Large-scale data analysis relies on custom code both for preparing the data for analysis as well as for the core analysis algorithms. The map-reduce framework offers a simple model to parallelize custom code, but it does not integrate well with relational databases. Likewise, the literature on optimizing queries in relational databases has largely ignored user-defined functions (UDFs). In this paper, we discuss annotations for user-defined functions that facilitate optimizations that both consider relational operators and UDFs. We believe this to be the superior approach compared to just linking map-reduce evaluation to a relational database because it enables a broader range of optimizations. In this paper we focus on optimizations that enable the parallel execution of relational operators and UDFs for a number of typical patterns. A study on real-world data investigates the opportunities for parallelization of complex data flows containing both relational operators and UDFs.

Virtual Private Ontology Server (VPOS) is a middleware software with focus on ontologies (semantic models). VPOS is offering a smart way to its users how to access relevant part of ontology dependent on their context. The user context can be expertise level or level of experience or job position in a hierarchy structure. Instead of having numerous numbers of ontologies associated to different user contexts, VPOS keeps only one ontology but offers sub-ontologies to users on the basis of their context. VPOS also supports reasoning to infer new consequences out of assertions stated in the ontology. These consequences are also visible for certain contexts which have access to enough assertions inside ontology to be able to deduct them. There are some issues within current implementation of VPOS. The application uses the random-access memory of local machine for loading the ontology which could be the cause of scalability issue when ontology size exceeds memory space. Also assuming that each user of VPOS holds her own instance of application it might result into maintainability issues such as inconsistency between ontologies of different users and waste of computational resources. This thesis project is about to find some practical solutions to solve the issues of current implementation, first by upgrading the architecture of application using new framework to address scalability issue and then moving to cloud addressing maintainability issues. The final production of this thesis project would be Cloud-VPOS which is an application made to deal with semantic web mechanisms and function over cloud plat-form. Cloud-VPOS would be an application where semantic web meets cloud computing by employing semantic web mechanisms as cloud services. / ebbits project (Enabling business-based Internet of Things and Services)

The SAP HANA database is the core of SAP's new data management platform. The overall goal of the SAP HANA database is to provide a generic but powerful system for different query scenarios, both transactional and analytical, on the same data representation within a highly scalable execution environment. Within this paper, we highlight the main features that differentiate the SAP HANA database from classical relational database engines. Therefore, we outline the general architecture and design criteria of the SAP HANA in a first step. In a second step, we challenge the common belief that column store data structures are only superior in analytical workloads and not well suited for transactional workloads. We outline the concept of record life cycle management to use different storage formats for the different stages of a record. We not only discuss the general concept but also dive into some of the details of how to efficiently propagate records through their life cycle and moving database entries from write-optimized to read-optimized storage formats. In summary, the paper aims at illustrating how the SAP HANA database is able to efficiently work in analytical as well as transactional workload environments.

The main purpose of this master's thesis is to propose and implement a SAP CAR (customer activity repository) solution as an application into the current enterprise information system. Following the analysis of the existing system, there will be a solution created, which is fulfilling the customer demands and at the same time it is feasible under given conditions and in the current environment. This project is closely related with addressing the disaster recovery issue for making the system highly available. The final design is implemented, tested and then handed over to the customer.

Large-scale data analysis relies on custom code both for preparing the data for analysis as well as for the core analysis algorithms. The map-reduce framework offers a simple model to parallelize custom code, but it does not integrate well with relational databases. Likewise, the literature on optimizing queries in relational databases has largely ignored user-defined functions (UDFs). In this paper, we discuss annotations for user-defined functions that facilitate optimizations that both consider relational operators and UDFs. We believe this to be the superior approach compared to just linking map-reduce evaluation to a relational database because it enables a broader range of optimizations. In this paper we focus on optimizations that enable the parallel execution of relational operators and UDFs for a number of typical patterns. A study on real-world data investigates the opportunities for parallelization of complex data flows containing both relational operators and UDFs.

Graph-structured data is ubiquitous and with the advent of social networking platforms has recently seen a significant increase in popularity amongst researchers. However, also many business applications deal with this kind of data and can therefore benefit greatly from graph processing functionality offered directly by the underlying database. This paper summarizes the current state of graph data processing capabilities in the SAP HANA database and describes our efforts to enable large graph analytics in the context of our research project SynopSys. With powerful graph pattern matching support at the core, we envision OLAP-like evaluation functionality exposed to the user in the form of easy-to-apply graph summarization templates. By combining them, the user is able to produce concise summaries of large graph-structured datasets. We also point out open questions and challenges that we plan to tackle in the future developments on our way towards large graph analytics.

The diploma thesis focuses on implementation of ERP solution produced by SAP, especially on implementation methodology and project definition, in a company environment. The main aim of this thesis is to devise methodology based on ASAP methodology using experience from previous projects of the company I work for. This company specializes in software implementation. This text reveals phases of a project in great details, defines it and describes implementation methodology including outputs and aims. The text also includes a brief description of not only ERP system, but also SAP HANA system. SAP HANA (at the time of writing this text) is an innovative product. Finally, SAP HANA installation is briefly described along with ERP, considering the previously created methodology.

Hlavním cílem této práce je vyvinout uživatelské rozhraní a získávání nezbytných podnikových dat v aplikaci sloužící pro schvalování bankovních plateb za použití moderních technologií a technologií poskytovaných společností SAP. V první části je obecně popsáno téma bankovních plateb, jsou vysvětleny klíčové pojmy a zmíněny některé problémy z této oblasti, se kterými se společnosti a soukromníci v dnešní době potýkají. Dále je popsána architektura SAP S/4HANA, pro kterou je aplikace vyvíjena. V neposlední části jsou zmíněny technologie pro tvorbu uživatelských rozhraní, jenž jsou pro tento vývoj vhodné anebo jsou dnes nejvíce používány. Proces návrhu aplikace popisuje její požadavky, tvorbu prototypu aplikace, jenž vizualizuje způsob zobrazení dat uživateli a návrh datového modelu. Výsledná aplikace umožňuje získávat správná data z databáze, zobrazovat je definovaným způsobem způsobem a nabízí možnost jejich editace a správy.

The diploma thesis deals with migration of SAP Business Warehouse system to the new in-memory technology SAP HANA. Theoretical basis defines basic terms, usage in-memory technology in Business Intelligence and migration options. In the practical part, the best option of migration and best practices for the company was designed.