• What is data management?

Data management is the development and execution of architectures, policies, practices and procedures in order to manage the information lifecycle needs of an enterprise in an effective manner.

• Describe data management issues

The following are some briefly described issues or problems that might arise in the management of data.

• Technical data not recorded properly.

This occurs in research programs when the data are not recorded in accordance with the accepted standards of the particular academic field. This is a very serious matter. Should another researcher wish to replicate the research, improper recording of the original research would make any attempt to replicate the work questionable at best. Also, should an allegation of misconduct arise concerning the research, having the data improperly recorded will greatly increase the likelihood that a finding of misconduct will be substantiated.

• Technical data management not supervised.

In this situation the principal investigator might inappropriately delegate his/her oversight responsibilities to someone in his/her lab that is insufficiently trained. Another situation might arise if the principal investigator simply does not dedicate the appropriate time and effort to fulfill responsibilities related to proper data management.

• Data not maintained at the institution.

This situation could occur in a collaboration in which all data is maintained by one collaborator. It would be particularly problematical if each collaborator is working under a sponsored project in which their institutions are responsible for data management. In other cases, researchers might maintain data in their homes, and this can also present problems of access.

• Financial or administrative data not maintained properly.

 This basically means that the information is not maintained in sufficient detail, is inaccurately recorded, or not maintained in identifiable files. External auditors or reviewers would find these matters to be a serious breach of exercising appropriate responsibility regarding the proper stewardship of funds.

• Data not stored properly.

This could occur with research, financial, and administrative data. Careless storage of the data that could permit its being destroyed or made unusable is a significant matter. In such case, the institution and/or researcher have acted negligently, have not fulfilled their stewardship duties, and have violated sponsor policies as well as the terms of the sponsored agreement.

• Data not held in accordance with retention requirements.

 As noted previously, it is absolutely essential that those involved with sponsored projects know how long different kinds of data must be retained to satisfy all compliance requirements as well as to offer appropriate support in the event of lawsuits or disputes over intellectual property.

• Data not retained by the institution.

 This is a major problem that would occur if a researcher leaves the institution and takes the original research data and does not leave a copy at the institution. In the event access is needed, it places the institution in an untenable position since it has not fulfilled its fiduciary responsibility to the sponsor.

1.3 What is a database management system (DBMS)?

A Database Management System or DBMS is a single or set of computer programs that are responsible for creating, editing, deleting and generally maintaining a database or collection of data records. They type of database management system is determined by the database model. A database model is the manner in which the data collection is stored, managed and administered.

1.3.1 Ways in which database management systems (DBMS) can address the issues   mentioned above.

The database management system has a number of advantages as compared to traditional computer file-based processing approach. The DBA must keep in mind these benefits or capabilities during databases and monitoring the DBMS.
The Main advantages of DBMS are described below.

Data independence

A DBMS provides an abstract view of data in such a manner that applications are independent from how the data is physically stored. The separation of data structure of database from the application program that uses the data is called data independence. In DBMS, you can easily change the structure of database without modifying the application program

Efficient data access

A DBMS has advantageous techniques that leverages I/O throughput.

Data integrity and security

A DBMS enforces integrity constraints on the data, thus preventing erroneous data. Also, a DBMS enforces access controls that govern what data is visible to a user, role, or group of users.

Data administration

Centralized administration enables experienced DBMS administrators to manage data, tune the DBMS in accordance to its usage, and minimize data redundancy.

Concurrent access and crash recovery

A DBMS enables concurrent accesses to data, thus two concurrent actions will not influence each other. Further, the DBMS has built-in fault tolerance and fault isolation that prevent further propagation of eventual failures or erroneous data.

Controlling Data Redundancy 

In non-database systems each application program has its own private files. In this case, the duplicated copies of the same data are created in many places. In DBMS, all data of an organization is integrated into a single database file. The data is recorded in only one place in the database and it is not duplicated.

Sharing of Data

In DBMS, data can be shared by authorized users of the organization. The database administrator manages the data and gives rights to users to access the data. Many users can be authorized to access the same piece of information simultaneously. The remote users can also share same data. Similarly, the data of same database can be shared between different application programs.

Data Consistency 

By controlling the data redundancy, the data consistency is obtained. If a data item appears only once, any update to its value has to be performed only once and the updated value is immediately available to all users. If the DBMS has controlled redundancy, the database system enforces consistency.

Integration of Data

In Database management system, data in database is stored in tables. A single database contains multiple tables and relationships can be created between tables (or associated data entities). This makes easy to retrieve and update data.

Integration Constraints

Integrity constraints or consistency rules can be applied to database so that the correct data can be entered into database. The constraints may be applied to data item within a single record or the may be applied to relationships between records.

Data Security

Form is very important object of DBMS. You can create forms very easily and quickly in DBMS. Once a form is created, it can be used many times and it can be modified very easily. The created forms are also saved along with database and behave like a software component. A form provides very easy way (user-friendly) to enter data into database, edit data and display data from database. The non-technical users can also perform various operations on database through forms without going into technical details of a database.

