Business intelligence comprises of tools and applications that are leverages software and services to translate data into intelligent actions for strategic, tactical and operational decisions. The intelligent business solution facilitates and develops the service provided to the market researchers, saves time and effort needed to identify the customers predict demand and manage production more efficiently, ability to explore possibilities to increase revenue. The purpose of this paper is using business intelligence solutions for forecasting in Marketing Researches. The intelligence solutions are helping the market researchers to achieve efficiency, effectiveness, and differentiation.
Business Intelligence for Small Scale IT Based Entrepreneurship in Malaysiaijtsrd
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"Small scale businesses are the heart of Malaysian economy. It is but proper to support these businesses with new technology for their information needs. One such technology is business intelligence. Although it was developed with large businesses in mind, new processes in data management has made things possible for small business to use this technology. Small IT based entrepreneurship in Malaysia may yet to benefit from the use of business intelligence in managing information in their organizations. The paper is an exploratory study to apply business intelligence in small scale IT based business processes to get the maximum benefit from large amount of data for informed decision making. Alinaswe Sikana | Amanda Percy Kinsi | Mia Torres-Dela Cruz | Illiana Azizan ""Business Intelligence for Small-Scale IT-Based Entrepreneurship in Malaysia"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Advanced Engineering and Information Technology , November 2018, URL: https://www.ijtsrd.com/papers/ijtsrd19143.pdf
Paper URL: https://www.ijtsrd.com/management/business-administration/19143/business-intelligence-for-small-scale-it-based-entrepreneurship-in-malaysia/alinaswe-sikana"
Background: As a result of enormous progress in the information technology and communications, several
organizations adopt business intelligence (BI) applications in order to cope with the development in
business mechanisms, staying at the marketplace, competition, customer possession and retention.
The rapid growing capabilities of both generating and gathering data has created an imperative
necessity for new techniques and tools can intelligently and automatically transform the processed data in
to a valuable information and knowledge. Knowledge management is a cornerstone in selecting accurate
information at the appropriate time from many relevant resources.
Objective: The major Objective of this research is to "examine the impact of business intelligence on
employee's knowledge sharing at the Jordanian telecommunications company (JTC)".
Design/methodology/approach: A review of the literature serves as the basis for measuring the impact of
business intelligence using knowledge sharing scale. The study sample consisted of administrators,
technical staff, and senior managers.75 questionnaires were distributed in the site of JTC. (70)
Questionnaires were collected. (63) Found statistically usable for this study representing a response rate
of (84 %).
Findings: Most important findings for this study demonstrate that business intelligence tools respectively
(OLAP, Data Warehousing, and Data Mining)are highly effect on employee knowledge sharing.
Originality/ Value: Business Intelligence play a significant role in obtaining the underlying knowledge in
the organization, through optimum utilization of data sources the internal and external alike. Several
researches addressed the importance of integrating business intelligence with knowledge management,
little of these researches addressing the impact of business intelligence on knowledge sharing. This study
has tried to address this need.
Business Intelligence for Small Scale IT Based Entrepreneurship in Malaysiaijtsrd
Â
"Small scale businesses are the heart of Malaysian economy. It is but proper to support these businesses with new technology for their information needs. One such technology is business intelligence. Although it was developed with large businesses in mind, new processes in data management has made things possible for small business to use this technology. Small IT based entrepreneurship in Malaysia may yet to benefit from the use of business intelligence in managing information in their organizations. The paper is an exploratory study to apply business intelligence in small scale IT based business processes to get the maximum benefit from large amount of data for informed decision making. Alinaswe Sikana | Amanda Percy Kinsi | Mia Torres-Dela Cruz | Illiana Azizan ""Business Intelligence for Small-Scale IT-Based Entrepreneurship in Malaysia"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Advanced Engineering and Information Technology , November 2018, URL: https://www.ijtsrd.com/papers/ijtsrd19143.pdf
Paper URL: https://www.ijtsrd.com/management/business-administration/19143/business-intelligence-for-small-scale-it-based-entrepreneurship-in-malaysia/alinaswe-sikana"
Background: As a result of enormous progress in the information technology and communications, several
organizations adopt business intelligence (BI) applications in order to cope with the development in
business mechanisms, staying at the marketplace, competition, customer possession and retention.
The rapid growing capabilities of both generating and gathering data has created an imperative
necessity for new techniques and tools can intelligently and automatically transform the processed data in
to a valuable information and knowledge. Knowledge management is a cornerstone in selecting accurate
information at the appropriate time from many relevant resources.
Objective: The major Objective of this research is to "examine the impact of business intelligence on
employee's knowledge sharing at the Jordanian telecommunications company (JTC)".
Design/methodology/approach: A review of the literature serves as the basis for measuring the impact of
business intelligence using knowledge sharing scale. The study sample consisted of administrators,
technical staff, and senior managers.75 questionnaires were distributed in the site of JTC. (70)
Questionnaires were collected. (63) Found statistically usable for this study representing a response rate
of (84 %).
Findings: Most important findings for this study demonstrate that business intelligence tools respectively
(OLAP, Data Warehousing, and Data Mining)are highly effect on employee knowledge sharing.
Originality/ Value: Business Intelligence play a significant role in obtaining the underlying knowledge in
the organization, through optimum utilization of data sources the internal and external alike. Several
researches addressed the importance of integrating business intelligence with knowledge management,
little of these researches addressing the impact of business intelligence on knowledge sharing. This study
has tried to address this need.
The Japanese are masters of business intelligence, and some American companies were founded on the eyes and ear's culture. Business intelligence is rapidly becoming a major source to achieve competitive advantage. This innovation is a legitimate business function, and businesses over time have collected data about a whole range of issues - mostly about their competitors. According to Greene (1966) business intelligence is processed information of interest to management, about the present and future environment in which the business is operating.
IT and business leaders must increase their efforts to evolve from traditional BI tools, that focus on descriptive analysis (what happened), to advanced analytical technologies, that can answer questions like âwhy did it happenâ, âwhat will happenâ and âwhat should I doâ.
"While the basic analytical technologies provide a general summary of the data, advanced analytical technologies deliver deeper knowledge of information data and granular data.â - Alexander Linden, Gartner Research Director
The reward of a smarter decision making process, based on Data Intelligence, is a powerful driver to improve overall business performance.
Wiseminer is the only and most efficient end-to-end Data Intelligence software to help you make smarter decisions and drive business results.
Contact us: info@wiseminer.com
Learn about Addressing Storage Challenges to Support Business Analytics and Big Data Workloads and how Storage teams, IT executives, and business users will benefit by recognizing that deploying appropriate storage infrastructure to support a wide range of business analytics workloads will require constant evaluation and willingness to adjust the infrastructure as needed. For more information on IBM Storage Systems, visit http://ibm.co/LIg7gk.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
Digital Enterprise Journal identified 20 technology vendors that are providing innovative solutions for extracting business context from IT monitoring data and enabling multiple non-IT job roles to make better informed decisions. It should be noted that the primary purpose of the majority of these solutions is still IT performance monitoring, but their ability to provide business insights make them more valuable for end-user organizations, especially those that are looking to become digital businesses.
The need, applications, challenges, new trends and
a consulting perspective
(Why is Big Data a strategic need for optimization of organizational processes especially in the business domains and what is the consultantâs role?)
With every transaction and activity, organizations churn out data. This process happens even in the case of idle operation. Hence, data needs to be effectively analyzed to manage all processes better. Data can be used to make sense of the current situation and predict outcomes. It also can be used to optimize business processes and operations. This is easier said than done as data is being produced at an unprecedented rate, huge volumes and a high degree of variety. For the outcome of the data analysis to be relevant, all the data sets must be factored in to the analysis and predictions. This is where big data analysis comes in with its sophisticated tools that are also now easy on the pocket if one prefers the open source.
