Effects of interband and intraband impurity scattering on coherence length in the pnictide superconductors

After discovery of cuprates, a search for new high temperature superconducting families began and it led to the discovery of layered pnictide compounds with critical temperatures limited up to ~56 K. Pnictides consist elements from Group V of Periodic Table (nitrogen, phosphorus, arsenic, antimony and bismuth). In this work coherence length ξh in mixed state of pnictide superconductors is calculated numerically. In calculation is taken into account interband and intraband impurity scattering in framework of quasiclassical Eilenberger theory for s± pairing symmetry. Differences between Ginzburg-Landau and Eilenberger theories is shown and the comparison with existing models is done.

MASTER DATA MANAGEMENT MATURITY AND TECHNOLOGY ASSESSMENT - From theory to practice, case Ineo Oy

After decades of mergers and acquisitions and successive technology trends such as CRM, ERP and DW, the data in enterprise systems is scattered and inconsistent. Global organizations face the challenge of addressing local uses of shared business entities, such as customer and material, and at the same time have a consistent, unique, and consolidate view of financial indicators. In addition, current enterprise systems do not accommodate the pace of organizational changes and immense efforts are required to maintain data. When it comes to systems integration, ERPs are considered “closed” and expensive. Data structures are complex and the “out-of-the-box” integration options offered are not based on industry standards. Therefore expensive and time-consuming projects are undertaken in order to have required data flowing according to business processes needs. Master Data Management (MDM) emerges as one discipline focused on ensuring long-term data consistency. Presented as a technology-enabled business discipline, it emphasizes business process and governance to model and maintain the data related to key business entities. There are immense technical and organizational challenges to accomplish the “single version of the truth” MDM mantra. Adding one central repository of master data might prove unfeasible in a few scenarios, thus an incremental approach is recommended, starting from areas most critically affected by data issues. This research aims at understanding the current literature on MDM and contrasting it with views from professionals. The data collected from interviews revealed details on the complexities of data structures and data management practices in global organizations, reinforcing the call for more in-depth research on organizational aspects of MDM. The most difficult piece of master data to manage is the “local” part, the attributes related to the sourcing and storing of materials in one particular warehouse in The Netherlands or a complex set of pricing rules for a subsidiary of a customer in Brazil. From a practical perspective, this research evaluates one MDM solution under development at a Finnish IT solution-provider. By means of applying an existing assessment method, the research attempts at providing the company with one possible tool to evaluate its product from a vendor-agnostics perspective.

Evaluating the Maturity of Data Management Practices in a Major Energy Provider Company

Data is the most important asset of a company in the information age. Other assets, such as technology, facilities or products can be copied or reverse-engineered, employees can be brought over, but data remains unique to every company. As data management topics are slowly moving from unknown unknowns to known unknowns, tools to evaluate and manage data properly are developed and refined. Many projects are in progress today to develop various maturity models for evaluating information and data management practices. These maturity models come in many shapes and sizes: from short and concise ones meant for a quick assessment, to complex ones that call for an expert assessment by experienced consultants. In this paper several of them, made not only by external inter-organizational groups and authors, but also developed internally at a Major Energy Provider Company (MEPC) are juxtaposed and thoroughly analyzed. Apart from analyzing the available maturity models related to Data Management, this paper also selects the one with the most merit and describes and analyzes using it to perform a maturity assessment in MEPC. The utility of maturity models is two-fold: descriptive and prescriptive. Besides recording the current state of Data Management practices maturity by performing the assessments, this maturity model is also used to chart the way forward. Thus, after the current situation is presented, analysis and recommendations on how to improve it based on the definitions of higher levels of maturity are given. Generally, the main trend observed was the widening of the Data Management field to include more business and “soft” areas (as opposed to technical ones) and the change of focus towards business value of data, while assuming that the underlying IT systems for managing data are “ideal”, that is, left to the purely technical disciplines to design and maintain. This trend is not only present in Data Management but in other technological areas as well, where more and more attention is given to innovative use of technology, while acknowledging that the strategic importance of IT as such is diminishing.