Report Writers

Most of the DBMSs provide the report writer tools used to create reports. The users can create very easily and quickly. Once a report is created, it can be used may times and it can be modified very easily. The created reports are also saved along with database and behave like a software component.

Control Over Concurrency 

In a computer file-based system, if two users are allowed to access data simultaneously, it is possible that they will interfere with each other. For example, if both users attempt to perform update operation on the same record, then one may overwrite the values recorded by the other. Most database management systems have sub-systems to control the concurrency so that transactions are always recorded with accuracy.

Backup and Recovery Procedures 

In a computer file-based system, the user creates the backup of data regularly to protect the valuable data from damage due to failures to the computer system or application program. It is very time consuming method, if amount of data is large. Most of the DBMSs provide the ‘backup and recovery’ sub-systems that automatically create the backup of data and restore data if required.

2.1 Commonly implemented features of commercial database management systems.

A typical DBMS has the following features:

• Provides a way to structure data as records, tables, or objects
• Accepts data input from operators and stores that data for later retrieval
• Provides query languages for searching, sorting, reporting, and other “decision support” activities that help users correlate and make sense of collected data
• Provides multiuser access to data, along with security features that prevent some users from viewing and/or changing certain types of information
• Provides data integrity features that prevent more than one user from accessing and changing the same information simultaneously
• Provides a data dictionary (metadata) that describes the structure of the database, related files, and record information
• Represents complex relationship between data
• Controls data redundancy.
• Enforces user defined rules.
• Ensures data sharing.
• It has automatic and intelligent backup and recovery procedures.
• It has central dictionary to store information.
• Pertaining to data and its manipulation.
• It has different interfaces via which user can manipulate the data.
• Enforces data access authorization.

3.1 Describe the different type of DBMS`s.

The various database management systems based on these data models are:

3.1.1   Relational Database Management Systems

Relational database management systems are the most widely used database management systems today. They are relatively easy to use. Relational database management systems are named so because of the characteristic of normalizing the data which is usually stored in tables. The relational model relies on normalizing data within rows and columns in tables. The data can be related to other data in the same table or other tables which has to be correctly managed by joining one or more tables. Relational models may be somewhat less efficient than other models; however this may not be a problem with the processing power and memory found in modern computers. Data in this type of model is stored is fixed predefined structures and are usually manipulated using Structured Query Language (SQL). Relational database management systems include Oracle, Ms SQLServer, IBM DB2, mySQL, SQLite and PostgreSQL among others.

3.1.2  Flat File Based Database Management Systems

Flat File based database management systems are probably the simplest of them all. These are sometimes called Flat models. These come in human readable text formats as well as in binary formats. These are ideal for stand alone applications, holding software configuration and native format storage models. Flat files in a formatted row and column model rely on assumptions that every item in a particular model consists of the same data. One common example of this type of database is the CSV (Comma Separated Values) and another is a spreadsheet such as Ms Excel.

• Hierarchical Database Management Systems

Hierarchical database management systems operate on the parent child tree-like model. These normally have a 1:N relationship and are good for storing data with items describing attributes, features and so on. These could store a book with information on chapters and verses. They can also be used to store a database of songs, recipes, models of phones and anything that can be stored in a nested format. Hierarchical database management systems are not quite efficient for various real world operations. One such example of a Hierarchical database management system is a XML document. Here is an example of a Flash application manipulating a Hierarchical XML data model.

• Network Database Management Systems

A Network database management system uses a data model similar to Hierarchical database management systems The major difference here is that the tree structure in the Network models can have a many parent to many child relational model. The Network model structure is based on records and sets and most of these databases use SQL for manipulation of their data. Network database management systems tend to be very flexible but are rarely used ad were very quite common in the1960s and 1970s. Searching for an item in this model requires the program to traverse the entire data set which is quit cumbersome. These have mainly been replaced by Relational database management systems in today’s modern computing.

• Object-oriented Database Management Systems

Object-oriented database management systems borrow from the model of the Object-oriented programming paradigm. In this database model, the Object and its data or attributes are seen as one ad accessed through pointers rather than stored in relational table models. Object-oriented database models consist of diverse structures and are quite extensible. This data model was designed to work closely with programs built with Object-oriented programming languages thereby almost making the data and the program operate as one. With this model applications are able to treat the data as native code. There is little commercial implementation of this database model as it is still developing. Examples of Object-oriented database management systems include IBM DB4o and DTS/S1 from Obsidian Dynamics.

4.1 Review DBMS end-user tools.

End-user databases consist of data developed by individual end-users. Examples of these are collections of documents, spread sheets, presentations, multimedia, and other files. Several products exist to support such databases. Some of them are much simpler than full-fledged DBMSs, with more elementary DBMS functionality.