The future of high potential marketing lead generation would be based on big data. Virtually every business vertical can benefit from big data initiatives. Even those without deep pockets can use the cloud model for business analytics/big data analysis.
Some challenges remain to be addressed to engender large scale adoption but the current benefits outweigh the concerns.
India has seen a massive growth in big data adoption and the trend will grow though it is generally amongst the bigger players. As quality of data improves and customer reluctance to being honest when they volunteer data reduces, the forecasts will become more accurate and Big Data will have come to its rightful place as a key enabler.
The Japanese are masters of business intelligence, and some American companies were founded on the eyes and ear's culture. Business intelligence is rapidly becoming a major source to achieve competitive advantage. This innovation is a legitimate business function, and businesses over time have collected data about a whole range of issues - mostly about their competitors. According to Greene (1966) business intelligence is processed information of interest to management, about the present and future environment in which the business is operating.
IT and business leaders must increase their efforts to evolve from traditional BI tools, that focus on descriptive analysis (what happened), to advanced analytical technologies, that can answer questions like âwhy did it happenâ, âwhat will happenâ and âwhat should I doâ.
"While the basic analytical technologies provide a general summary of the data, advanced analytical technologies deliver deeper knowledge of information data and granular data.â - Alexander Linden, Gartner Research Director
The reward of a smarter decision making process, based on Data Intelligence, is a powerful driver to improve overall business performance.
Wiseminer is the only and most efficient end-to-end Data Intelligence software to help you make smarter decisions and drive business results.
Contact us: info@wiseminer.com
Learn about Addressing Storage Challenges to Support Business Analytics and Big Data Workloads and how Storage teams, IT executives, and business users will benefit by recognizing that deploying appropriate storage infrastructure to support a wide range of business analytics workloads will require constant evaluation and willingness to adjust the infrastructure as needed. For more information on IBM Storage Systems, visit http://ibm.co/LIg7gk.
Visit the official Scribd Channel of IBM India Smarter Computing at http://bit.ly/VwO86R to get access to more documents.
Digital Enterprise Journal identified 20 technology vendors that are providing innovative solutions for extracting business context from IT monitoring data and enabling multiple non-IT job roles to make better informed decisions. It should be noted that the primary purpose of the majority of these solutions is still IT performance monitoring, but their ability to provide business insights make them more valuable for end-user organizations, especially those that are looking to become digital businesses.
The need, applications, challenges, new trends and
a consulting perspective
(Why is Big Data a strategic need for optimization of organizational processes especially in the business domains and what is the consultantâs role?)
With every transaction and activity, organizations churn out data. This process happens even in the case of idle operation. Hence, data needs to be effectively analyzed to manage all processes better. Data can be used to make sense of the current situation and predict outcomes. It also can be used to optimize business processes and operations. This is easier said than done as data is being produced at an unprecedented rate, huge volumes and a high degree of variety. For the outcome of the data analysis to be relevant, all the data sets must be factored in to the analysis and predictions. This is where big data analysis comes in with its sophisticated tools that are also now easy on the pocket if one prefers the open source.
The future of high potential marketing lead generation would be based on big data. Virtually every business vertical can benefit from big data initiatives. Even those without deep pockets can use the cloud model for business analytics/big data analysis.
Some challenges remain to be addressed to engender large scale adoption but the current benefits outweigh the concerns.
India has seen a massive growth in big data adoption and the trend will grow though it is generally amongst the bigger players. As quality of data improves and customer reluctance to being honest when they volunteer data reduces, the forecasts will become more accurate and Big Data will have come to its rightful place as a key enabler.
Data analytics is important because it helps businesses
optimize their performances. Implementing it into the
business model means companies can help reduce
costs by identifying more efficient ways of doing
business and by storing large amounts of data. A
company can also use data analytics to make better
business decisions and help analyze customer trends
and satisfaction, which can lead to newâand betterâ
products and services
1. Top of FormResource Project Systems Acquisition Plan Gradi.docxambersalomon88660
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1.
Top of Form
Resource: Project Systems Acquisition Plan Grading Guide
Resources:Â
¡ Baltzan, P., and Phillips, A. (2015). Business Driven Information Systems (5th ed).
¡ Week 3 articles and videos
¡ It is recommended students search the Internet for a Systems Acquisition Plan template.
Scenario: You are an entrepreneur in the process of researching a business development idea. As you create a high-level Information Technology (IT) strategy for your new enterprise, it is important to consider the acquisition of IT resources. A Systems Acquisition Plan will guide the process of identifying enterprise technology needs and acquiring appropriate information systems in the context of your goal to incorporate business driven IT. The Systems Acquisition Plan is intended to describe a high-level process for acquiring and maintaining IT systems. The Systems Acquisition Plan is a working document, which is expected to change over time as new project details emerge.Â
Create a high-level Project Systems Acquisition Plan for your project in a minimum of 1,050 words that includes the following information: Â
¡ A description and justification of the specific systems design and development approach (SDLC, RAD, Spiral, outsourcing, etc.) the enterprise will employ
¡ A summary of the steps in the systems acquisition process including initiation, analysis, design, acquisition, and maintenance
¡ A high-level overview of who will participate in each step of the systems acquisition process
Cite a minimum of 3 peer-reviewed references from the University of Phoenix Library.Â
FormatâŻconsistent with APA guidelines.Â
Submit your assignment.
Resources
¡ Center for Writing Excellence
¡ Reference and Citation Generator
¡ Grammar and Writing Guides
¡ Learning Team Toolkit
2
CHAPTER
Decisions and Processes: Value Driven Business
CHAPTER OUTLINE
SECTION 2.1
Decision Support Systems
SECTION 2.2
Business Processes
Making Organizational Business Decisions
Measuring Organizational Business Decisions
Using MIS to Make Business Decisions
Using AI to Make Business Decisions
Managing Business Processes
Using MIS to Improve Business Processes
Whatâs in IT for me?
Working faster and smarter has become a necessity for companies. A firmâs value chain is directly affected by how well it designs and coordinates its business processes. Business processes offer competitive advantages if they enable a firm to lower operating costs, differentiate, or compete in a niche market. They can also be huge burdens if they are outdated, which impedes operations, efficiency, and effectiveness. Thus, the ability of management information systems to improve business processes is a key advantage.
The goal of Chapter 2 is to provide an overview of specific MIS tools managers can use to support the strategies discussed in Chapter 1. After reading this chapter, you, the business student, should have detailed knowledge of the types of information systems that exist to support decision making and business .
Small and medium enterprise business solutions using data visualizationjournalBEEI
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The small and medium enterprise (SME) companies optimize performance using different automated systems to highlight the operations concerns. However, lack of efficient visualization in reporting results in slow feedbacks, difficulties in extracting root cause, and minimal corrective actions. To complicate matters, the data heterogeneity has intensely increased, and it is produced in a fast manner making it unmanageable if the traditional methods of analytics are applied. Hence, we propose the use of a dashboard that can summarize the operational events using real-time data based on the data visualization approach. This proposed solution summarizes the raw data, which allows the user to make informed decisions that can give a positive impact on business performance. An interactive intelligent dashboard for SME (iid-SME) is developed to tackle issues such as measurement of cases completed, the duration of time needed to solve a case, the individual performance of handling cases and other tasks as a proof of concept. From the result, the implementation of the iid-SME approach simplifies the conveyance of the message and helps the SME personnel to make decisions. With the positive feedback obtained, it is envisaged that such a solution can be further employed for SME improvement for better profit and decision making.
