The document discusses various technologies used for business research including the internet, email, World Wide Web, data analysis software, computer-aided design and manufacturing software, enterprise resource planning systems, videoconferencing, and data warehousing. It provides examples of how these technologies can help businesses obtain information, communicate, design products, track resources, and analyze data to support decision-making.
Big data refers to huge set of data which is very common these days due to the increase of internet utilities. Data generated from social media is a very common example for the same. This paper depicts the summary on big data and ways in which it has been utilized in all aspects. Data mining is radically a mode of deriving the indispensable knowledge from extensively vast fractions of data which is quite challenging to be interpreted by conventional methods. The paper mainly focuses on the issues related to the clustering techniques in big data. For the classification purpose of the big data, the existing classification algorithms are concisely acknowledged and after that, k-nearest neighbour algorithm is discreetly chosen among them and described along with an example.
An Investigation on Scalable and Efficient Privacy Preserving Challenges for ...IJERDJOURNAL
ABSTRACT:- Big data is a relative term describing a situation where the volume, velocity and variety of data exceed an organization’s storage or compute capacity for accurate and timely decision making. Big data refers to huge amount of digital information collected from multiple and different sources. With the development of application of Internet/Mobile Internet, social networks, Internet of Things, big data has become the hot topic of research across the world, at the same time; big data faces security risks and privacy protection during collecting, storing, analyzing and utilizing. Since a key point of big data is to access data from multiple and different domains security and privacy will play an important role in big data research and technology. Traditional security mechanisms, which are used to secure small scale static data, are inadequate. So the question is which security and privacy technology is adequate for efficient access to big data. This paper introduces the functions of big data, and the security threat faced by big data, then proposes the technology to solve the security threat, finally, discusses the applications of big data in information security. Main expectation from the focused challenges is that it will bring a novel focus on the big data infrastructure.
Big data refers to huge set of data which is very common these days due to the increase of internet utilities. Data generated from social media is a very common example for the same. This paper depicts the summary on big data and ways in which it has been utilized in all aspects. Data mining is radically a mode of deriving the indispensable knowledge from extensively vast fractions of data which is quite challenging to be interpreted by conventional methods. The paper mainly focuses on the issues related to the clustering techniques in big data. For the classification purpose of the big data, the existing classification algorithms are concisely acknowledged and after that, k-nearest neighbour algorithm is discreetly chosen among them and described along with an example.
An Investigation on Scalable and Efficient Privacy Preserving Challenges for ...IJERDJOURNAL
ABSTRACT:- Big data is a relative term describing a situation where the volume, velocity and variety of data exceed an organization’s storage or compute capacity for accurate and timely decision making. Big data refers to huge amount of digital information collected from multiple and different sources. With the development of application of Internet/Mobile Internet, social networks, Internet of Things, big data has become the hot topic of research across the world, at the same time; big data faces security risks and privacy protection during collecting, storing, analyzing and utilizing. Since a key point of big data is to access data from multiple and different domains security and privacy will play an important role in big data research and technology. Traditional security mechanisms, which are used to secure small scale static data, are inadequate. So the question is which security and privacy technology is adequate for efficient access to big data. This paper introduces the functions of big data, and the security threat faced by big data, then proposes the technology to solve the security threat, finally, discusses the applications of big data in information security. Main expectation from the focused challenges is that it will bring a novel focus on the big data infrastructure.
The objective of this module is to provide an overview of the basic information on big data.
Upon completion of this module you will:
-Comprehend the emerging role of big data
-Understand the key terms regarding big and smart data
- Know how big data can be turned into smart data
- Be able to apply the key terms regarding big data
Duration of the module: approximately 1 – 2 hours
Efficient Data Filtering Algorithm for Big Data Technology in Telecommunicati...Onyebuchi nosiri
Efficient data filtering algorithm for Big Data technology Telecommunication is a concept aimed at effectively filtering desired information for preventive purposes, the challenges posed by unprecedented rise in volume, variety and velocity of information has necessitated the need for exploring various methods Big Data which is simply a data sets that are so large and complex that traditional data processing tools and technologies cannot cope with is been considered. The process of examining such data to uncover hidden patterns in them was evolved, this was achieved by coming up with an Algorithm comprising of various stages like Artificial neural Network, Backtracking Algorithm, Depth First Search, Branch and Bound and dynamic programming and error check. The algorithm developed gave rise to the flowchart, with each line of block representing a sub-algorithm.
