Thursday, December 11, 2008

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Create a Data Source with DataTime, join through the visual tool of arbitrary DataTime, Report from multiple tables, multiple Datagrid


E' possibile inoltre creare un Report con DataTime cliccando sulla finestra ' New Data Source '.
A sinistra della pagina che si aprirà sono elencate una serie di tabelle , scegliamo a titolo esemplicativo le tabelle: ProductName, OrderID e ProductID.
Selezioniamo da ogni tabella gli elementi che ci interessano e successivamente stabiliamo delle relazioni tra le tabelle prescelte cliccando sul tasto destro del mouse e scegliendo dal menu a tendina l'opzione ' Map Dms Relationships on Objects on Designer Panel '.
A questo punto selezioniamo l'opzione ' Check Out' per testare la nostra query attraverso il tasto 'Try Query ', Then opens the window' User Query '.
The next step is to save what has been done so far by clicking the 'Refine Manual' and then 'Save '.
Finally we return to the home page and click first on ' Data Source' and then ' New Report' to view the report. Once you have chosen dimensions and measures, we will create our Report window by clicking on the 'Generate '.
You can add text, graphics and tables from the 'Report Composer'.

Tuesday, December 9, 2008

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Reporting, Charting with DataTime

DataTime allows the inclusion of texts, graphics, pictures and gauge in a completely customized by the user, through the window ' Report Composer '.

Example Report:





In this case it was possible to construct the gauge or dashboard, that tool to represent the values \u200b\u200bof individual cells through the window ' multichat Designer' ' . This window allows you to create two-dimensional graphics and three-dimensional choosing colors and properties.
If you want to change the style of table you must click the right mouse button. From the pulldown menu click sulla voce ' Grid Styles' , comparirà allora la finestra 'Bulk Style Changes ' che consente di modificare il layout della tabella con stili già presenti nel software o creandone di nuovi.























Monday, December 8, 2008

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DataTime Introducing Reporting System: a simple report

To create a report with DataTime is necessary, first, go to the homepage of the software and select the setting ' New Project' . Once this is done click on the 'Open project' DataTime at this point we ask you to create a connection to the database. Then select the command 'New Connection ' will open a window containing a list of ' Common Connection', select Microsoft Office Access, then save the connection.
Now click on the ' Db Explorer / Quik Report' and then ' (Re) Load Structure' , We will then show all data tables. We choose, for example, the table ID Oder. You can create a Quik Reports from key 'Quik Report'. This will open the ' Reportgrid ' from which we can choose dimensions and measures of our report.
The last step will be to generate the report by clicking on the option 'Generate '.

Sunday, December 7, 2008

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The main QUERY REPORTING TOOL SW






The software queries are reporting business intelligence tools can help companies to improve their performance.







Here I report the main

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function of 'ETL and ETL

ETL (Extract, Transform, Load) is a process of extraction, transformation and loading of data into a synthesis system (data warehouse, data mart ...). ETL processes (Extraction, Transformation and Loading ) are the components important and with more value-added infrastructure Business Intelligence (BI), they retrieve data from all operating systems and pre-process them for analysis and reporting tool. The accuracy and timeliness of the entire BI platform depend largely on the ETL processes.

The processes of extraction, transformation and loading include multiple steps that have as their goal the transfer of data from production applications to business intelligence systems:

  • Extraction of data from production applications and databases (ERP, CRM, RDBMS, files, etc...)
  • Transformation of these data for their reconciliation on all i sistemi sorgente, eseguire calcoli o parsing di stringhe, arricchirli con informazioni di lookup esterne e confrontare il formato richiesto dal sistema target (Third Normal Form Star Schema, Slowly Changing Dimensions, ecc.).
  • Caricamento dei dati risultanti nelle varie applicazioni BI: Data Warehouse o Enterprise Data Warehouse, Data Mart, applicazioni Online Analytical Processing (OLAP) o “cubi”, ecc.
I maggiori TOOLS di Query Reporting sono:



-ACCESS di Microsoft;

-BOAD;

-COGNOS;

-SAP;

-BUSINESS OBJECTS.