To succeed in a modern digital world, healthcare industry must be data driven. Hospitals and healthcare institutions desire to make their workflows more efficient in order to meet demand. One way they can achieve this is with the help of business intelligence BI software. BI refers to the acquisition, correlation, and transformation of data into insightful and actionable information through analytics. Utilizing a BI software is an indispensable part of the growth process toward becoming data driven. In the modern healthcare environment, almost all BI initiatives will be driven by data analytics. This paper provides a brief examination of the deployment and constraints of business intelligence in healthcare. Matthew N. O. Sadiku | Adedamola Omotoso | Sarhan M. Musa ""Healthcare Business Intelligence: A Primer"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30041.pdf
Paper Url : https://www.ijtsrd.com/engineering/other/30041/healthcare-business-intelligence-a-primer/matthew-n-o-sadiku
PREDICTIVE BUSINESS INTELLIGENCE: CONSUMER GOODS SALES FORECASTING USING ARTI...IAEME Publication
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Business competition between manufacturing businesses in Indonesia is getting
tighter along with the development of businesses from competing companies that have
similar businesses. One strategy that can be applied by this company is Business
Intelligence, that is by utilizing the data that is already available to help in better
decision making, such as decisions based on facts stored in the data, precisely namely
the lack of errors in the presentation of reports, and fast that is, cut down on the time
for making the usual report. The method proposed by the author is a method that can
be used to predict sales value based on existing sales data (sales forecasting). By
implementing Business Intelligence and data mining, companies can learn from the
data that has been collected, can evaluate the performance of the sales department,
can understand market trends from the products sold, and can predict future sales
levels. In addition, Business Intelligence can display detailed transaction data
recapitulation quickly.
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AI in Business Intelligence Impact use cases and implementationChristopherTHyatt
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Data, data everywhere! In the contemporary business landscape, organizations are inundated with a constant stream of data. But without the ability to interpret and analyze this data effectively, it remains just that â data. This is where business intelligence (BI) comes in. As Carly Fiorina aptly stated, âThe goal of business intelligence is to turn data into information and information into insight.âBusiness intelligence tools and strategies enable companies to uncover the latent opportunities hidden within their data, translating it into actionable insights that enhance decision-making processes.
In our homes or offices, security has been a vital issue. Control of home security system remotely always offers huge advantages like the arming or disarming of the alarms, video monitoring, and energy management control apart from safeguarding the home free up intruders. Considering the oldest simple methods of security that is the mechanical lock system that has a key as the authentication element, then an upgrade to a universal type, and now unique codes for the lock. The recent advancement in the communication system has brought the tremendous application of communication gadgets into our various areas of life. This work is a real-time smart doorbell notification system for home Security as opposes of the traditional security methods, it is composed of the doorbell interfaced with GSM Module, a GSM module would be triggered to send an SMS to the house owner by pressing the doorbell, the owner will respond to the guest by pressing a button to open the door, otherwise, a message would be displayed to the guest for appropriate action. Then, the keypad is provided for an authorized person for the provision of password for door unlocking, if multiple wrong password attempts were made to unlock, a message of burglary attempt would be sent to the house owner for prompt action. The main benefit of this system is the uniqueness of the incorporation of the password and messaging systems which denies access to any unauthorized personality and owner's awareness method.
Augmented reality, the new age technology, has widespread applications in every field imaginable. This technology has proven to be an inflection point in numerous verticals, improving lives and improving performance. In this paper, we explore the various possible applications of Augmented Reality (AR) in the field of Medicine. The objective of using AR in medicine or generally in any field is the fact that, AR helps in motivating the user, making sessions interactive and assist in faster learning. In this paper, we discuss about the applicability of AR in the field of medical diagnosis. Augmented reality technology reinforces remote collaboration, allowing doctors to diagnose patients from a different locality. Additionally, we believe that a much more pronounced effect can be achieved by bringing together the cutting edge technology of AR and the lifesaving field of Medical sciences. AR is a mechanism that could be applied in the learning process too. Similarly, virtual reality could be used in the field where more of practical experience is needed such as driving, sports, neonatal care training.
Image fusion is a sub field of image processing in which more than one images are fused to create an image where all the objects are in focus. The process of image fusion is performed for multi-sensor and multi-focus images of the same scene. Multi-sensor images of the same scene are captured by different sensors whereas multi-focus images are captured by the same sensor. In multi-focus images, the objects in the scene which are closer to the camera are in focus and the farther objects get blurred. Contrary to it, when the farther objects are focused then closer objects get blurred in the image. To achieve an image where all the objects are in focus, the process of images fusion is performed either in spatial domain or in transformed domain. In recent times, the applications of image processing have grown immensely. Usually due to limited depth of field of optical lenses especially with greater focal length, it becomes impossible to obtain an image where all the objects are in focus. Thus, it plays an important role to perform other tasks of image processing such as image segmentation, edge detection, stereo matching and image enhancement. Hence, a novel feature-level multi-focus image fusion technique has been proposed which fuses multi-focus images. Thus, the results of extensive experimentation performed to highlight the efficiency and utility of the proposed technique is presented. The proposed work further explores comparison between fuzzy based image fusion and neuro fuzzy fusion technique along with quality evaluation indices.
Graphs have become the dominant life-form of many tasks as they advance a
structure to represent many tasks and the corresponding relations. A powerful
role of networks/graphs is to bridge local feats that exist in vertices as they
blossom into patterns that help explain how nodal relations and their edges
impacts a complex effect that ripple via a graph. User cluster are formed as a
result of interactions between entities. Many users can hardly categorize their
contact into groups today such as âfamilyâ, âfriendsâ, âcolleaguesâ etc. Thus,
the need to analyze such user social graph via implicit clusters, enables the
dynamism in contact management. Study seeks to implement this dynamism
via a comparative study of deep neural network and friend suggest algorithm.
We analyze a userâs implicit social graph and seek to automatically create
custom contact groups using metrics that classify such contacts based on a
userâs affinity to contacts. Experimental results demonstrate the importance
of both the implicit group relationships and the interaction-based affinity in
suggesting friends.
This paper projects Gryllidae Optimization Algorithm (GOA) has been applied to solve optimal reactive power problem. Proposed GOA approach is based on the chirping characteristics of Gryllidae. In common, male Gryllidae chirp, on the other hand some female Gryllidae also do as well. Male Gryllidae draw the females by this sound which they produce. Moreover, they caution the other Gryllidae against dangers with this sound. The hearing organs of the Gryllidae are housed in an expansion of their forelegs. Through this, they bias to the produced fluttering sounds. Proposed Gryllidae Optimization Algorithm (GOA) has been tested in standard IEEE 14, 30 bus test systems and simulation results show that the projected algorithms reduced the real power loss considerably.
In the wake of the sudden replacement of wood and kerosene by gas cookers for several purposes in Nigeria, gas leakage has caused several damages in our homes, Laboratories among others. installation of a gas leakage detection device was globally inspired to eliminate accidents related to gas leakage. We present an alternative approach to developing a device that can automatically detect and control gas leakages and also monitor temperature. The system detects the leakage of the LPG (Liquefied Petroleum Gas) using a gas sensor, then triggred the control system response which employs ventilator system, Mobile phone alert and alarm when the LPG concentration in the air exceeds a certain level. The performance of two gas sensors (MQ5 and MQ6) were tested for a guided decision. Also, when the temperature of the environment poses a danger, LED (indicator), buzzer and LCD (16x2) display was used to indicate temperature and gas leakage status in degree Celsius and PPM respectively. Attension was given to the response time of the control system, which was ascertained that this system significantly increases the chances and efficiency of eliminating gas leakage related accident.
