Business Intelligence: Data and Text Management Instructor: Bajuna Salehe Web:

The focus IT applications cannot be done with some kind of data. Without data you cannot have most IT applications, nor can you make good decisions. Hence data management should in the core of any business organisation.

The focus Likewise organisations produce more texts in day to day tasks. These texts are in form of documents. Therefore document management is also key issue to be considered by organisations.

Data Problems and Difficulties Various reasons render to difficultness in managing data: The amount of data increase exponentially with time. Data are scattered throughout the organizations and are collected by many individuals using several methods and devices. Continuous increasing of external data which must be considered in making organisational decisions.

Data Problems and Difficulties Data security, quality, and integrity are critical and yet are jeopardised. Selecting data management tools can be a major problems because of the huge number of products available.

Solutions Various means can be used in improving data management. These includes: Data warehouse, intranets, extranets, and some web technologies. The purpose of data management is to ease the burden of maintaining data which is a critical asset of an organisation.

Data and Database Administration Data Administration: A high-level function that is responsible for the overall management of data resources in an organization, including maintaining corporate-wide definitions and standards. Database Administration: A technical function that is responsible for physical database design and for dealing with technical issues such as security enforcement, database performance, and backup and recovery.

Data administration functions Data policies, procedures, standards Planning Data conflict (ownership) resolution Managing the data repository

Database administration functions Selection of hardware and software Installing/upgrading DBMS Tuning database performance Improving query processing performance Managing data security, privacy, and integrity Data backup and recovery

Data Life Cycle and Data Sources Businesses do not run on raw data but they run on data that have been processed to information and knowledge which managers apply to business problems and opprtunities. Due to difficulties of managing data, getting knowledge from large accumulated data is not an easy task.

Data Life Cycle and Data Sources The transformation of data into knowledge and solutions is accomplished in several ways. Data life cycle describes how to accomplish this process. The figure below demonstrate Data Life Cycle

Data Life Cycle

Data Sources The data life cycle begins with acquisition of data from data sources Data sources can be classified into: –Internal Data Sources –Personal Data Sources –External Data Sources

Data Sources Internal data sources focus on internal data. That is data about people, products, services, and processes. –E.g. Data about employees and their pay stored in corporate database. –Data about equipment and machinery.

Data Sources Personal data: Refers to data from Information System users or other corporate employees who document their own expertise by creating personal data. External Data: These ranges from commercial database to sensors and satellites. –Also government reports, data available on CD ROMs, Internet servers, etc.

Data Security Data security refers to how to prevent someone else from knowing the data contents. The data security can be categorised into two aspects: –Data security in transfer –Data security in storage

Data security in transfer Refers how to protect data when it is transferred from one point to another. Data security in transfer is accomplished by using: –Encryption – transform data into a different, unintelligible form. –Decryption – restore the original data from the encrypted form. In encryption plaintext refer to original data and ciphertext refer to encrypted data.

Data security in storage Data security in storage refers to database security. Database security is the protection of data against accidental or intentional loss, destruction, or misuse. There is an increase in difficulty of securing data in the database due to the Internet access and client server technology.

Possible locations of data security threats

Threats to data security can come from: Accidental losses - attributable to Human error, software or hardware failure – tackle using procedures on user authorisation, uniform software installation procedures, hardware maintenance schedules Theft and fraud – attention should be focussed on all the locations in the previous Fig. (control of physical access, firewalls etc.)

Threats to data security can come from: Loss of privacy (personal data) and loss of confidentiality (corporate data) Loss of data integrity – invalid/corrupt data – need established backup/recovery procedures Loss of availability (through, e.g. sabotage)

Data management software should have these security features: Views or subschemas which restrict user views of the database (discussed previously) Integrity controls which are enforced by the DBMS during querying and updating Authorization rules identifying users and restricting actions they can take User-defined procedures defining additional constraints.

Data management software should have these security features: Encryption procedures for encoding data in an unrecognisable form Backup, journalizing, and checkpointing capabilities which facilitate recovery procedures.