The aim of this thesis is to implement Business Intelligence solution in the investment banking sector. The first part of this thesis is focused on general use of Business Intelligence in the banking sector and future developments in this area. Further it defines the objectives and reasons for the implementation of BI in the areas of investment banking. This part also explains basic terms used in investment banking which occur in the thesis and introduces a project in which the Business Intelligence is implemented. The second part focuses on determination of requirements and their analysis from which the data warehouse design is derived. Another part deals with the implementation of the designed data warehouse and ETL packages for loading the data. Further the tool in which the reports are created is described by exemplary implementation of the reports. In the last part of this thesis the implemented BI solution is evaluated by the users.

This thesis focuses on developing methodics for performance comparison of data warehouse systems. Firstly, the thesis defines data warehouses in various development stages of organization BI and describes knowledge about data warehouses. Methodics developed in the thesis describes architecture of standardized data warehouse, data flow between areas of data warehouse and processes in data warehouse. Understanding of these concepts is crucial for assurance of methodics applicability. Methodics offer logical progression of steps, which start and include testing of data warehouse systems. The contribution of the thesis is in having guide, what needs to be done when organization must do while testing various systems for data warehouses. Also it describes how this testing should be done on middle level detail, which is the absolute minimum level of abstraction that can be done due to wide applicability of methodics. Methodics offers solution to the problem of performance comparison when organization need to answer question - Which data warehouse system should we use in our organization? However, methodics expects already some knowledge about data warehouse content.

Master thesis deals with a problem of data integration between Big Data platform and enterprise data warehouse. Main goal of this thesis is to create a complex transfer system to move data from a data warehouse to this platform using a suitable tool for this task. This system should also store and manage all metadata information about previous transfers. Theoretical part focuses on describing concepts of Big Data, brief introduction into their history and presents factors which led to need for this new approach. Next chapters describe main principles and attributes of these technologies and discuss benefits of their implementation within an enterprise. Thesis also describes technologies known as Business Intelligence, their typical use cases and their relation to Big Data. Minor chapter presents main components of Hadoop system and most popular related applications. Practical part of this work consists of implementation of a system to execute and manage transfers from traditional relation database, in this case representing a data warehouse, to cluster of a few computers running a Hadoop system. This part also includes a summary of most used applications to move data into Hadoop and a design of database metadata schema, which is used to manage these transfers and to store transfer metadata.

The Kimball methodology, often referred to as dimensional modelling, is well established in data warehousing and business intelligence as a highly successful means for turning data into information. Yet weaknesses exist in the Kimball approach that make it difficult to rapidly extend or interrelate dimensional models in complex business areas such as Health Care. This Thesis looks at the development of a methodology that will provide for the rapid extension and interrelation of Kimball dimensional models. This is achieved through the use of techniques similar to those employed in the semantic web. These techniques allow for rapid analysis and insight into highly variable data which previously was difficult to achieve. / Graduate

As an effort to guide patients toward being more informed and more involved as healthcare decision makers in the clinical processes, health care organizations have adopted a new technology referred to as an integrative social media platform (ISMP). This ISMP combines features of mobile technology and those of social media technology, integrating healthcare systems in order to support a more patient-centered healthcare process. However, users, both physicians and patients, have showed varied usages of ISMP, as a results, have shown mixed results of ISMP. To provide a better understanding of the use of ISMP, especially the interaction between patients and physicians, I turned to the concept of affordances. Affordances describe the possibilities for goal-oriented actions that a technical object offers to a user. Using a mixed-method approach with real archival event log data, conversation texts, documents, interview, and focus-group data from a large hospital which had adopted an ISMP, I confirmed three types of affordance: perceived affordance, behavioral affordance, and interactive affordance. I identified two key affordances of ISMP that lead to patient-centered care, namely ubiquitous access and virtual healthcare consultation, which represent a behavioral affordance and an interactive affordance, respectively. I also explored how different types of affordances are actualized and how they interact with each other to contribute to patient-centered care.

