Online Analytical Processing (OLAP) – Definition, Architecture and Functionality

OLAP Council (1997) define Online Analytical Processing (OLAP) as a group of decision support system that facilitate fast, consistent and interactive access of information that has been reformulate, transformed and summarized from relational dataset mainly from data warehouse into Multi-Dimensional Databases (MDDB) which allow optimal data retrieval and for performing trend analysis. OLAP is an important concept for strategic database analysis. OLAP have the ability to analyze large amount of data for the extraction of valuable information. Analytical development can be of business, education or medical sectors. The technologies of data warehouse, OLAP, and analyzing tools support that ability. Online Analytical Processing (OLAP) enable discovering pattern and relationship contain in business activity by query tons of data from multiple database source systems at one time. Processing database information using OLAP required an OLAP server to organize and transformed and builds MDDB. MDDB are then separated by cubes for client OLAP Continue reading

Uses and Risks of Personal Data in Big Corporations

Big Data has taken a huge role in art in creating today’s Technological Revolution. It is a phrase coined to describe the exponential volume of data we currently hold. Data is collected from a number of sources including cell phones, applications, databases, servers, etc. In return, it can then be used to find trends, patterns, and connections specifically related to how humans behave along with their interactions. This information includes likes, dislikes, preferences, and search and buyer history and is not limited to personal data such as birthdate, social security number, home address, and much more. Corporations across the globe have found new ways to use this data in everyday business functions. The collection of Big Data can be used to a company’s advantage in marketing, finance, and Government. Despite the fact that in a few situations Big Data can be hard to control, it can possibly enable organizations to Continue reading

Text Mining Concept in Data Mining

Data mining is the process of extracting patterns from data. Data mining is becoming an increasingly important tool to transform the data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud detection and scientific discovery. Data mining can be applied on a variety of data types. Data types include structured data (relational), multimedia data, free text, and hypertext. Nowadays, text is the most common and convenient way for information exchange. This due to the fact that much of the world’s data is contained in text documents (newspaper articles, emails, literature, web pages, etc.). The importance of this way has led many researchers to find out suitable methods to analyze natural language texts to extract the important and useful information. In comparison with data stored in structured format (databases), texts stored in documents is unstructured and to deal with such data, a Continue reading

Understanding Different Eras of Data Analytics

Back in the 1950’s and 1970’s, the role of information systems (IS) was to support operational functions within the organization. IS was primarily used in transaction applications, involving accounting transactions. The focus was on IS efficiency and IS effectiveness. With the advent of internet and as information technology (IT) advanced over time, the methods to assess the data and the amount that could be processed increased significantly. Data became more quickly accessible and could be processed at greater speeds. This assisted organizations and managers to report and run data more effectively. Information systems have helped organizations improve their decision making process and help managers reduce the risk involved. The way in which Data Analytics field has evolved in terms of capabilities and volume is of significance. Analytics has evolved and has been perceived differently across different periods in time or eras. ANALYTICS 1.0 – THE ERA OF BUSINESS INTELLIGENCE AND TRADITIONAL Continue reading

The Difference Between Traditional File Systems and DBMS

Traditional File Systems File-based systems were an early attempt to computerize the manual filing system. File-based system is a collection of application programs that perform services for the end-users, such as updating, insertion, deletion adding new files to database etc. Each program defines and manages its data. When a computer user wants to store data electronically they must do so by placing data in files. Files are stored in specific locations on the hard disk (directories). The user can create new files to place data in, delete a file that contains data, rename the file, etc which is known as file management; a function provided by the Operating System (OS). Database Management System The improvement of the File-Based System (FBS) was the Database Management System (DBMS) which came up in the 60’s. (DBMS) consists of software that operates databases, providing storage, access, security, backup and other facilities. This system can Continue reading

Data Mining Functionalities

Data mining has an important place in today’s world. It becomes an important research area as there is a huge amount of data available in most of the applications. This huge amount of data must be processed in order to extract useful information and knowledge, since they are not explicit. Data Mining is the process of discovering interesting knowledge from large amount of data. The kinds of patterns that can be discovered depend upon the data mining tasks employed. By and large, there are two types of data mining tasks: descriptive data mining tasks that describe the general properties of the existing data, and predictive data mining tasks that attempt to do predictions based on inference on available data. The data mining functionalities and the variety of knowledge they discover are briefly presented in the following list: Characterization: It is the summarization of general features of objects in a target Continue reading