Saturday, December 6, 2008

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main tool software architectures for enterprise information systems: DW, transactional DBMS, Data mart

E' opportuno chiarire innanzitutto cosa intendiamo per sistema informativo aziendale . Si tratta dell'insieme di tutti i dati e di tutti i flussi che riguardano la raccolta, la produzione, l’archiviazione, l’elaborazione, la distribuzione dei dati, nelle attività operative e di controllo che si svolgono all’interno dell’azienda. I data warehouse e i data mart sono basi di dati che integrano fonti diverse di dati e separano l'ambiente operativo e transazionale del sistema informativo aziendale dall'ambiente di analisi e produzione delle informazioni manageriali.

Più dettagliatamente:

Una BASE DI DATI TRANSAZIONALE è un DBMS in cui le operazioni di scrittura sul database sono in gradi di ESSERE RIPRISTINATE se non sono compilate correttamente. Il concetto stesso di transazione indica quell'operazione che si deve concludere sempre con un successo o un insuccesso,

I DATA WAREHOUSE sono dbms orientati all'analisi che non hanno bisogno di sistemi di sicurezza, di dinamicità e di normalizzazione che invece sono caratterizzanti dei sistemi transazionali. Possiamo definirli come tipi di sistemi decisionali, orientati all'analisi utente interattiva, intuitiva e veloce di dati corretti e consolidati.

Un DATA MART è un raccoglitore di dati specializzato in un particolare soggetto. Normalmente si colloca a valle di un data waehouse più globale ed è alimentato a partire da esso, di cui costituisce, in pratica, un estratto. Detto in termini più tecnici, un Data mart è un sottoinsieme logico o fisico di un Data warehouse di maggiori dimensioni. La differenza fondamentale consiste nel fatto che la creazione del Data warehouse avviene in maniera generalizzata per poi venire incontro alle specifiche esigenze, mentre il Data mart viene generalmente creato per venire incontro ad un'esigenza specifica e già determinata.

La necessità di creare un sistema separato per il Data mart rispetto al Data warehouse può riassumersi nelle seguenti motivazioni:

  • La necessità di utilizzare un diverso schema.
  • Improve performance by separating the dedicated computer.
  • Increasing security having to grant access to a smaller set of data.



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What are the data warehouse and what differentiates them from OLTP systems

As mentioned above, a Data Warehouse is a computer file containing the data of an organization.
What is it?
-The aim is to 'focus' all the company's data in one place.
-It also integrates information from different sources.
-The data are inside processed / cleaned.
-The design is optimized in reading.
For all these reasons, therefore, we can consider it as a db-Ready Only.
What are the objectives?
-Ability to access all of the data, in one centralized database.
-Consistency and data consolidation.
-speed access to information by users.
-base for OLAP.

The data warehouse is a system OLAP (On Line Analytical Processing), analyzes the decision-making processes focusing on the component size information, is a subject oriented, integrated, historic and permanent. Being a sistema OLAP differisce dai sistemi OLTP (On Line Transaction Processing) che vengono utilizzati per analisi. I data warehouse non vengono mai cambiati come, invece, viene fatto con i sistemi OLTP.
Ancora, il sistema OLAP designa un insieme di tecniche software per l'analisi interattiva e veloce di grandi quantità di dati, che è possibile esaminare in modalità piuttosto complesse. Questa è la componente tecnologica base del data warehouse e, ad esempio, serve alle aziende per analizzare i risultati delle vendite, l'andamento dei costi di acquisto merci, al marketing per misurare il successo di una campagna pubblicitaria, ad una università i dati di un sondaggio ed altri casi simili. Mentre gli strumenti OLAP have the goal of performance and achievement in the search query on a scale as large as possible, as OLTP, however, are aimed at ensuring integrity and security of transactions.
A source of data for a data warehouse is an operating system. The micro data are summarized in two distinct levels: the first level (first level data mart) specifies the unit of time and in the second (second level of data marts) are stored permanently only data with higher frequency. The main approaches to develop a data warehouse are two: create a central data warehouse or data mart to create independent.

Friday, December 5, 2008

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Ansi SQL

In 1982 the American National Standards Institute (ANSI ) approved a rudimentary version of the Structured Query Language (SQL ) produced by IBM to query the database in a relational database management system (RDBMS ). Since then the SQL language becomes the standard for querying databases universally adopted by all manufacturers.
Over the years, SQL has undergone several revivals by the Committee of ANSI SQL, the last of which dates back to 1996.
It was therefore an attempt at unity that would allow all databases speak the same language. In reality, however, every kind of language presents substantial differences that have enabled this project to fulfill their potential.
Given the age and the consequent evolution of this language, we have defined different levels of standards over time. The most important are SQL89, SQL92 and SQL99 , also known as SQL1, SQL2 and SQL3 respectively. The adhesion of the various systems to the standard SQL92 DBMS is never complete and perfect, so have been defined in this sub-standard to define the degree of compatibility of a DBMS. They are: entry SQL, SQL intermediate and full SQL . It may mean that the former is the minimum level of compatibility and the last represents the total compatibility. The de facto standard is represented mainly by the first level, which basically coincides with the former standard, SQL89. From this we understand that the state of assimilation of SQL99 is even more backward.

