This master’s thesis deals with designing of the reporting solution for the selected company. In the theoretical part its describing the present state of the topic, defines the basic terminology, clarifes theoretical background and explain how to understand to a concept of business intelligencem reporting or information systém. Next part describes the design of the solution. This thesis then concludes with brief evalution of the solution and recommendation for the company.

Nevídal, J. Application for business decisions. Diploma thesis. Brno: Mendel Univer-sity, 2015 In this thesis are described a data processing techniques with a focus on Busi-ness Intelligence with using data warehouses. Then is performed analysis of the business environment and determined key performance indicators that will be monitored. In the next section is designed data warehouse that enables reporting the above mentioned of indicators, including their evolution in time. Subsequently is designed and implemented a user interface that makes the resulting reports will be available by the users. In conclusion, the resulting solution is evaluated, both from an economic and from an implementation viewpoint.

This master’s thesis deals with design of the monitoring solution for the Power BI service. The thesis is divided into theoretical, analytical and design sections. In the theoretical part describes the theoretical fundamentals, used technologies and analytical tools. The analytical part analyzes the company Intelligent Technologies, competitive solutions and data sources for the design part. The design part proposes its own solution for monitoring the Power BI service, including the costs and benefits of the proposed solution.

The diploma thesis deals with the design and creation of a reporting solution in a corporate environment over a selected Business Intelligence system. The most suitable Business Intelligence solution will be selected on the basis of criteria specified by the company and a comparison of existing solutions. The output of the diploma thesis will be automatic monitoring of company reports in the Business Intelligence environment, both in information and visually attractive form.

This thesis follows up the creation of data warehouse on Microsoft SQL Server for analysis of measured railway vehicle transits, with provided weather data by Dark Sky service. Thesis represents full data warehouse design (by Kimball Group model) with ETL processes to secure data initialization and automatic updates. Thesis also shows two approaches to presentation layer on data warehouse, by Microsoft Excel (linked to multidimensional cube) and by Power BI.

Many construction companies worldwide continue to implement different methodologies to optimize time and improve management in the execution of works; however, a lack of control in projects continues to be observed. For this reason, one of the most common problems currently is the incompletion of scheduled work. Due to this, it is necessary to keep better control of the projects at the execution stage so that the contractor can optimally, quickly, and easily manage the progress of all the specialties involved. In this sense, this research develops the use of the Plan Grid Application for data collection in the field and the Power Bi software for the automatic processing and information visualization through a management dashboard where indicators are shown to reflect the progress and actual performance of the activities as well as the main non-compliance causes, which leads to optimize the control process and the time spent by its administrators to carry out this management.

I mätrummet på Sandvik Coromant finns en lösning för att visualisera maskinhälsa, mäthistorik och servicetider för olika mätinstrument. Lösningen för datavisualiseringen nyttjar verktyget Power BI och är kopplad till Excelfiler. När data väl hämtats in görs en rad modifieringar på tabellerna för att få fram visualiserbar data. Dessa modifieringar i kombination med många Excelark resulterar i att ledtiderna för att uppdatera en Power BI rapport blir väldigt långa. Nu önskas det att istället nyttja en databaslösning för den data dessa Excelfiler innehåller och därmed förbättra dessa ledtider. Således skapades en databas utifrån den data dessa Excelfiler innehöll. Power BI tillåter användaren att importera data från en databas till applikationen på två sätt, via Import Mode eller DirectQuery. Import Mode läser in samtliga tabeller som efterfrågas och lagrar dessa i minnet. DirectQuery ställer frågor direkt till databasen utifrån vad som efterfrågas. I och med denna skillnad i importsätt finns metoder för att optimera den databas som data läses in ifrån. Studien undersöker hur olika typer av indexering och olika typer av kompression av dessa index påverkar svarstiden på frågor ställda av Power BI för att besvara följande två forskningsfrågor: Hur påverkar olika typer av indexering av en databas datahämtningshastigheten vid användning av Power BI? Hur påverkar olika typer av kompression av index datahämtningshastigheten vid användning av Power BI? Studien utfördes genom att studera execution plans och exekveringshastighet för de frågor som ställdes mot databasen av Power BI. Med hjälp av T-SQL kunde exekveringshastigheten för en specifik fråga tas fram. Denna exekveringshastighet jämfördes sedan för de olika typerna av index och kompression mot exekveringshastigheten för samma fråga mot en tabell helt utan index. Detta utfördes sedan på tabeller med varierande antal rader, där antalet rader som testades var 33 001, 50 081, 100 101, 500 017 och 1 000 217. Resultatet av studien visar att för Import Mode är det bästa typen av index ett clustered rowstore index utan kompression, med undantag för tabeller med över 1 001 217 rader där radkompression presterade bättre. För DirectQuery presterade non-clustered rowstore index bäst, men för vilken kompression var resultatet tvetydigt. Detta eftersom samtliga typer av kompression presterade bäst för olika antal rader i tabellen. För tabeller med fler än 500 017 rader presterade dock ingen kompression allra bäst. / In the measurement room at Sandvik Coromant there is a solution for visualizing machine health, measurement history and service times for different measuring instruments. The data visualization solution uses Power Bi and connects to Excel files. Once the data has been collected, a number of modifications are made on the tables to produce something that is possible to visualize. These modifications in combination with many Excel sheets result in very long lead times for updating a Power BI report. Now it is desired to use a database solution for the data contained in the Excel files and thus improve these lead times. For this, a database was created based on the data that these Excel files contained. Power BI allows the user to import data from a database into the application in two ways, via Import Mode or DirectQuery. Import Mode loads all the requested tables and stores them in memory. DirectQuery runs queries directly to the database, based on what is requested. Due to this difference, there are methods to optimize the database from which the data is loaded. This study examines how different types of indexing and different types of compression affect the response time for queries ran by Power BI to answer the following two research questions: How do different types of indexing affect a database's data retrieval rate when using Power BI? How do different types of compression affect the data retrieval rate when using Power BI? This was done by studying execution plans and execution rate for the queries that was done towards the database by Power BI. With the help of T-SQL, the execution rate for a specific query was obtained. The execution rate for different types of index and compression was then compared against a table without an index. This was then performed on tables with varying numbers of rows, where the numbers of rows that were tested was 33 001, 50 081, 100 101, 500 017 and 1 000 217. The results of the study show that for Import Mode, the best type of index is a clustered rowstore index without compression, with the exception of tables with over 1 001 217 rows where row compression performed better. For DirectQuery, non-clustered rowstore index performed best, but for which compression the result was ambiguous. This was because all types of compression performed best for different number of rows in the table. However, for tables with more than 500 017 rows, no compression performed best.