Feature selection problem is one of the main important problems in the text and data mining domain. This paper presents a comparative study of feature selection methods for Arabic text classification. Five of the feature selection methods were selected: ICHI square, CHI square, Information Gain, Mutual Information and Wrapper. It was tested with five classification algorithms: Bayes Net, Naive Bayes, Random Forest, Decision Tree and Artificial Neural Networks. In addition, Data Collection was used in Arabic consisting of 9055 documents, which were compared by four criteria: Precision, Recall, F-measure and Time to build model. The results showed that the improved ICHI feature selection got almost all the best results in comparison with other methods.
In this paper Gentoo Penguin Algorithm (GPA) is proposed to solve optimal reactive power problem. Gentoo Penguins preliminary population possesses heat radiation and magnetizes each other by absorption coefficient. Gentoo Penguins will move towards further penguins which possesses low cost (elevated heat concentration) of absorption. Cost is defined by the heat concentration, distance. Gentoo Penguins penguin attraction value is calculated by the amount of heat prevailed between two Gentoo penguins. Gentoo Penguins heat radiation is measured as linear. Less heat is received in longer distance, in little distance, huge heat is received. Gentoo Penguin Algorithm has been tested in standard IEEE 57 bus test system and simulation results show the projected algorithm reduced the real power loss considerably.
08 20272 academic insight on applicationIAESIJEECS
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This research has thrown up many questions in need of further investigation.There was an expressive quantitative-qualitative research, which a common investigation form was used in.The dialogue item was also applied to discover if the contributors asserted the media-based attitude supplements their learning of academic English writing classes or not.Data recounted academicâ insights toward using Skype as a sustaining implement for lessons releasing based on chosen variables: their occupation, year of education, and knowledge with Skype discovered that there were no important statistical differences in the use of Skype units because of medical academics major knowledge. There are statistically important differences in using Skype units. The findings also, disclosed that there are statistically significant differences in using Skype units due to the practice with Skype variable, in favors of academics with no Skype use practice. Skype instrument as an instructive media is a positive medium to be employed to supply academic medical writing data and assist education. Academics who do not have enough time to contribute in classes believe comfortable using the Skype-based attitude in scientific writing. They who took part in the course claimed that their approval of this media is due to learning academic innovative medical writing.
Cloud computing has sweeping impact on the human productivity. Today itâs used for Computing, Storage, Predictions and Intelligent Decision Making, among others. Intelligent Decision-Making using Machine Learning has pushed for the Cloud Services to be even more fast, robust and accurate. Security remains one of the major concerns which affect the cloud computing growth however there exist various research challenges in cloud computing adoption such as lack of well managed service level agreement (SLA), frequent disconnections, resource scarcity, interoperability, privacy, and reliability. Tremendous amount of work still needs to be done to explore the security challenges arising due to widespread usage of cloud deployment using Containers. We also discuss Impact of Cloud Computing and Cloud Standards. Hence in this research paper, a detailed survey of cloud computing, concepts, architectural principles, key services, and implementation, design and deployment challenges of cloud computing are discussed in detail and important future research directions in the era of Machine Learning and Data Science have been identified.
Notary is an official authorized to make an authentic deed regarding all deeds, agreements and stipulations required by a general rule. Activities carried out at the notary office such as recording client data and file data still use traditional systems that tend to be manual. The problem that occurs is the inefficiency in data processing and providing information to clients. Clients have difficulty getting information related to the progress of documents that are being taken care of at the notary's office. The client must take the time to arrive to the notary's office repeatedly to check the progress of the work of the document file. The purpose of this study is to facilitate clients in obtaining information about the progress of the work in progress, and make it easier for employees to process incoming documents by implementing an administrative system. This system was developed with the waterfall system development method and uses the Multi-Channel Access Technology integrated in the website to simplify the process of delivering information and requesting information from clients and to clients with Telegram and SMS Gateway. Clients will come to the office only when there is a notification from the system via Telegram or SMS notifying that the client must come directly to the notary's office, thus leading to an efficient time and avoiding excessive transportation costs. The overall functional system can function properly based on the results of alpha testing. The results of beta testing conducted by distributing the system feasibility test questionnaire to end users, get a percentage of 96% of users agree the system is feasible to be implemented.
In this work Tundra wolf algorithm (TWA) is proposed to solve the optimal reactive power problem. In the projected Tundra wolf algorithm (TWA) in order to avoid the searching agents from trapping into the local optimal the converging towards global optimal is divided based on two different conditions. In the proposed Tundra wolf algorithm (TWA) omega tundra wolf has been taken as searching agent as an alternative of indebted to pursue the first three most excellent candidates. Escalating the searching agentsâ numbers will perk up the exploration capability of the Tundra wolf wolves in an extensive range. Proposed Tundra wolf algorithm (TWA) has been tested in standard IEEE 14, 30 bus test systems and simulation results show the proposed algorithm reduced the real power loss effectively.
In this work Predestination of Particles Wavering Search (PPS) algorithm has been applied to solve optimal reactive power problem. PPS algorithm has been modeled based on the motion of the particles in the exploration space. Normally the movement of the particle is based on gradient and swarming motion. Particles are permitted to progress in steady velocity in gradient-based progress, but when the outcome is poor when compared to previous upshot, immediately particle rapidity will be upturned with semi of the magnitude and it will help to reach local optimal solution and it is expressed as wavering movement. In standard IEEE 14, 30, 57,118,300 bus systems Proposed Predestination of Particles Wavering Search (PPS) algorithm is evaluated and simulation results show the PPS reduced the power loss efficiently.
In this paper, Mine Blast Algorithm (MBA) has been intermingled with Harmony Search (HS) algorithm for solving optimal reactive power dispatch problem. MBA is based on explosion of landmines and HS is based on Creativeness progression of musicians-both are hybridized to solve the problem. In MBA Initial distance of shrapnel pieces are reduced gradually to allow the mine bombs search the probable global minimum location in order to amplify the global explore capability. Harmony search (HS) imitates the music creativity process where the musicians supervise their instrumentsâ pitch by searching for a best state of harmony. Hybridization of Mine Blast Algorithm with Harmony Search algorithm (MH) improves the search effectively in the solution space. Mine blast algorithm improves the exploration and harmony search algorithm augments the exploitation. At first the proposed algorithm starts with exploration & gradually it moves to the phase of exploitation. Proposed Hybridized Mine Blast Algorithm with Harmony Search algorithm (MH) has been tested on standard IEEE 14, 300 bus test systems. Real power loss has been reduced considerably by the proposed algorithm. Then Hybridized Mine Blast Algorithm with Harmony Search algorithm (MH) tested in IEEE 30, bus system (with considering voltage stability index)- real power loss minimization, voltage deviation minimization, and voltage stability index enhancement has been attained.
Artificial Neural Networks have proved their efficiency in a large number of research domains. In this paper, we have applied Artificial Neural Networks on Arabic text to prove correct language modeling, text generation, and missing text prediction. In one hand, we have adapted Recurrent Neural Networks architectures to model Arabic language in order to generate correct Arabic sequences. In the other hand, Convolutional Neural Networks have been parameterized, basing on some specific features of Arabic, to predict missing text in Arabic documents. We have demonstrated the power of our adapted models in generating and predicting correct Arabic text comparing to the standard model. The model had been trained and tested on known free Arabic datasets. Results have been promising with sufficient accuracy.
