SODA: Generating SQL for Business Users

The purpose of data warehouses is to enable business analysts to make better decisions. Over the years the technology has matured and data warehouses have become extremely successful. As a consequence, more and more data has been added to the data warehouses and their schemas have become increasingly complex. These systems still work great in order to generate pre-canned reports. However, with their current complexity, they tend to be a poor match for non tech-savvy business analysts who need answers to ad-hoc queries that were not anticipated. This paper describes the design, implementation, and experience of the SODA system (Search over DAta Warehouse). SODA bridges the gap between the business needs of analysts and the technical complexity of current data warehouses. SODA enables a Google-like search experience for data warehouses by taking keyword queries of business users and automatically generating executable SQL. The key idea is to use a graph pattern matching algorithm that uses the metadata model of the data warehouse. Our results with real data from a global player in the financial services industry show that SODA produces queries with high precision and recall, and makes it much easier for business users to interactively explore highly-complex data warehouses.Comment: VLDB201

The Credit Suisse meta-data warehouse

This paper describes the meta-data warehouse ofCredit Suisse that is productive since 2009. Like most otherlarge organizations, Credit Suisse has a complex applicationlandscape and several data warehouses in order to meet theinformation needs of its users. The problem addressed by themeta-data warehouse is to increase the agility and flexibility ofthe organization with regards to changes such as the developmentof a new business process, a new business analytics report, or theimplementation of a new regulatory requirement. The meta-datawarehouse supports these changes by providing services to searchfor information items in the data warehouses and to extract thelineage of information items. One difficulty in the design of sucha meta-data warehouse is that there is no standard or well-knownmeta-data model that can be used to support such search services.Instead, the meta-data structures need to be flexible themselvesand evolve with the changing IT landscape. This paper describesthe current data structures and implementation of the CreditSuisse meta-data warehouse and shows how its services helpto increase the flexibility of the whole organization. A seriesof example meta-data structures, use cases, and screenshots aregiven in order to illustrate the concepts used and the lessonslearned based on feedback of real business and IT users withinCredit Suisse

Olfactory behavior and physiology are disrupted in prion protein knockout mice

The prion protein PrP(C) is infamous for its role in disease, but its normal physiological function remains unknown. Here we found a previously unknown behavioral phenotype of Prnp(-/-) mice in an odor-guided task. This phenotype was manifest in three Prnp knockout lines on different genetic backgrounds, which provides strong evidence that the phenotype is caused by a lack of PrP(C) rather than by other genetic factors. Prnp(-/-) mice also showed altered behavior in a second olfactory task, suggesting that the phenotype is olfactory specific. Furthermore, PrP(C) deficiency affected oscillatory activity in the deep layers of the main olfactory bulb, as well as dendrodendritic synaptic transmission between olfactory bulb granule and mitral cells. Notably, both the behavioral and electrophysiological alterations found in Prnp(-/-) mice were rescued by transgenic neuronal-specific expression of PrP(C). These data suggest that PrP(C) is important in the normal processing of sensory information by the olfactory system