinktos Microsoft SQL Server priemonės. Duomenų saugykla yra skirta vaistinių tinklui, kur be tradicinių pardavimų duomenų, yra ir tik farmacijoje naudojami duomenys (kompensuojamųjų vaistų receptai, draudimo nuolaidos ir pan.). Darbo metu sukurtas OLAP analizės kubas, apimantis vaistinių tinklo pardavimų, nuolaidų kortelių panaudojimo duomenis. Tai leidžia įmonės analitikams efektyviau analizuoti klientų įpročius, paklausiausias prekes ir pasiūlyti klientams tinkamiausius sprendimus, išlaikant esamus klientus ir pritraukiant naujus. Darbo metu realizuotas analizės kubas, nustatyti jo atnaujinimo intervalai, ištestuotas bendras sistemos veikimas. Taip pat nustatytos pagrindinės duomenų saugyklų projektavimo, realizavimo problemos. / This work investigates Pharmacy Data Warehouse model and practice. The development and design of data warehouse is faced with various problems. One of the biggest and most time consuming data warehousing design and development issues - is the data extraction from existing systems, transformations and load (ETL process) to target systems. Analyzed company uses Oracle database as operational data store. Examination of the current situation, the technical base, for the implementation of the data warehouse is selected the Microsoft SQL Server 2000 Analysis Services tools. Because these tools already exist in the company, thus reducing the overall costs needed. During this work is realized the cube of Pharmacy customers analysis, tested overall system performance, in addition, an example schedules for cube updating are created. This enables the analysts to more effectively analyze customer behavior, sales and offer customers the most appropriate solutions, while retaining existing customers and attracting new ones.

Veiklos analizavimas bei sprendimų priėmimas labai svarbus šiandieninėje įmonių veikloje. Norėdamos atlikti veiklos statistinę analizę, įmonės perka brangius ir sudėtingus produktus nesigilindamos apie tų produktų nauda įmonės veikloje. Vienas iš sprendimo būdų kaip efektyviai atlikti statistinę duomenų analizę neinvestuojant didelių resursų – naudoti standartines DBVS statistines priemones. Šiomis priemonėmis įmonės gali atlikti įvairią statistinę analizę kasdienėje veikloje naudojant statistinės analizės metodus: linijinę regresiją, koreliacijos analizę, nuspėjamąją duomenų analitika, Pareto analitika, Chi kvadrato analitika, ANOVA. / This work reviews advantages and disadvantages of existing statistical analysis tools usage for small and mid sized enterprises, explores usage of statistical analysis of enterprise data in data warehouse, reviews integrated statistical analysis functions in existing database management systems and integrated graphical software for graphical statistical analysis usage. In this work were analyzed Oracle, Microsoft SQL Server and DB2 DBMS. The new statistical analysis solution was offered. This solution allows statistical analysis of existing data using integrated statistical functions of the database management systems and integrated graphical tool. Proposed solution has been designed and realized for the statistical analysis of insurance company‘s data. Oracle DBMS was selected for statistical analysis, because this DBMS is used by insurance company. Oracle has a large number of integrated statistical analysis functions; it ensures more diverse and rapid analysis. Graphic depiction of the selected Oracle Discoverer tool to optimally exploit data analysis potential of Oracle DBMS. The proposed statistical analysis process is versatile and suitable for different business areas and can be applied to other DBMS, which has an integrated analytical functions and graphical tools for the results display.

Universiẗat, Master-Thesis--Leipzig, 2006.