In the present-day communications speech signals get contaminated due to
various sorts of noises that degrade the speech quality and adversely impacts
speech recognition performance. To overcome these issues, a novel approach
for speech enhancement using Modified Wiener filtering is developed and
power spectrum computation is applied for degraded signal to obtain the
noise characteristics from a noisy spectrum. In next phase, MMSE technique
is applied where Gaussian distribution of each signal i.e. original and noisy
signal is analyzed. The Gaussian distribution provides spectrum estimation
and spectral coefficient parameters which can be used for probabilistic model
formulation. Moreover, a-priori-SNR computation is also incorporated for
coefficient updation and noise presence estimation which operates similar to
the conventional VAD. However, conventional VAD scheme is based on the
hard threshold which is not capable to derive satisfactory performance and a
soft-decision based threshold is developed for improving the performance of
speech enhancement. An extensive simulation study is carried out using
MATLAB simulation tool on NOIZEUS speech database and a comparative
study is presented where proposed approach is proved better in comparison
with existing technique.
Previous research work has highlighted that neuro-signals of Alzheimerâs disease patients are least complex and have low synchronization as compared to that of healthy and normal subjects. The changes in EEG signals of Alzheimerâs subjects start at early stage but are not clinically observed and detected. To detect these abnormalities, three synchrony measures and wavelet-based features have been computed and studied on experimental database. After computing these synchrony measures and wavelet features, it is observed that Phase Synchrony and Coherence based features are able to distinguish between Alzheimerâs disease patients and healthy subjects. Support Vector Machine classifier is used for classification giving 94% accuracy on experimental database used. Combining, these synchrony features and other such relevant features can yield a reliable system for diagnosing the Alzheimerâs disease.
Attenuation correction designed for PET/MR hybrid imaging frameworks along with portion making arrangements used for MR-based radiation treatment remain testing because of lacking high-energy photon weakening data. We present a new method so as to uses the learned nonlinear neighborhood descriptors also highlight coordinating toward foresee pseudo-CT pictures starting T1w along with T2w MRI information. The nonlinear neighborhood descriptors are acquired through anticipating the direct descriptors interested in the nonlinear high-dimensional space utilizing an unequivocal constituent guide also low-position guess through regulated complex regularization. The nearby neighbors of every near descriptor inside the data MR pictures are looked during an obliged spatial extent of the MR pictures among the training dataset. By that point, the pseudo-CT patches are evaluated through k-closest neighbor relapse. The planned procedure designed for pseudo-CT forecast is quantitatively broke downward on top of a dataset comprising of coordinated mind MRI along with CT pictures on or after 13 subjects.
The cognitive radio prototype performance is to alleviate the scarcity of spectral resources for wireless communication through intelligent sensing and quick resource allocation techniques. Secondary users (SUâs) actively obtain the spectrum access opportunity by supporting primary users (PUâs) in cognitive radio networks (CRNs). In present generation, spectrum access is endowed through cooperative communication-based link-level frame-based cooperative (LLC) principle. In this SUs independently act as conveyors for PUs to achieve spectrum access opportunities. Unfortunately, this LLC approach cannot fully exploit spectrum access opportunities to enhance the throughput of CRNs and fails to motivate PUs to join the spectrum sharing processes. Therefore, to overcome this con, network level cooperative (NLC) principle was used, where SUs are integrated mutually to collaborate with PUs session by session, instead of frame based cooperation for spectrum access opportunities. NLC approach has justified the challenges facing in LLC approach. In this paper we make a survey of some models that have been proposed to tackle the problem of LLC. We show the relevant aspects of each model, in order to characterize the parameters that we should take in account to achieve a spectrum access opportunity.
In this paper, the author provides insights and lessons that can be learned from colleagues at American universities about their online education experiences. The literature review and previous studies of online educations gains are explored and summarized in this research. Emerging trends in online education are discussed in detail, and strategies to implement these trends are explained. The author provides several tools and strategies that enable universities to ensure the quality of online education. At the end of this research paper, the researcher provides examples from Arab universities who have successfully implemented online education and expanded their impact on the society. This research provides a strategy and a model that can be used by universities in the Middle East as a roadmap to implement online education in their regions.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
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Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Dev Dives: Train smarter, not harder â active learning and UiPath LLMs for do...UiPathCommunity
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đĽ Speed, accuracy, and scaling â discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Miningâ˘:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing â with little to no training required
Get an exclusive demo of the new family of UiPath LLMs â GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
đ¨âđŤ Andras Palfi, Senior Product Manager, UiPath
đŠâđŤ Lenka Dulovicova, Product Program Manager, UiPath
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
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The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties â USA
Expansion of bot farms â how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks â Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
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Clients donât know what they donât know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clientsâ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
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Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
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The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. Whatâs changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
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Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overviewâ
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
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Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
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Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
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Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as âpredictable inferenceâ.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Neuro-symbolic is not enough, we need neuro-*semantic*
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6. 17448 33940-1-ed 20 apr 13mar 28dec2018 ed iqbal qc
1. International Journal of Informatics and Communication Technology (IJ-ICT)
Vol.8, No.2, August 2019, pp. 102~110
ISSN: 2252-8776, DOI: 10.11591/ijict.v8i2.pp102-110 ď˛ 102
Journal homepage: http://iaescore.com/journals/index.php/IJICT
Using business intelligence solutions for forecasting in
marketing researches
Christina Albert Rayed Assad
Computer and Information System Department, Sadat Academy for Management Science, Egypt
Article Info ABSTRACT
Article history:
Received Dec 28, 2018
Revised Mar 13, 2019
Accepted Apr 20, 2019
Business intelligence comprises of tools and applications that are leverages
software and services to translate data into intelligent actions for strategic,
tactical and operational decisions. The intelligent business solution facilitates
and develops the service provided to the market researchers, saves time and
effort needed to identify the customers predict demand and manage production
more efficiently, ability to explore possibilities to increase revenue. The
purpose of this paper is using business intelligence solutions for forecasting in
Marketing Researches. The intelligence solutions are helping the market
researchers to achieve efficiency, effectiveness, and differentiation.
Keywords:
Business intelligence (BI)
Business intelligent solutions
Data mining
Extraction, transformation and
loading (ETL)
Marketing researches
Copyright Š 2019 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Christina Albert Rayed Assad,
Computer and Information System Department,
Sadat Academy for Management Science, Cairo, Egypt.
Email: sams.christina.albert@gmail.com
1. INTRODUCTION
Business intelligence is a powerful new management approach thatâwhen done rightâcan deliver
knowledge, efficiency, better decisions, and profit to almost any organization that uses it [1]. Business
intelligence may be defined as a set of mathematical models and analysis methodologies that exploit the
available data to generate information and knowledge useful for complex decision-making processes [2].
Business intelligence is depending on collecting data from various sources, by compressing these data can be
analyzed from multiple aspects in order to support making marketing researches.Business intelligence is a
broad category of applications and technologies for gathering, storing, analyzing, and providing access to data
to help enterprise users make better business decisions. BI applications include the activities of decision support
systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and Data
Mining [3].
Forecasting is a process of predicting or estimating the future based on past and present data.
Forecasting process provides information about the potential future events and their consequences for the
organization. Forecasting in market researches is very important for companies. It helps to enhance
performance of companies and enhance customer relationships and provide strategic advantages. Several
forecasting models existing each organization can choose the model which I suitable for its activities.
There are many problems in the global marketing related to the forcasting. In the globalization era,
many companies face many challenges to pertrate and compitete in the global marketing. There are two
important milesones in the marketing process: first is reducing costs and the second is increasing sales and
revenue. Many companies face many challenges like acquization customers, repeated purchases, increasing
customers, opening new markets and targeting the right customers in the right time. There are many marketing
researches to investigate these problems and forcaste for solutions for these problems though the globalization
market.
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So, the propsed intelligent business analytics solutions can assist for forcasting for the future and
predicating of solutions for many marketing problems. Intelligent business analytics solutions develop all
activities including collect, analyze and plan for new campaigns to gain a competitive advantage. Business
Intelligence analytical solutions can help in sophisticated problems with large amount of data to reach to
customized solutions in the right time. Therefore by using business intelligence analytical solutions for
forecasting process will predict customized intelligent solutions.that will assist market researchers to increase
sales and reduce costs in order to gain the pick revenue and enhance the organization image.