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Insights on SQL: WHERE clause, GROUP BY , Having.

Clause Where is the list of conditions or requirements that a field must meet to be taken from the 'question (the conditions are specified by comparison operators, logical connectors and comparators as between, in, like, is null).

Group by dividing the rows of a table into smaller groups .
This operator is used to group the results of a SELECT based on the specified field after BY . The operator must be used in conjunction with a statistical function (COUNT, SUM ...), using the following syntax: SELECT
   _campo_, _funzione stat._ 
_tabelle_
FROM [WHERE _condizione_]
GROUP BY _campo_

where _campo_ must be the same in SELECT and GROUP BY .

Having specifica una condizione di ricerca per un gruppo o una funzione di aggregazione. Può essere specificata solo nell'istruzione SELECT. In genere viene inclusa in una clausola GROUP BY. Se la clausola GROUP BY non è specificata, la funzionalità della clausola HAVING corrisponde a quella di una clausola WHERE.

Supponiamo ad esempio che la tabella antichità abbia la colonna prezzo e che ciascuna riga abbia un valore inserito in questa colonna. Quello che ci interessa è di vedere il prezzo dell’oggetto più costoso comprato da ciascun acquirente. Si deve impartire via SQL l’ordine di raggruppare gli acquisti di ciascun acquirente, e di stampare il prezzo dell’acquisto più costoso:

SELECT IDAcquirente, MAX(Prezzo)
FROM ANTICHITA
GROUP BY IDAcquirente;

Ora, aggiungiamo l’istruzione di stampare il prezzo massimo di acquisto se supera i 100 dollari; in questo caso si usa l’istruzione HAVING:

SELECT IDAcquirente, MAX(Prezzo)
FROM ANTICHITA
GROUP BY IDAcquirente
HAVING Prezzo > 100.



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Working with SQL in Access

Access è un DBMS realizzato da Microsoft ed incluso nel pacchetto Microsoft Office, che consente la creazione di un database o tramite db vuoto, o seguendo modelli reimpostati per i meno esperti.
Il linguaggio SQL "standard" può presentare delle variazioni più o meno marcate a seconda del DBMS preso in considerazione.
Access, a tal proposito, presenta delle differenze notevoli.
Di seguito riporto alcune delle peculiarità del linguaggio SQL di Access:

- L'operatore JOIN deve essere sempre identificato con il termine INNER od OUTER, mentre con Oracle utilizzeremmo, per esempio, WHERE operator.

-To define the "field investigation" Access uses braces [...]; Oracle, by contrast, uses quotation marks "... ..."

-
For strings that contain dates, Access allows you to adopt the Latin formula DD / MM / YYYY and a number of DBMS Anglo-Saxon origin that is not possible. In commands the dates are enclosed by single quotes (') for most SQL dialects, while in Access using the pound (#).



Thursday, December 4, 2008

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Aggregate functions

Aggregate functions are special di restituire un solo valore. Inoltre, dato che operano su insiemi di righe, vengono anche chiamate funzioni di gruppo .
Sono di certo una delle più importanti estensioni di SQL fornendo in più, rispetto all' algebra relazionale, un supporto che permette così la valutazione di proprietà che dipendono da più tuple, come ad esempio l'operatore aggregato di conteggio count .

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DEPTH SQL: SELECT clause, WHERE, ORDER BY, TO INSERT, UPDATE, DELETE, COUNT

SQL è un acronimo si Structured Query Language , è il linguaggio di riferimento per le basi di dati relazionali. Non è solo un linguaggio di interrogazione, infatti contiene al suo interno sia le funzionalità a Data Definition Language , DDL (with a set of commands to define the schema of a relational database), whether a Data Manipulation Language, DML (with a set of commands for editing and 'Question of the instance of a database) and those of Data Control Language, DCL (with a set of commands for user management).
SQL allows you to create tables and change their structure or act on the tables, creating queries, adding data, modifying and / or deleting data. Specifically, the DML provides commands to insert, edit, delete or read data into tables in a database. The structure these data must already be defined by DDL. In addition, permission to access that data must be assigned to the user through the DCL.
The syntax for creating a table is: CREATE TABLE

table_name (field_name datatype required ?)

