Principle of operation of ORM

Key feature of ORM is display which is used for an object binding to its data in a DB. ORM as if creates the "virtual" database scheme in memory and allows to manipulate data already at the object level. Display shows as an object and its properties are connected to one or several tables and their fields in the database. ORM uses information of this display for process control of data transformation between a basis and forms of objects, and also for creation of SQL queries for an insertion, up-dating and deleting data in response to changes which the application makes to these objects.

Distributed database – a set of the separated data which are logically connected among themselves (and their descriptions) which are physically distributed on some computer network. The distributed DBMS – the program complex intended for control of distributed databases and allowing to make distribution of information of the transparent for the ultimate user.

Users interact with a distributed database through applications. Applications can be classified as those which don't require data access on other websites (local applications), and those which require similar access (global applications).

One of approaches to integration of object-oriented applications with relational databases consists in development of heterogeneous information systems. Heterogeneous information systems facilitate integration of the heterogeneous information sources structured (with existence of the regular (normalized) diagram), semistructured and sometimes even unstructured. Any heterogeneous information system is constructed on the global database scheme over databases of components so users get advantages of the diagram, that is uniform interfaces of access (for example, the sql-style interface) to the data saved in different databases and rich functional capabilities. Such heterogeneous information system is called system of the integrated multi-databases.

Formation of the database management systems (DMS) matched on time the considerable progress in development of technologies of the distributed computation and parallel processing. Distributed control systems databases and parallel database management systems resulted. These systems become the dominating tools for application creation of intensive data handling.

The parallel computer, or the multiprocessor in itself is the distributed system made of the nodes (processors, memory components) connected by a bystry network in the general casing. The technology of distributed databases can be naturally reconsidered and widespread on parallel database systems, i.e. database systems on parallel computers

The distributed and parallel DBMS provides the same functionality, as host-based DBMSes, except for the fact that they work in the environment where data are distributed on nodes of a computer network or the multiprocessor system.

Questions:

1.What makes databases such an essential component of modern life?

2. Can databases be used to predict consumer behavior?

3. What are the basic components of a database?

4. Why are relationships a significant aspect of databases?

5. What’s the difference between flat files and other database models?

References

1. June J. Parsons and Dan Oja, New Perspectives on Computer Concepts 16th Edition - Comprehensive, Thomson Course Technology, a division of Thomson Learning, Inc Cambridge, MA, COPYRIGHT © 2014.

2. Lorenzo Cantoni (University of Lugano, Switzerland) James A. Danowski (University of Illinois at Chicago, IL, USA) Communication and Technology, 576 pages.

3. Craig Van Slyke Information Communication Technologies: Concepts, Methodologies, Tools, and Applications (6 Volumes). ISBN13: 9781599049496, 2008, Pages: 4288

4. Utelbaeva A.K.,Utelbaeva A.K. Study guide for lectures on discipline “Computer science”, Shimkent 2008, 84 pages.

Lecture №6. Data analysis. Data management..
Purpose: to give a common concepts of correlation, regression, and also to become acquainted with descriptive statistics.
Plan:
1.Data analysis bases.

2.Methods of collection, classification and prediction. Decision trees. Processing of large volumes of data.

3. Methods and stages of Data mining. Tasks Data mining. Visualization of data.

1. Data analysis bases.

In this lecture we will consider some aspects of statistical analysis of data, in particular, descriptive statistics, cross-correlation and regression analyses. A statistical analysis includes the large variety of methods, even for a superficial acquaintance with that volume of one lecture too small. Aim of this lecture - to give a common idea about the concepts of correlation, regression, and also to become acquainted with descriptive statistics. The examples considered in a lecture are intentionally simplified.

There is a large variety of the applied packages realizing the wide spectrum of statistical methods, they are also named universal packages or instrumental sets. About such sets we in detail will talk in the final chapter of course. The wide arsenal of methods of mathematical statistics is also realized in Microsoft Excel, realization of examples of this lecture is shown exactly on this program

Descriptive statistics
Descriptive statistics is a technique of collection and adding up of quantitative data, that is used for converting of mass of digital data into a form comfortable for perception and discussion.

Aim of descriptive statistics - to generalize the primary results got as a result of supervisions and experiments.