There are many previous researches that refer to the using of business intelligence solutions for
supporting and predicting for decision making in the marketing researches. Business Intelligence possesses the
capabilities that support superior business decision-making through past, present and predictive
composition/trends of organization operations. Business intelligence is not a product, technology and or
methodology, but a combination of all to leverage information assets within key business processes to achieve
improved business performance [1].
Decision-making is everyday life activity and it is the essence of management [4]. Business
Intelligence, the basic technology of Business Intelligence, and the contents of Supply Chain Integration and
focuses on the analysis of the application of Business Intelligence in Supply Chain Integration to provide basis
for enterprises to implement Business Intelligence [5].
2. THE BUSINESS INTELLIGENCE ENVIRONMENT
Business intelligence and analytics requires a huge amount of structured and unstructured data from
different resources, analytic tools, and people who deal with these tools to plan and predict for the future and
solve complicated problems. Specific case of business intelligence (BI) infrastructures, should be decided
according to the speed of the decision-making processes, which are usually executed in real time. It is determine
the flexibility rate at which the business can grow. Businesses grow but the key drivers can remain the same.
It analyzes the elements required for an optimal deployment of smart decision architectures [6].
As shown in Figure 1 which gives an overview of a business intelligence environment starting with
the data and ending with different solutions to the end users. The business intelligence environment consists of
six milestones.
2.1. Data
In the business environment, there are different types of structured, semi structured and unstructured
data from different resources with containing the mobile devices and social networks. All these data is needed
by the decision makers in order to analyze to gain a competitive advantage.
2.2. Business intelligent infrastructure
Business intelligent infrastructure consists of the databases, data warehouse and data marts in order
to turn data into information and information into knowledge and knowledge into strategic plans that gain a
competitive advantage.
2.3. Business analytics tools
There are many business analytics tools like OLAP, data mining, statistical models, and reports.
2.4. Management methods
The management methods used to predict and forecast using key indicators of performance. Managers
use a variety of managerial methods in order to demonstrate strategic business goals and performance
management.
2.5. Delivery platform
The delivery platform contains management information system (MIS), decision support system
(DSS), executive support system (ESS). The results from business intelligence and analytics are delivered to
managers and employees in a variety of ways. MIS, DSS, and ESS that help track and keep information flowing
in the amount and direction organization needs to stay on track, deliver information and knowledge to different
levels of management from top, middle and low management. Delivery platform can present, summarize, and
analyze data from an organizationâs databases or data warehouse to operational employees, middle managers,
and senior executives.
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Int J Inf & Commun Technol, Vol. 8, No. 2, August 2019 : 102 â 110
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2.6. User interface
Todayâs business analytics software can deliver reports and summarized data through the using of
smart phones and handheld computers. The user interface can be through web portals or mobile applications
or social networks. Business analytics software highlights visual techniques such as dashboards and scorecards.
Mobile business intelligence tool (MBIT) aims to provide these features in a flexible and cost-efficient manner.
Business analytics software describes the detailed architecture of MBIT to overcome the limitations of existing
mobile business intelligence tools. Business analytics software discusses the benefits of using service oriented
architecture to design flexible and platform independent mobile business applications [7].
Figure 1. Business intelligence environment
3. BUSINESS INTELLIGENCE SOLUTION ARCHITECTURE
Business intelligence solution architecture is a collection of organizing the data, information
management and technology components that are used to build business intelligence systems for generating
reports and analyzing data. This architecture contains operational, strategic, tactical decision support
applications and databases that provides the business community easy access to data in a real time special for
market researches. Business intelligence solution architecture is based on the vision, mission and objectives of
the business.
Business intelligence solution architecture consists of five stages as shown in Figure 2:
- Data modeling is one of the core phases of designing a BI solution and in this phase all the data that is
gathered regarding requirements are used which means the data model will effectively function as a
foundation for building the BI solution [8]. Source systems are essentially systems that provide a BI system
with data thus the definition data sources. SAP (Systems Applications Products) has a different
classification, and as such it associates data sources with metadata of source system, which is used when
the actual data is transferred in the form of Info Packages. SAP defines four types of data sources for SAP
source systems and these are grouped into two, based on the type of data, transaction data and master
data [9].
- Data acquisition implies the extraction of data from source systems. An Extraction, Transformation and
Loading (ETL) process can also be used to facilitate the data acquisition process
- Data extraction is an area where the data that is extracted from a source system is stored temporarily and in
a raw format, that is without any changes to the data. SAP defines this area a Persistent Staging
Area (PSA) [10].
- Data transformation phase, Transformation in this case implies that the source data is consolidated and
formatted so that it can be transferred for further processing and analyzing. Once the data is in the staging
area, it can be cleansed, transformed, and transferred to a cube. The process Extraction, Transformation and
Loading (ETL) can support facilitating this stage. The ETL (Extract, Load, and Transform) is one of the
main components of a business intelligence system that depends on data accuracy in order todata extraction.
- The data presentation layer of a BI solution ultimately represents the end user environment, where reports
and queries are used to present the data in a certain format so that drill down analysis on multidimensional
data can be performed [11]. The presentation layer may use modern web technologies such as Adobe flash,
HTML5 and PDF to present easy to use, highly interactive, and user-friendly reports.
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Figure 2. Business Intelligence solution Architecture
Even-Driven Architecture (EDA) based Right-Time Business Intelligence System Framework (EDA
based RTBISF), which combines RT-BI and the business process based on the EDA and Agent, to resolve the
environment uncertainty, business dynamics and to meet the needs of dynamic adjustment of business solution
for the enterprise in the fierce competitive environment [12]. Specific case of business intelligence (BI)
infrastructures, should be decided according to the speed of the decision-making processes, which are usually
executed in real time. It is determine the flexibility rate at which the business can grow. Businesses grow but
the key drivers can remain the same. It analyzes the elements required for an optimal deployment of smart
decision architectures [6]. There are many essential factors in business intelligence solution architecture
depending on scalability and high performance, agility, complete functionality, extensibility, rapid
development and deployment.
4. USING BUSINESS INTELLIGENCE SOLUTIONS IN MARKET RESEARCHES
It's very important in the competitive business environment to offer new business intelligence
solutions to increase the revenue and reduce expenses. The business intelligence solutions can offer a fast
access to information at low cost in marketing researches that can lead to gain a competitive advantage and
acquisition new customers and open new markets. Business intelligence solutions also offer intelligent queries
and reports, so that they help in decision making.
One of the keys of business strategy for creating competitive advantages is understands the data that
firms generate in its own business. Information processing has gradually become the basis for achieving
competitive advantage. The organization has to believe that have the right information at the right time and
available to the right people [13].
BI bridges between different systems and users wishing to access information, providing an
environment that facilitates access to information needed for day to day activities, allowing analyze the
business performance [14]. With BI organizations can integrate powerful tools, analysis, standardized
reporting, monitoring system withvarious metrics, data integration, among other features within a service-
oriented architecture [15, 16].
E-business intelligence aims to develop a tremendous spectrum of business opportunities and user's
adoption of the business intelligence is very important and relevant propositions are made [17]. Market
intelligence (MI) is a process geared towards the market environment that an organisation operates in and
differentiates itself from market research with the analytic capabilities [18].Market intelligence is decision-
centric and expressed by some marketing researches, Market intelligence is a subset of business intelligence to
gain from the experiences and to anticipate the future market opportunities before the competition.