The desire to obtain value and justify investments from the different Information Systems in place in organizations has been around for a long time. Organizations constantly theorize and implement different approaches that provide some sort of alignment between their different business objectives and Information Systems. Unfortunately, the environments in which these organizations operate are often dynamic, constantly changing with influence from external and internal factors that require continual realignment of the Information Systems with business objectives to provide value. When businesses evolve, leading to changes in business requirements, it is hard to know what direct Information System changes are needed to respond to the new requirements. Similarly, when there are changes in the Information System, it is not often easy to discern which business objectives are directly affected. Whilst the different Enterprise Architecture frameworks available today provide and propose some form of alignment, in their implementation, they do not show links between business objectives and Information Systems, i.e., indicating what Information System is directly responsible for different business objectives thereby allowing for anticipation and support of changes as the business evolves. This thesis utilizes insights from Business Intelligence and uses the User Requirements Notation (URN), which enables modeling of business processes and goals, to provide a framework that exploits links between business objectives and Information Systems. This Business Intelligence - Enabled Adaptive Enterprise Architecture framework allows for anticipating and supporting proactively the adaptation of Enterprise Architecture as and when the business evolves. The thesis also identifies and models levels within the enterprise where responses to change as the business evolves are needed and the ways the changes are presented. The tool-supported framework is evaluated against the different levels and types of changes on a realistic Enterprise Architecture at a Government of Canada department, with encouraging results.

Public healthcare provision is under increasing economic restraints making an efficient and sustainable managerial planning a necessity in the hospital sector. Business Intelligence is the extraction of business relevant knowledge in order to adjust and refine executive operations. On the free market industries have applied the according methods and software dedicated to the generation of Business Intelligence is offered by variety of companies. Data Mining, furthermore, describes the facilitation of algorithms in order to train programs to detect unseen patterns from huge amounts of data. Therefore mining techniques are suitable for adding to the business relevant knowledge, particularly as they can produce more accurate predictions. The thesis examined the status of Information Technology normally utilized in Austrian hospitals and simultaneously identified studies that apply Data Mining to a Hospital Information System to gain Business Intelligence. While the general level of Austrian Hospital Information Systems is well sophisticated, common challenges are present in a separation between clinical and administrative systems and their interfaces. For the Data Mining a majority of studies aims at medical improvements. Some applications were found to have good business relevant prospects but their feasible introduction into the practice needs additional fostering.

This thesis analyzes the situation in the area of Business Intelligence at O2 Czech Republic. It focuses on identifying key issues and finding solutions to the overall improvement of the service within the company. It can be a guide for managers on how to proceed in the analysis of the BI environment, finding opportunities for improving organization setup and technical aspects, especially in the data warehouse solution. Here one can also find recommendations on how to proceed with the definition of development methodologies and how to effectively set the tools and processes associated with the development of the data warehouse. This approach results in an efficient, clearly documented and sustainable development concept of the data warehouse in a large company.

Diplomová práce popisuje moderní koncept řízení Corporate Performance Management a jeho efektivní podporu v informačních systémech organizace. První část práce se věnuje základním principům CPM, vycházejících ze současných manaţerských systémů, a jejich provázanosti na business intelligence technologie. Uvádí procesy, metriky, technologie, metodiky a přístupy, které se v rámci řízení výkonnosti a jeho zavádění v organizaci pouţívají. Druhá část práce se jiţ zabývá reálným projektem implementace řízení výkonnosti ve skupině RWE CZ. Popisuje průběh tohoto projektu a konfrontuje ho s doporučeními, která uvádí teorie. Pro jednotlivé fáze projektu jsou pak odvozeny kritické faktory úspěchu. V závěru práce je navrţena kategorizace těchto faktorů a ke kaţdému z faktorů je uvedeno doporučení pro jeho řešení.

První část této diplomové práce je zaměřena na vymezení základních aspektů Business Intelligence a její popis, který může být určen k prostudování, jakožto úvod pro jedince této problematiky neznalé. Základní myšlenky a principy jsou vysvětlovány na názorných obrázcích. Ideje zde přednesené ale mohou dále sloužit jako ?jiný? pohled určený k dalšímu uvažování o těchto základních otázkách. Následně se práce zabývá implementací Business Intelligence v organizaci a některými souvislostmi v projektu Business Intelligence. Shrnutí doporučení uváděných v literatuře a nejen z nich vyúsťující návrhy ETL standardů jsou poslední teoretickou částí. Práce je uzavřena dokumentací k projektu Reportingového systému, resp. především části ETL, kterou autor v době psaní textu zpracovával (neveřejná část práce)