Information Systems is a set of interrelated components that collect (input), manipulate (process), store, and disseminate (output) data and information and provide a feedback mechanism to meet an objective.
The talk will cover in broad strokes the building blocks, facilitators and challenges for big data based decision making.
Using examples from two projects from very dissimilar domains (High tech manufacturing and Public Health) Dr. Vinze will present possibilities for Data Science for both practitioners and academic researchers.
Implementation of application for huge data file transferijwmn
Nowadays big data transfers make people’s life difficult. During the big data transfer, people waste so
much time. Big data pool grows everyday by sharing data. People prefer to keep their backups at the cloud
systems rather than their computers. Furthermore considering the safety of cloud systems, people prefer to
keep their data at the cloud systems instead of their computers. When backups getting too much size, their
data transfer becomes nearly impossible. It is obligated to transfer data with various algorithms for moving
data from one place to another. These algorithms constituted for transferring data faster and safer. In this
Project, an application has been developed to transfer of the huge files. Test results show its efficiency and
success.
The objective of this module is to provide an overview of the basic information on big data.
Upon completion of this module you will:
-Comprehend the emerging role of big data
-Understand the key terms regarding big and smart data
- Know how big data can be turned into smart data
- Be able to apply the key terms regarding big data
Duration of the module: approximately 1 – 2 hours
Efficient Data Filtering Algorithm for Big Data Technology in Telecommunicati...Onyebuchi nosiri
Efficient data filtering algorithm for Big Data technology Telecommunication is a concept aimed at effectively filtering desired information for preventive purposes, the challenges posed by unprecedented rise in volume, variety and velocity of information has necessitated the need for exploring various methods Big Data which is simply a data sets that are so large and complex that traditional data processing tools and technologies cannot cope with is been considered. The process of examining such data to uncover hidden patterns in them was evolved, this was achieved by coming up with an Algorithm comprising of various stages like Artificial neural Network, Backtracking Algorithm, Depth First Search, Branch and Bound and dynamic programming and error check. The algorithm developed gave rise to the flowchart, with each line of block representing a sub-algorithm.
Information Systems is a set of interrelated components that collect (input), manipulate (process), store, and disseminate (output) data and information and provide a feedback mechanism to meet an objective.
The talk will cover in broad strokes the building blocks, facilitators and challenges for big data based decision making.
Using examples from two projects from very dissimilar domains (High tech manufacturing and Public Health) Dr. Vinze will present possibilities for Data Science for both practitioners and academic researchers.
Implementation of application for huge data file transferijwmn
Nowadays big data transfers make people’s life difficult. During the big data transfer, people waste so
much time. Big data pool grows everyday by sharing data. People prefer to keep their backups at the cloud
systems rather than their computers. Furthermore considering the safety of cloud systems, people prefer to
keep their data at the cloud systems instead of their computers. When backups getting too much size, their
data transfer becomes nearly impossible. It is obligated to transfer data with various algorithms for moving
data from one place to another. These algorithms constituted for transferring data faster and safer. In this
Project, an application has been developed to transfer of the huge files. Test results show its efficiency and
success.
Information technology in global arena & enterprise resource planningSubhajit Bhattacharya
INFORMATION TECHNOLOGY IN GLOBAL ARENA & ENTERPRISE RESOURCE PLANNING. This presentation describes how Information Technology is overall impacting the global arena and how IT is necessary for the organizational growth in the competitive global market.
Role of ERP and how ERP can further enables business to run more productively and bring organization wide growth. The key constraints to identify the correct ERP suite. An overview of ERP project management and ERP as a service on cloud infrastructure.