Customer Relationship Management (CRM) systems and Business Intelligence provides a holistic
approach to customers which includes improvements in customer profiling, simpler detection value for
customers, measuring the success of the company in satisfying its customers, and create a comprehensive
customer relationship management [19]. Business Intelligence and Business Process Management (BPM)
applications is using for data analysis and simulation of forecasting in market researches.
Using business intelligence applications includes three stages as shown in Figure 3; the first stage is
analysis that contains the using of data mining, advanced analysis, Visual and OLAP analysis. The second
phase is reporting by creating marketing and statistical reports. The last phase is monitoring which contains
dashboards, scorecards and mobile apps.
Data presentation
Data transformation
Data extraction
Data acquisition
Data modelling
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Int J Inf & Commun Technol, Vol. 8, No. 2, August 2019 : 102 â 110
106
Figure 3. Stages of using business intelligence solutions
By applying these three stages in market researches, the business intelligence solution must aim to
ensure the business strategy, increase the economics scales, offer the full range of business intelligence
functionality, generate integration reports to dashboards ,OLAP, ad hoc queries and mobile applications,
accessibility and real time access, agility to Rapid Development and Deployment and Consistency and security
issues.
5. APPLYING BUSINESS INTELLIGENVE SOLUTIONS IN MARKETING RESEARCHES
By applying business intelligent solutions in market researches, will achieve the reported that the
major goals for the companies such as increase revenue, reduce costs, and increase productivity.This paper
presents a business intelligence solution framework for applying business intelligence solution in market
researches. The proposed framework is structured in four phases as shown in Figure 4; planning, analyzing ,
execution and dissemination.
5.1. Planning stage
In this stage, it's important to obtain the approvals from the management, illustrate the objectives and
goals, put the methodology for applying and create the plan. The planning study includes the data modeling
and acquisition. After determining the market, business intelligence solutions starts to collecting internal and
external data which containing all types of data structured , semi-structured and unstructured data in order to
data modeling and acquisition.
5.2. Analyzing stage
There are many analytical methods must be applied in order to get value out such as OLAPs, planning
and forecasting methods, statistical models optimization and simulation. In the analysis stage, there are
different types of analysis as following; strategic, tactical and operational analysis. Each type of analysis
support the different levels of management; top, middle and operational.
5.3. Execution stage
In the execution stage, there is a need to increase revenue and reduce cost. The business intelligence
solutionâs role is to take the right decisions in the right time to maximize the benefits of using business
intelligence solution in market researches and fast access to profiles of customers in order to present right
services at the right time. Many reports can execute like operational, web, and exception reports.
In this stage, the business intelligence solution can help all levels of management. At a strategic level, the
business intelligence solution can help the top managers to put the strategies and objective, generate smart
reports, forecast for the future, make optimization and simulation. At a tactic level, the business intelligence
solution can help the middle managers for taking decisions o different fields such as inventory, sales,
marketing, finance and so on. Finally at the operational level, business intelligence solutions can be useful for
querying and day to day operations reports.
5.4. Dissemination stage
In the dissemination stage, there are many applications containing mobile apps and Alerts, dashboards
and scorecards, OLAP analysis, data mining, run time reporting, decision engines and advanced analysis.
â˘Data Mining
â˘Advanced Analysis
â˘Visual and OLAP analysis
Analysis
â˘Dashboards
â˘Scorecards
â˘Mobile Apps
Reporting
â˘Marketing reports
â˘Statistical reports
Monitoring
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Figure 4. Business Intelligence solution framework
6. BENEFITS OF USING BUSINESS INTELLIGENCE SOLUTIONS IN MARKETING
RESEARCHES
BI helps administrators by breaking down information from various resources in better basic
leadership at both tactical and strategic level, for customary utilization, conventional data frameworks farewell,
yet for hierarchical and functional planning; new tools are required for business analysis [20].
Business analytics programs stress the utilization of quantitative analyses, predictive models and
statistical tools to help organizational leadership gain a different view of their data, derive maximum value
from its interpretation, and utilize the results to improve decision making and problem solving [21].
There are many benefits of using business intelligence solutions in marketing researches as:
- Analyze different types of data from different sources,
- Take intelligent decisions on the different levels of managements,
- Improve accuracy in predictions in different fields,
- Achieve operational efficiency,
- Make fundamental changes serving as finding new collaborations, acquiring new customers, opening new
markets,
- Add value in the supply chain for the products or services to the customers,
- Enhance the administrative process efficiencies,
- Ensure the business strategy,
- Increase the economics scales,
- Offer the full range of business intelligence functionality,
- Generate integration reports to dashboards ,OLAP, ad hoc queries and mobile applications,
- Increase accessibility and real time access,
- Agile to Rapid Development and Deployment.
7. RESULTS AND DISCUSSION
According to the previous studies, there are different approaches for applying business intelligence
solutions. The using of business intelligent solutions differs from one company to the other depending on the
size and the budget of the company. As Robert Walters said BI managers are increasingly utilising BI for
performance management (12%) and predictive analysis (13%) to promote business growth [22]. The
percentages of using business intelligence tools can be viewed in Figure 5.
Planning
â˘Data modeling
â˘Data aquisiation
Analyzing
â˘Data extraction
â˘Data transformation
Execution
⢠Reporting
â˘Forcationg
Dissemination
Business
intellegence
solutions
ďˇ Mobile apps
ďˇ Dashboard
ďˇ OLAPanalysis
ďˇ Data mining
ďˇ Decision engines
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Int J Inf & Commun Technol, Vol. 8, No. 2, August 2019 : 102 â 110
108
Figure 5. The percentages of using business intelligence tools [20]
In this paper, by applying business intelligence solutions framework on some companies worldwide
as a pilot study which presenting services like electronic banking, telecommunications, healthcare servies,
electronic banking and electronic learning. The companies will need to employ cost-effective business
intelligence (BI) solutions.In the business intelligence solutions framework there are some phases that will
apply in many companies like planning and analzing. These two phases are used by many companies in order
to forecasting and predicting for the future. According to the four phases in the business intelligence solutions
framework , the applying perentage of using business intelligence in planning is 79.75%, the second phase
(analyzing phase) percentage is 53.75%, the third phase (exectution phase) percentage is 41% and the last phase
( dissemination phase) percentage is 32.25% as shown in Figure 6.
Figure 6. The percentages of the framework's phases
According to the pilot study, the greatest companies that applying business intelligence solutions is
telecommunication then electronic banking. The latest companie is electronic learning. Farthermore the
panning and analyzing phases are the most phases in applying business intelligence solutions for the different
companies and vary from field and sector to another as shown in Figure 7. The planning and analzing phases
is very useful for forcasting in the marketing researches.
Planning
79.75%Analyzing
53.75%
Execution
41%
Dissemination
32.25%
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Using business intelligence solutions for forecasting in marketing researches (Christina Albert Rayed Assad)
109
Figure 7. The perentages of framework's phase according to different sectors
By applying business intelligence solution framework on companies, we can gain the results:
- It is useful to applying business intelligence solution framework on different categories of sectors which
promoting servicies and products like telecommunication companies, airlines, healthcare, electronic
learning and electronic banking manufacturers, electronic commence businesses, retailers, financial
services, bioinformatics and hotels.
- The business intelligence solution framework can assist in customer relationship management , market
research, cutomers segmentation, product profitability, inventory and distribution analysis, statistical
analysis, supply chain management, strategic management, Business Process Management, knowledge
management etc.
- By implementing the phases of business intelligence solutions framework, it's pereferable to understand
each phase. Also there are some phases is more applied like using business intelligence in planning and
analyzing in order to forecasting for new insights and decisions.
- There is a need to quick and real time forcasting and analytical systems through the globalization market
to reach to a new insights and gain opportunities and catch directives.