• A federated database systemcomprises several distinct databases, each with its own DBMS. It is handled as a single database by a federated database management system (FDBMS), which transparently integrates multiple autonomous DBMSs, possibly of different types (in which case it would also be a heterogeneous database system), and provides them with an integrated conceptual view. Sometimes the term multi-database is used as a synonym to federated database, though it may refer to a less integrated (e.g., without an FDBMS and a managed integrated schema) group of databases that cooperate in a single application. In this case typically middleware is used for distribution, which typically includes an atomic commit protocol (ACP), e.g., the two-phase commit protocol, to allow distributed (global) transactions across the participating databases.
• A graph databaseis a kind of NoSQL database that uses graph structures with nodes, edges, and properties to represent and store information. General graph databases that can store any graph are distinct from specialized graph databases such as triplestores and network databases.
• In a hypertextor hypermedia database, any word or a piece of text representing an object, e.g., another piece of text, an article, a picture, or a film, can be hyperlinked to that object. Hypertext databases are particularly useful for organizing large amounts of disparate information. For example, they are useful for organizing online encyclopedias, where users can conveniently jump around the text. The World Wide Web is thus a large distributed hypertext database.
• A knowledge database(abbreviated KB, kb or Δ^[23][24]) is a special kind of database for knowledge management, providing the means for the computerized collection, organization, and retrieval of knowledge. Also a collection of data representing problems with their solutions and related experiences.
• A mobile databasecan be carried on or synchronized from a mobile computing device.
• Operational databasesstore detailed data about the operations of an organization. They typically process relatively high volumes of updates using transactions. Examples include customer databases that record contact, credit, and demographic information about a business’ customers, personnel databases that hold information such as salary, benefits, skills data about employees, enterprise resource planning systems that record details about product components, parts inventory, and financial databases that keep track of the organization’s money, accounting and financial dealings.
• A parallel databaseseeks to improve performance through parallelization for tasks such as loading data, building indexes and evaluating queries.

The major parallel DBMS architectures which are induced by the underlying hardware architecture are:

• Shared memory architecture, where multiple processors share the main memory space, as well as other data storage.
• Shared disk architecture, where each processing unit (typically consisting of multiple processors) has its own main memory, but all units share the other storage.
• Shared nothing architecture, where each processing unit has its own main memory and other storage.
• Probabilistic databasesemploy fuzzy logic to draw inferences from imprecise data.
• Real-time databasesprocess transactions fast enough for the result to come back and be acted on right away.
• A spatial databasecan store the data with multidimensional features. The queries on such data include location based queries, like “Where is the closest hotel in my area?”.
• A temporal databasehas built-in time aspects, for example a temporal data model and a temporal version of SQL. More specifically the temporal aspects usually include valid-time and transaction-time.
• A terminology-orienteddatabase builds upon an object-oriented database, often customized for a specific field.
• An unstructured datadatabase is intended to store in a manageable and protected way diverse objects that do not fit naturally and conveniently in common databases. It may include email messages, documents, journals, multimedia objects, etc. The name may be misleading since some objects can be highly structured. However, the entire possible object collection does not fit into a predefined structured framework. Most established DBMSs now support unstructured data in various ways, and new dedicated DBMSs are emerging.

4.1.2 Relationship between Visual Database Tools and Databases

The database management system (DBMS) affects the available tool features.The type of database you connect to can affect the behavior of the tools, because different commercial DBMS products offer different features. The Visual Database Tools are sensitive to the features present in the DBMS you connect to. Thus, some dialog boxes and property pages will vary depending on the underlying DBMS. This variance might be as simple as different lists of values in a drop-down list, or it might be as substantial as the presence or absence of some dialog-box controls.

In addition, the Query and View Designer will construct SQL in the particular dialect of the underlying DBMS to which you are connected.

The tools retain your work in memory

The Visual Database Tools retain local copies of your work before you save it to the database. This means that you can make changes freely without immediately affecting the underlying database. Thus, you can experiment with “what if” scenarios.

When you finish your modifications to any database object, you have three choices:

• You can save the changes, propagating them to the database. You can save database objects such as tables, diagrams, triggers, indexes, stored procedures, user-defined functions.
• You can create a script file containing the SQL code generated by your changes. Later, you or another user can run this script file to modify the database accordingly. For more information, see Saving a Change Script.
• You can discard your changes. In Query and View Designer, discarding modifications is straightforward; simply close the window without saving your work. But in Database Designer and Table Designer, there are special considerations. 

The Visual Database Tools employ several strategies for retaining local copies of your work. One strategy applies to the work you do with the Database Designer and Table Designer. 

The tools support multiuser environments

You can work with Visual Database Tools in a multiuser environment — an environment in which more than one user can simultaneously connect to and change the database. When you save a modified database object, the Visual Database Tools verify that the object has not been modified since you last saved it. You might need to reconcile your changes with changes already made by another user.