Select

Select The command is the only command Question ( query) SQL, but its expressive power is that you can achieve in a few lines that questions in other languages \u200b\u200bwould require many pages of code. The result is a table of command.

The syntax in its simplest form is:
  SELECT_  list attributi_    
FROM_ list tabelle_
WHERE _condizione_
The list of attributes after the SELECT is that of table columns in output.
The list of tables after FROM table is necessary (in simple cases only one table) to produce the output table.
La condizione dopo WHERE è quella che selezionerà le tuple o righe da inserire nella tabella di uscita.

Insert


Il comando Insert serve ad inserire una o più nuove tuple nella tabella indicata .

La sintassi è:
 INSERT INTO_Tabella_     
[ _lista attributi_]
VALUES ( _lista valori_)

dove è facoltativa; se non è presente si intende che devono essere specified all the fields, but if there is a list, then only the fields must be specified in the order listed.

Update

Update The command used to update data in a table. The

syntax is:
 UPDATE_Tabella_   
SET_nome Field_A = _Name valore_
[WHERE-condizione_ ]
fields listed in the SET clause are updated for all records that satisfy the WHERE clause. The latter may be omitted but in this case all the rows are updated table.



Delete The Delete command serves to delete one or more rows of a data-base. The

syntax is: DELETE

 FROM_Tabella_   
WHERE_condizione_

deletes all tuples that satisfy the condition specified in WHERE, so you can eliminate a large number of data with a single command.

Wednesday, December 3, 2008

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Il content management system


A Content Management System (CMS ), literally "Content Management System", is a tool software installed on a web server designed to facilitate content management of websites , freeing the user from technical knowledge of programming. There are specialized
CMS, that is specially designed for a specific type of content (on-line encyclopedia, a blog, a forum, etc.). CMS and generic , which tend to be more flexible to allow the publication of different types of content.

The two main solutions are opensource CMS Joomla and Drupal.

Joomla community has broader and has its strengths in ease of use and comprehensive functionality, favored by the built-in functions and built-in plug-in developed (both free and commercial). E 'considered a bit' lacking in architecture because you can do a bi-level hierarchies of content (sections and categories).

Drupal , by contrast, is strong on the architecture, but has fewer features and plug-in for Joomla. Other solutions are consolidated

Typo3, Plone Mabo and (the only one written in Python, the others are almost all in PHP). Promising projects, but still young, they are CMS Made Simple, and webgui TYPOlight.

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Multidimentional Cube, Slice & Dice, Roll Up, Drill Down, Filtering


A Date warehouse (DW or ) (English term translatable data warehouse) is a computer file containing the data of an organization.
The amount of data that companies store for analytical purposes is growing every year by about 50%. Only a few years ago, the data used for business intelligence were stored in a centralized data warehouse and data mart in a few departments. Now, the growing demand for business intelligence data of good quality has created a wide range of data repositories distributed within organizations, which has increased costs and complexity for companies looking to maximize the use of analytical data .
information systems that are based on a traditional database systems are often called OLTP (online transaction processing). Their function is to run the daily operations: data editing and simple read operations. A data-warehouse, however, is the heart of an OLAP system (onlineanalytical processing). Their function is to provide support to operations, data analysis and decision making.

For the achievement of DW is juxtaposed with two solutions:
- The first is the 'use of relational technology, data is stored using tables, but the analysis operations are carried out efficiently using special data structures. Systems of this type are said ROLAP (Relational OLAP ).
- the latter, more radical, stores data directly in the form of multi-dimensional structures using vector data. Systems of this type are said MOLAP (Multidimensional OLAP ).
Creating an OLAP database is, more generally, carrying a photograph of information at a given moment and turn these items of information in multidimensional data. E 'possible to perform further queries on the same data to get answers in time much lower than similar operations on other types of databases. The OLAP
Specimen layout created for this purpose is called a multidimensional cube . It is a powerful entity to perform all possible combinations in a table extracted for analysis. The multi-dimensional cube can be created in several ways but the best known is the one that uses the pattern "star". At the center of the diagram is the table of "facts" that lists the main elements which will be built on the question. Connect to this table there are various tables of the "dimensions" that specify how the data will be aggregated. The calculation of the possible combinations of these groupings form an OLAP structure that potentially could contain all the answers for each combination. The

basic functions of an OLAP tool are: Drill down

that adds a dimension of analysis by disaggregating the data. For example, an analyst may wish to add the distribution of the amount sold in the sales areas, carrying out the 'drill down on transaction Area. attribute values \u200b\u200btake zone 'North', 'center', 'South'.