- Using business intelligence solutions can use in decision making to develop and predict in making strategic
decisions.
8. CONCLUSION
Business intelligence solutions can improve businesses process modeling quality and present the right
solution in the right time. The complexity of today's business environment requires companies to be agile and
proactive in relation to decision-making processes [23].
According to the increasing of the data types and volumes from different resources in the organization,
the business intelligence solutions have become necessary for any company in decision making in market
researches. Also, using business intelligence solutions for Forecasting can have a good role in improving the
efficiency of market researches, which is reflected positively on the planning accuracy in all parts of the
organization. Finally, using business intelligence for forecasting in market researches proves its importance
and usefulness in relation with ensuring the quality of economic activities and processes within organizations.
9. FUTURE WORK
The proposed business intelligence framework can apply in different market researches for services
and products. Also the business intelligence solutions need to evaluate and test in order to estimate the impacts
of the decisions in the markets researches and analyze through applying on complex business scenarios.
In the future works,its essential to measure main objectives of using intelligence solutions in market
researches such as efficiency, effectiveness, and differentiation.
0
10
20
30
40
50
60
70
80
Planning
Analyzing
Execution
disemination
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REFERENCES
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BIOGRAPHY OF AUTHOR
Christina Albert Rayed Assad
Associate Professor
Computer and Information System Department
Sadat Academy for Management Science, Cairo, Egypt
![International Journal of Informatics and Communication Technology (IJ-ICT)
Vol.8, No.2, August 2019, pp. 102~110
ISSN: 2252-8776, DOI: 10.11591/ijict.v8i2.pp102-110 ď˛ 102
Journal homepage: http://iaescore.com/journals/index.php/IJICT
Using business intelligence solutions for forecasting in
marketing researches
Christina Albert Rayed Assad
Computer and Information System Department, Sadat Academy for Management Science, Egypt
Article Info ABSTRACT
Article history:
Received Dec 28, 2018
Revised Mar 13, 2019
Accepted Apr 20, 2019
Business intelligence comprises of tools and applications that are leverages
software and services to translate data into intelligent actions for strategic,
tactical and operational decisions. The intelligent business solution facilitates
and develops the service provided to the market researchers, saves time and
effort needed to identify the customers predict demand and manage production
more efficiently, ability to explore possibilities to increase revenue. The
purpose of this paper is using business intelligence solutions for forecasting in
Marketing Researches. The intelligence solutions are helping the market
researchers to achieve efficiency, effectiveness, and differentiation.
Keywords:
Business intelligence (BI)
Business intelligent solutions
Data mining
Extraction, transformation and
loading (ETL)
Marketing researches
Copyright Š 2019 Institute of Advanced Engineering and Science.
All rights reserved.
Corresponding Author:
Christina Albert Rayed Assad,
Computer and Information System Department,
Sadat Academy for Management Science, Cairo, Egypt.
Email: sams.christina.albert@gmail.com
1. INTRODUCTION
Business intelligence is a powerful new management approach thatâwhen done rightâcan deliver
knowledge, efficiency, better decisions, and profit to almost any organization that uses it [1]. Business
intelligence may be defined as a set of mathematical models and analysis methodologies that exploit the
available data to generate information and knowledge useful for complex decision-making processes [2].
Business intelligence is depending on collecting data from various sources, by compressing these data can be
analyzed from multiple aspects in order to support making marketing researches.Business intelligence is a
broad category of applications and technologies for gathering, storing, analyzing, and providing access to data
to help enterprise users make better business decisions. BI applications include the activities of decision support
systems, query and reporting, online analytical processing (OLAP), statistical analysis, forecasting, and Data
Mining [3].
Forecasting is a process of predicting or estimating the future based on past and present data.
Forecasting process provides information about the potential future events and their consequences for the
organization. Forecasting in market researches is very important for companies. It helps to enhance
performance of companies and enhance customer relationships and provide strategic advantages. Several
forecasting models existing each organization can choose the model which I suitable for its activities.
There are many problems in the global marketing related to the forcasting. In the globalization era,
many companies face many challenges to pertrate and compitete in the global marketing. There are two
important milesones in the marketing process: first is reducing costs and the second is increasing sales and
revenue. Many companies face many challenges like acquization customers, repeated purchases, increasing
customers, opening new markets and targeting the right customers in the right time. There are many marketing
researches to investigate these problems and forcaste for solutions for these problems though the globalization
market.](https://image.slidesharecdn.com/6-201020035204/85/6-17448-33940-1-ed-20-apr-13mar-28dec2018-ed-iqbal-qc-1-320.jpg)
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Using business intelligence solutions for forecasting in marketing researches (Christina Albert Rayed Assad)
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So, the propsed intelligent business analytics solutions can assist for forcasting for the future and
predicating of solutions for many marketing problems. Intelligent business analytics solutions develop all
activities including collect, analyze and plan for new campaigns to gain a competitive advantage. Business
Intelligence analytical solutions can help in sophisticated problems with large amount of data to reach to
customized solutions in the right time. Therefore by using business intelligence analytical solutions for
forecasting process will predict customized intelligent solutions.that will assist market researchers to increase
sales and reduce costs in order to gain the pick revenue and enhance the organization image.
There are many previous researches that refer to the using of business intelligence solutions for
supporting and predicting for decision making in the marketing researches. Business Intelligence possesses the
capabilities that support superior business decision-making through past, present and predictive
composition/trends of organization operations. Business intelligence is not a product, technology and or
methodology, but a combination of all to leverage information assets within key business processes to achieve
improved business performance [1].
Decision-making is everyday life activity and it is the essence of management [4]. Business
Intelligence, the basic technology of Business Intelligence, and the contents of Supply Chain Integration and
focuses on the analysis of the application of Business Intelligence in Supply Chain Integration to provide basis
for enterprises to implement Business Intelligence [5].
2. THE BUSINESS INTELLIGENCE ENVIRONMENT
Business intelligence and analytics requires a huge amount of structured and unstructured data from
different resources, analytic tools, and people who deal with these tools to plan and predict for the future and
solve complicated problems. Specific case of business intelligence (BI) infrastructures, should be decided
according to the speed of the decision-making processes, which are usually executed in real time. It is determine
the flexibility rate at which the business can grow. Businesses grow but the key drivers can remain the same.
It analyzes the elements required for an optimal deployment of smart decision architectures [6].
As shown in Figure 1 which gives an overview of a business intelligence environment starting with
the data and ending with different solutions to the end users. The business intelligence environment consists of
six milestones.
2.1. Data
In the business environment, there are different types of structured, semi structured and unstructured
data from different resources with containing the mobile devices and social networks. All these data is needed
by the decision makers in order to analyze to gain a competitive advantage.
2.2. Business intelligent infrastructure
Business intelligent infrastructure consists of the databases, data warehouse and data marts in order
to turn data into information and information into knowledge and knowledge into strategic plans that gain a
competitive advantage.
2.3. Business analytics tools
There are many business analytics tools like OLAP, data mining, statistical models, and reports.
2.4. Management methods
The management methods used to predict and forecast using key indicators of performance. Managers
use a variety of managerial methods in order to demonstrate strategic business goals and performance
management.
2.5. Delivery platform
The delivery platform contains management information system (MIS), decision support system
(DSS), executive support system (ESS). The results from business intelligence and analytics are delivered to
managers and employees in a variety of ways. MIS, DSS, and ESS that help track and keep information flowing
in the amount and direction organization needs to stay on track, deliver information and knowledge to different
levels of management from top, middle and low management. Delivery platform can present, summarize, and
analyze data from an organizationâs databases or data warehouse to operational employees, middle managers,
and senior executives.](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)