Today, the construction industry handles and analyzes a lot of data manually. This can be a very time-consuming process that could be improved by introducing Business Intelligence (BI). BI is a technology that could visualize the current status of a company automatically, with the help of Key Performance Indicators (KPIs).MVP Software is a company that has developed a project management tool, ”Projektportalen”, for companies in the construction industry. MVP Software would like to enhance their application with BI functionality.This thesis researches, through a case study, how BI functionalities could be integrated into the web application Projektportalen. The case study consisted of interviews and explorations of Microsoft’s product Power BI.The final result is a list of desired BI functionalities in Projektportalen. The result also consists of a suggested updated architecture of Projektportalen for a Power BI integration and how an example dashboard could be created. Actual implementations in source code could be conducted in the future to integrate Power BI. The example dashboard could also be further developed into a dashboard prototype. / Byggoch hantverksbranschen använder idag mycket manuell datahantering och manuell analys av data. Detta kan vara en tidskrävande process som skulle kunna effektiviseras genom Business Intelligence (BI). BI är en teknologi som automatiskt, med hjälp av nyckeltal, kan visa hur en verksamhet presterar och mår.MVP Software är ett företag som utvecklat projektverktyget ”Projektportalen” för byggoch hantverksbranschen. De vill nu utöka Projektportalen med BIfunktionalitet.Den här rapporten undersöker, genom en fallstudie, hur BI-funktionalitet skulle kunna integreras i webbapplikationen Projektportalen. Fallstudien bestod av intervjuer och enklare testkörningar av Microsofts produkt Power BI.Resultatet blev i slutändan en lista med önskvärda BI-funktionaliteter för Projektportalen. Resultatet består också av ett förslag på en uppdaterad applikationsarkitektur för att möjliggöra integrering av Power BI samt hur en enkel exempeldashboard skulle kunna skapas. Vidare tekniska undersökningar behöver göras för att ta reda på hur applikationens källkod ska utökas för att möjliggöra integrering av Power BI. Exempel-dashboarden skulle också kunna utvecklas vidare till en mer komplett dashboard-prototyp.

Актуальность выбранной темы обусловлена потребностью предприятия ООО «ПРОФХОЛОД», которое выбрало путь цифровой трансформации бизнеса. Цель трансформации – опираться на данные при разработке и принятии управленческих решений, при этом не тратить значительные ресурсы на расчет показателей. Компания ОOO «ПРОФХОЛОД» разрабатывает системы и технологии управления теплом. Является лидером Российского рынка в сфере по объему продаж сэндвич-панелей с пенополиуретаном и полиизоциануратом. Цель работы: повышение качества управленческой отчетности компании путем разработки и внедрения в компанию ООО «Профхолод» BI-аналитики на базе инструмента Microsoft Power BI. Объектом исследования является бизнес-процесс в бизнес-аналитике. Предметом исследования следует указать внедрение и разработку бизнес-аналитики в бизнес-процессы через автоматизацию отчетности компании на базе инструментов Micrasoft Power BI. Результаты работы заключается в том, что были определены понятия Бизнес-аналитики и ее основные инструменты. С практической точки зрения были автоматизированы системы отчетности в компании и тем самым бизнес-процессы на предприятие были модернизированы через внедрение BI. Научная новизна состоит в том, что проанализированы различные системы BI и подробно изучены современные функции Power BI для реализации проекта. Экономическая эффективность имеет лишь прогнозный характер и показывает по подсчетам, что система полностью окупит себя. / The relevance of the chosen topic is due to the needs of the enterprise PROFHOLOD LLC, which has chosen the path of digital business transformation. The goal of the transformation is to rely on data in the development and adoption of management decisions, while not spending significant resources on calculating indicators. LLC "PROFHOLOD" develops systems and technologies for heat management. It is the leader of the Russian market in terms of sales of sandwich panels with polyurethane foam and polyisocyanurate. The purpose of the work: improving the quality of the company's management reporting by developing and implementing BI-analytics based on the Microsoft Power BI tool in Profholod LLC. The object of study is a business process in business analytics. The subject of the study should be the implementation and development of business intelligence in business processes through the automation of company reporting based on Micrasoft Power BI tools. The results of the work lies in the fact that the concepts of Business Intelligence and its main tools were defined. From a practical point of view, the reporting systems in the company were automated and thus the business processes in the enterprise were modernized through the introduction of BI. The scientific novelty lies in the fact that various BI systems have been analyzed and modern Power BI functions for project implementation have been studied in detail. Economic efficiency is only predictive in nature and shows, according to estimates, that the system will fully pay for itself.

This thesis describes modern approaches to Business intelligence. It also explains in detail platform Power BI and Business intelligence add-ins for Microsoft Excel 2013. This thesis also shows how to create an application that communicates with free billing service iDoklad. The resulting aaplication is evaluated from an economic and implementation standpoint.