This document discusses the current trends in data warehousing, business intelligence, and data mining. It also explores the concepts and principles of predictive analytics software. The importance of BI and data handling in business decision-making is highlighted.
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Table of Contents INTRODUCTION...........................................................................................................................1 TASK...............................................................................................................................................1 1. Identification and critically evaluation of current trends in data warehousing, business intelligence and data mining:.......................................................................................................1 Business Intelligence...................................................................................................................1 Data warehousing........................................................................................................................2 Data mining.................................................................................................................................2 2. Demonstration ofthorough knowledge of basic concepts and principles using predictive analytics software:.......................................................................................................................3 CONCLUSION................................................................................................................................4 REFERENCES................................................................................................................................5
INTRODUCTION Business Intelligence (BI)relates to a group of techniques, architects and systems which are accountable to transform raw data/information into valuable information with aim to enhance corporation performance (Minelli, Chambers and Dhiraj, 2013). The study is focused on Panintelligence Limited, whichis provider of services of business intelligence as well as analyticaltools that offers real-time information interfaces for decision making and support business decisions. The study-report, along with its thorough analysis, is centred on the business reporting. TASK 1. Identification and critically evaluation of current trends in data warehousing, business intelligence and data mining: Business Intelligence Business intelligence corresponds to keytechnologies, procedures and methodologies usedtoobtain,incorporate,measureandevaluateactivities.Itiscriticalforintegrating infrastructure together with technology for turning data into actionable insight that is necessary for guiding strategic decisions. Thisallow entities such as Panintelligence to view and evaluate data sets resources that can include strategic results in graphs, charts, workflows, analyses and abstracts and provide their customers with improved state-of-the-art intelligence (IşıK, Jones and Sidorova, 2013). This is important for integrating data modelling, data collection, extraction, technology, and systems that can help organizationsto have a morecomprehensive view of all kind ofdata that can contribute to adjustments in drive, remove inefficiencies, and cause a change the level of dataavailability. Thisallow businesses to document operations in an intelligent manner. Of instance, as data is obtained from various sources, various considerations relevant to the firm's individual context would be presented. This will help them improve decision-making in line with the preparation and evaluation of critical resources that they must have. Here in this context Panintelligence offers wide range of apps and systems which enable companies in gaining control and insights over operation by effective analysis of each aspect of processes. Here under this, for understanding the need business intelligence, discussion on business reporting is essential. 1
Businessreportingisreferringtoasamechanismofqualityimprovisingand dissemination of information offered by businesses to their customers and relevant parties for formulating smarter decisions. When organizing, this serves as an essential feature as it includes sharing information and details to their particular viewers. An example may be considered inthis aspect such as providing specific services through Panintelligence in order to include business plans, customer support feedback (to staff such that their teams can improve their services) including consumer survey outcomes toclients as well as interested parties. The focus then switched to frameworks that serve as key drivers of value together with contextual information specific to approaches, risks, prospects and projects.Business reporting indicates the insight gained by concentrating on particular business-related issues. It includes different ways by which suchdata is being produced for the layout of the BI. Data warehousing Data warehousing is definedas the mechanism concerned with gathering and storing data from numerous different channels to make useful insights into wholebusiness framework. Usually it involves design-related operations as well as majorsourceof data warehouse usage. This is developed by incorporating data from diverse channels that are important for facilitating ad hoc inquiries and predictive analysis that could aid in decision-making processes adoption and implementation. Data warehousing as well asbusiness intelligence are employed to characterize activities in the internally or externally database linked with the handling of corporate or businessdata. In this context, Organization may employ cloud technology to assure on-demand accessibility of data andinfrastructure services that include computational data transmission processing without any form of organized management. As instance, anorganization can use cloud capacity to store major information in order and share it with employees or managing personnel working at different locations remotely. Usually, data warehousing mechanism is used with regard to business analysis and reporting processesbecause it contains information across different systems which helps business intelligence companies to gain insight throughout their processes and can support them in datamining processes (Glider, Hix and Zalewski, ZeeWise, 2016). Data mining Data mining is characterized as the procedure used by corporations to process raw data into useful information. This helps to locate secret, relevant trends as well as probable trends 2