Roll up eliminates a dimension of analysis, re-aggregated data. For example, an analyst might lose interest in the monthly breakdown of sales, being more interested in highlighting areas for the subdivision through the operation roll up on months.
Alternating
operations roll up and drill down, the analyst can highlight the dependency of the phenomena represented in the facts on social dimensions, and thus highlight their properties. Note that the roll-up operation can be carried out by using the query results, while the drill down operation usually requires a reformulation of the question, because it can add columns not present in it.

Other functions include:

Slice and Dice , functionality that lets you restrict the analysis only to certain parts of the scale and only some of the dimensions proposed.

Filtering you need to select a portion dei dati in modo da dare una risposta utile all'utente in modo diretto o indiretto, migliorando la funzione di ricerca.










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Funzioni-Scopo dei software di query reporting. Prodotti software più diffusi, i più semplici da usare

I software di query reporting consentono di progettare, esplorare e visualizzare report, in modo tale da gestire chiaramente le informazioni aziendali garantendo un accesso affidabile e sicuro ai dati. Questi software consentono alle aziende di utilizzare in maniera strategica la mole di dati a loro disposizione e pertanto costituiscono la base di un’ampia strategia di business intelligence.
I software di query reporting più conosciuti e semplici da usare sono:

Crystal Reports è uno degli strumenti di programmazione utilizzato per produrre report. È stato creato dalla Cristal Decisions nel dicembre 2003. I punti di forza del prodotto sono dati dalla sua semplicità di utilizzo, dalla velocità di produzione di template di report, facilmente gestibili e modificabili, e dall'integrabilità con altri prodotti/programmi soprattutto su piattaforme Microsoft; il suo limite maggiore è dato dalle performance non ottimali in presenza di volumi di dati elevati .

Business Objects
è un'azienda, con sede centrale in Francia, che crea e commercializza applicazioni intelligence to analyze internal and external data. The company seeks to help customers increase efficiency, align business strategies and improve our products and service. It is a product dedicated to business intelligence, and therefore allows to create advanced reporting and analysis on existing data in other databases. While the data are stored on external databases, the different entities and the interrelationships are described in an intermediate level of metadata. The metadata is stored together with the reports, in an external database.

Microstategy is a leader in business intelligence software based on open systems. This software's query reporting, in its various versions, from access to all data of the 'company, and the data warehouse. It also offers powerful tools for data mining.

Cognos is an IBM product. It is a world leader in business intelligence, corporate performance management, data integration, enterprise risk management, olap reporting basis. It 's a software for managing the retail market, Oracle technology and balance scorecards for the company.

DataTime reporting solution is the most modern and powerful currently on mecato. Has high flexibility, makes it possible to create any type of layout with the almost unlimited possibilities of Slice and Dice Cube multimedia data.



Tuesday, December 2, 2008

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I principali DBMS presenti sul mercato

The following is a list of the top Data Base Management System :

