Definitions And Overview Of Business Performance Management

Performance management is a management process that brings managers and employees together to work towards an effective and efficient planning, monitoring and reviewing the output of employee using the organization’s goals and objectives as a parameter. It is a management success tool that helps the employees, managers, and the organization to succeed. Performance management makes sure the organization gets what the employer expect from the employees (Mathis & Jackson, 2012).

The logical layer is the planning part of the database. In this logical layer we write

What is Business Intelligence (BI)? BI is the way that using modern data warehouse technology, online analytical processing, and data mining to analysis the data then achieve business value. As a tool, BI is used to deal with the existing data in the enterprise, and convert it into knowledge, analysis and conclusions, and then help the decision-maker to make a right and wise decision.

These frameworks will either take physical duplicates of the records or move them to an off-site area, or they would take a virtual "picture" of the systems documents. These documents well then be overhauled when the following move down is finished, this will mean an association can have the exceptionally most recent of its records restored in the case of a disappointment.

Business intelligence (BI) merges architectures, tools, databases, analytical tools, applications, and methodologies. It also is context free like DSS. BI deduces the connections between business entities by evaluating copious volumes of historical data which supports decisions. BI has four major components consisting of a data warehouse, business analytics, business performance management, and a user interface.

Author Ponniah divided the book into six major parts such as; Overview and Concepts. Planning and Requirements, Architecture and Infrastructure, Data Design and Data Preparation, Information Access and Delivery, and the sixth one is Implementation and Maintenance.

Organizations collect data. This raw data must be analyzed to tease out useful information. The software used to analyze raw data is known as Business Intelligence (BI). BI is comprised of theories and processes such as data mining, online analytical processing, querying and reporting. BI improves decision making, cuts costs and identifies new business opportunities (Mulcahy, 2007). The web data extraction company, Connotate, uses BI systems, specifically dashboards, to focus on more profitable business, saving them time and money while also boosting customer satisfaction rates (6 Real Life., 2013).

Data objects can model relational data or advanced data types such as graphics, movies, and audio. Smalltalk, C++, Java, and others are objects used in object-oriented data. The object-relational is a combination of relational and object-oriented databases. Traditional and advanced data types can be used to construct database management systems. These systems can connect to a company’s website and update records as needed. Database Approach The main purpose of a database is data storage that can be stored and retrieved when needed. A popular common language called structured query language (SQL) is used to store and retrieve data in relational database. This language enables the systems to run a report or modify data or remove the data from the database. A database management system (DBMS) controls all aspects of a database, this is not limited to the creation, maintenance, and use of database. The DBMS ensures proper applications are able to access the database. An important purpose of a DBMS is to maintain the data definitions (data dictionary) for all the data elements in the database. It also enforces data integrity and security measures. Data Models Data models provide a contextual framework and graphical representation that aid in the definition of data elements. In a relational database, the data model lays the foundation for the database and identifies important entities,

Business Intelligence (BI) is the consolidation and analysis of internal data and / or external data for the purpose of effective decision-making. At the core of all BI initiatives is a data warehouse to hold the data and analytics software. The data warehouse stores data from operational systems in the organization and restructures it to enable queries and models to extract decision support reports.

A new trend has emerged in the modern business environment in which companies are seeking to build what is referred to as "Business Intelligence" or BI for short. This has been viewed as one of the most important organizational priorities for many organizations in the last decade and it is unlikely that this trend will end anytime in the near future. The reason for the BI is pretty clear. Companies have been collecting and warehousing various types of data for many years. BI deals with the means in which companies can make better use of the data; often in real time. This allows companies to better harness information to better support organizational goals and their business objectives. Many of the BI technologies that have developed over the years can deliver better reporting mechanisms, dashboards, and different business metrics so companies can spot various trends and gather insights that can allow the company to ultimately become more competitive. Yet, in spite of the obvious appeal of the benefits a Bi system can offer a company, the development of these systems has been a relatively slow and arduous process. This paper will introduce some of the best practices for current BI systems, as well as some of the possibilities for these systems to further develop in the future.

(b) A conceptual schema of all the data generated in the enterprise and how it was all related

software is known as an architectural style that exploits the existing technology and protocols of

Connolly and Carolyn (2004) define a database as a structureordesign that consists of theclient’s data as well as metadata. It is also a persistent, logicallycoherentrepository of inherentlymeaningful data that is relevant to someaspects of therealworld. The database consists of data organized in a systematicway, anditallowseasy retrieval of information, analysis, updating andoutput of data. Thatdata can be in theform of graphics, scripts, reports, text, tables, andsoon. Most of thecomputerapplications are databases at their core. Manycompaniesusuallyhave a lot of data, andsotheyhavebig databases that can handlethatlargeamount of data. It is wherenothe database administratorcomes into playtopensurepropermanagement of the database sothatthe organizational data is safe from anyintrudersor data corruption (Jones, 2014). The database is whatcontrolsthedata of theentireorganization, andany tampering of the databases can culminate to the stoppage of businessoperations.

Many large companies have been using business intelligence (BI) computer software for some years to help them gain competitive advantage. With the introduction of cheaper and more generalized products to the market place BI is now in the reach of smaller and medium sized companies.

The concept of metadata is "data about data" which has simple in principle but very confusing in details. Metadata appears in all kind of file, it acts like a person behind the scene, records many information about the file such as Internet history files have the information about what Web page is accessed at a certain timeline. There are 4 common types of metadata: Internet metadata, Document metadata, File system metadata, Picture metadata.