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within large datasets. This is necessary for recognizing an unresolved connection with data that was earlier / unpredicted. This functions as a collaborative capacity that makes use of AI, algorithms, database technologies and stats.This canofferorganisationan overall view into fraud detection,technicalbusinessfindings,branding, and so on. This would help in the detection of correlations, trends and anomalies between large datasets for forecasting effectsPanintelligence mayusedifferentapproachestooptimizerevenue-relatedknowledge,improviseclient relationships, mitigate costs, eliminate risks, and much more. Via this, business andmarket analysis can be accomplished because data miningcan help them collect the data from which information will be collected. Via this service, they will provide sufficient market reports that will contribute to effective decisions (Demirkan and Delen, 2013). Thus, as per above discussion it has been analysed that BI, Data mining and warehousing is essential need of business. In current competitive market and technological environment, use of all the discussed aspects in business is significant for achieving predetermined objectives. 2. Demonstration ofthorough knowledge of basic concepts and principles using predictive analytics software: Predictive analytics involves the application of statistics, statistical techniques as well as machine learningstechniqueto assess the probability in potential outcomes dependent on past evidence. The aim is going through understanding what happens and have the strongest prediction of what is going and occur in the nearfuture. Artificial intelligence, predictive modelling as well as thedata mining offer a broad variety of tools for analysing current andhistoricalfacts/detailsforforecastingupcomingorotheruncertaincircumstancesis characterized aspredictive analytics software. Thissupport Panintelligence in formulating its findings and communicating with its customers in an effective manner by recognizing their business place and what they might put through from which their offerings can be strengthened. Essentially, information should be given in the sense of the past and actions will be taken in long term future by allowing usage of it. It also means the application of technologies like cloud storage so that information relevant to it can be obtained as needed (Babu, 2012). Organizations shiftingto predictive analyticsto effectively overcome complex challenges and to discover new possibilities. Following are key aspects of this, as follows: FraudDetection:Variousmonitoringapproachestogetherwillenhancetrend recognition and deter illegal activity. When cybersecurity isincreasing problem, high- 3
performance behavioural analytics is analyzing all activities on a network in real time to detectirregularitiesthatcouldsignifymalware,zero-dayvulnerabilities,including advanced persistent risks. Marketing campaigns optimisation:Predictive analyticssoftwareare being used to evaluate consumer preferences or transactions, and to encourage incentives for cross- selling.Predictivemodelsallowcompaniestorecruit,maintain,andexpandmost profitable clients base. OperationsImprovisation:Many organizationsuse predictiveanalysissoftwarein stock forecasting and asset control. LikeAirlines use these softwareto determine prices for their fares. Hotels aim to forecastnumber of visitors to optimize occupancy and raise sales for every given night. Risk Reduction:Credit ratings are used to determine the average probability of a customer for transactions and arewell-known instanceof predictive analytics. Credit score isnumbers created by this softwareintegrating all the credit worthiness information applicable to an entity. Other applications related to the event include premiums for compensation and returns. CONCLUSION From above study it has been articulated that BI and data handling makes a robust impact on corporation's financial, organizational, and strategical businessdecisions. BI 'sis responsible for conducting out regularmonitoring of fiscal and functional information for businesses as well as supplying ongoing information fororganisationdecision-makers to control operations. 4
REFERENCES Books and Journals: Minelli, M., Chambers, M. and Dhiraj, A., 2013.Big data, big analytics: emerging business intelligence and analytic trends for today's businesses(Vol. 578). John Wiley & Sons. IşıK, Ö., Jones, M.C. and Sidorova, A., 2013. Business intelligence success: The roles of BI capabilities and decision environments.Information & Management,50(1), pp.13-23. Glider, C.S., Hix, J. and Zalewski, B.J., ZeeWise Inc, 2016.Systems and methods for collection and consolidation of heterogeneous remote business data using dynamic data handling. U.S. Patent 9,411,864. Demirkan, H. and Delen, D., 2013. Leveraging the capabilities of service-oriented decision supportsystems:Puttinganalyticsandbigdataincloud.DecisionSupport Systems,55(1), pp.412-421. Babu, K.V.S.N., 2012. Business intelligence: Concepts, components, techniques and benefits. Components, Techniques and Benefits (September 22, 2012). 5