ACCESS , produced by Microsoft, is the most common management system database for the environment Microsoft Windows. Access can be used in two ways: 1
- as manager of the database independently on personal computers (in this case reflects the limitations of the architecture of personal computers provides a transactional product limited, with security mechanisms, data protection and management of competition rather simple and incomplete. On the other hand has a very low cost that justifies these limitations. The system interface provides a user-friendly environment for both the user application is for the designer of the database.
2 - as an interface to other systems, Access can be viewed as a tool to avoid writing SQL code, as it captures patterns and simple queries using a graphical representation easily understandable, these inputs are translated into appropriate SQL commands so transparent.
ORACLE is currently one of the world's leading manufacturers of software, and its product offering has the key management system for Oracle database server. Oracle Server is available for a large number of systems. A major strength of Oracle's own product availability on different platforms (including personal computers, local area network server, workstations, mini computers, mainframes and supercomputers, parallel) which makes it easier to integrate base data at different levels in the organization. It is not based on an archaic language understandable only to specialists, thereby changing the nature of the relationship between users and developers. The information is easily accessible by anyone, simply by entering a query in English. In this way, Oracle is used by more groups. The companies' information technology that produces it is the Oracle Corporation in 1977 and fonadata sede in California. ORACLE è stato il primo DBMS commerciale che utilizza il linguaggio di interrogazione strutturato SQL (Structured Query Language), basato sulla lingua inglese.
MySQL è il più diffuso database Open Source basato sul linguaggio SQL. Questo prodotto viene fornito dall'azienda MySQL AB che sviluppa il proprio business erogando servizi basati su MySQL stesso. Anche MySQL è un RDBMS (' Relational DataBase Management System'), ossia un sistema di gestione per database relazionali che offre la possibilità di conservare i dati in diverse tabelle. MySQL si occupa della strutturazione e della gestione a basso livello dei dati stessi in modo da velocizzarne l'accesso, la modifica e the inclusion of new items.
Why use MySQL?
is fast,
is reliable as it was designed to handle lots of data,
is scalable: it can work by using 2 megabytes of RAM to 4GigaByte,
is versatile: its open source nature ensures a version for each platform.
POSTGRESQL is a complete object-relational database is freely licensed, is an excellent alternative to be compared to other free products like MySQL, which in those closed-source like Oracle. E 'was developed by a large community of programmers and supported by various companies and making it free from the corporate policies and market. The programmability of PostgreSQL is its greatest strength and its primary advantage over its competitors.
SQL Server is a relational DBMS from Microsoft. In early versions were used for medium-sized databases, but from the 2000 version was also used to manage large data bases. It uses a variant of the standard SQL language called Transact-SQL T-SQL. SQL Server also supports Open Database Connectivity (ODBC).

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DBMS

A management system database (In English Data Base Management System , abbreviated DBMS) is a software system to manage collections of data that are large, shared and persistent ensuring their reliability and privacy. Like any computer product, a DBMS must be efficient and effective . A data base is a collection of data managed by a DBMS.

Advantages:
  • DBMS allow to consider the data as a common resource of an organization, available to all its sub-components.
  • The database provides a model unificato e preciso della parte del mondo reale di interesse per l'organizzazione.
  • Con l'uso di un DBMS è possibile un controllo centralizzato dei dati, che può essere arricchito di forme standardizzate.
  • La condivisione permette di ridurre ridondanze e inconsistenze.
  • L'indipendenza dei dati, caratteristica fondamentale dei DBMS, favorisce lo sviluppo di applicazioni più flessibili e facilmente modificabili.
Svantaggi:
  • I DBMS sono prodotti costosi, complessi e abbastanza diversi da molti altri strumenti informatici. La loro introduzione comporta quindi notevoli investimenti, diretti (acquisto del prodotto) e indiretti (acquisizione delle risorse hardware e software necessarie).
  • I DBMS forniscono, in forma integrata, una serie di servizi, che sono necessariamente associati ad un costo. Nei casi in cui alcuni di questi servizi non siano necessari, è difficile scorporare quelli effettivamente richiesti dagli altri, e ciò può comportare una riduzione di prestazioni.

Possiamo dire, dunque, che si riscontrano situazioni nelle quali l'adozione di un DBMS può risultare sconveniente per cui, per certe applicazioni, diventa preferibile ricorrere a file ordinari che non a DBMS.

Oggi i principali Data Base in circolazione sono di tipo relazionale, ciò perché praticamente tutti gli insiemi di dati, che corrispondono a entità complesse organizzate come imprese, scuole, associazioni varie, implicano collegamenti tra i vari dati. Ad esempio: ai fornitori sono collegate le merci, agli alunni i corsi, e così via. La norma fondamentale per stabilire relazioni tra tabelle, cioè tra contenitori di dati correlabili, è che il campo di collegamento non deve avere ripetizioni, ossia ogni record deve potere essere identificato in maniera univoca. Il campo che permette l'identificazione di ogni record è detto "chiave primaria" e deve essere comune alle tabelle che si intende correlare.
Si possono stabilire tre tipi di relazione:
uno a uno : si tratta di relazioni tra elementi che hanno a unique match: an element of a table corresponds to one only in another and vice versa;
one to many: are relationships established between a record in a table and more records in another table, but not the contrary, many to many
: a record may be related to more than one record in another table and vice versa, this relationship is usually defined by a third table which is a "bridge" between the two to relate .