Effective handling of Complaints - Optimizing the use of ICT in Law EnforcementChukwuebukaUgwu4
Effective handling of Complaints - Optimizing the use of ICT in Law Enforcement
Talk by Ebuka Ugwu at Civil Society Legislative Advocacy Center (CISLAC) Information Officers Workshop
Thursday, 29th August 2019
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BUSINESS INTELLIGENCE
TECHNOLOGIES USED IN BUSINESS ANALYST:
Data Warehousing
Dashboards
Ad Hoc Reporting
Data Discovery
Cloud Data Services
BI TECHNOLOGIES USED:
SAP Business Intelligence
Tableau
TIBCO Spotfire
SAS Business Intelligence
MicroStrategy
Sisense
Yellowfin BI
Dundas BI
Systum
Microsoft Power BI
Looker
Clear Analytics
domo
Oracle BI
QlikView
Overview of major factors in big data, analytics and data science. Illustrates the growing changes from data capture and the way it is changing business beyond technology industries.
Information systems are combinations of hardware, software, and telecommunications networks that people build and use to collect, create, and distribute useful data, typically in organizational settings.
Many businesses use information technology to complete and manage their operations, interact with their consumers, and stay ahead of their competition. Some companies today are completely built on information technology, like eBay, Amazon and Google.
Inter - I Year - Commerce - Sources of Business Finance - Meaning - Nature - Significance - Classification of sources of funds - Factors determining the choice of sources of finance
Inter - I Year - Commerce - Formation of a company - Important documents - Memorandum of Association - Its Clauses - Articles of Association - Contents - Prospectus
Definition of Business, Characteristics or Features and Objectives of Business - PPT for Junior Intermediate - Commerce - Andhra Pradesh State in India
Sources of Data-Primary Sources of Data & Secondary Sources - Data collection methods - Collection Methods-
Interviews: Structured Interviews and Unstructured Interviews etc
Research Design -Definitions -Features - Steps in Planning Research Design - Types of Research Design - Exploratory, Descriptive, and Causal Research Designs
ETHICS AND BUSINESS RESEARCH - Ethics in business research refers to a code of conduct or expected societal norm of behaviour while conducting research. ETHICS IN SOCIAL SCIENCE RESEARCH
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The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
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June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
R18 unit-1-tk-part-1-technologies in research
1. U N I T 1
T E C H N O L O G I E S U S E D I N BU S I N E S S R E S E A R C H
DR. THULASI KRISHNA. K
2. INFORMATION NEEDS OF BUSINESS
• To run a business, useful, timely, accurate, reliable, and valid data are needed.
When data in their raw form are evaluated, analyzed, and synthesized, useful
information becomes available to managers that helps them make good business
decisions.
• Ex: Regional sales statistics, competitors‘ sales and strategies, and the like
3. TECHNOLOGIES USED IN BUSINESS RESEARCH
• Internet
The internet began in 1969 as an experimental hook-up between computers at
Stanford University, The University of California at Santabarbara and the
University of Utah (USA) in conjunction (combination) with the Department of
Defence,America.
4. • The internet is helpful to get information about any industry easily.
Information can also be obtained from un-published materials on any topic of
interest.
• One can easily download secondary data and print them as well.
• One can also conduct computer-interactive surveys very efficiently with large
global audiences
5. Electronic Mail
• Electronic mail, most commonly referred to as email or e-mail since 1993.
Today's email systems are based on a store-and-forward model.
• Email servers accept, forward, deliver, and store messages.
• Neither the users nor their computers are required to be online
simultaneously; they need connect only briefly, typically to a mail server, for as
long as it takes to send or receive messages.
6. An E-mail address consists of two parts, separated by ‘@’ symbol. ‘.Com’ indicates that it is a
commercial site. Educational sites end in ‘edu’ or ‘ac.in’, Government sites end in ‘gov’ and
other types of organizations end in ‘.org’.
i. E-mail is inexpensive, almost instantaneous
ii. Guaranteed delivery subject only to the correctness of the e-mail address.
iii. E-mail is a simple and effective way of requesting and obtaining data on a variety of topics
from both within and outside the organization. Short surveys could also be conducted via e-
mail. Several cyber cafes offer access to the Internet for those who do not own or have ready
access to a computer.
7. • World-wide Web
The World Wide Web (www, W3) is an information system of
interlinked hypertext documents that are accessed via the Internet. Tim Berners-Lee (a
British Computer Scientist) invented the World Wide Web in 1989.At the time,Tim was
a software engineer at CERN, the large particle physics laboratory near Geneva,
Switzerland.
8. • The ‘WWW’ refers that portion of the internet made up of servers that supports a
retrieval system that organizes information in to documents called web pages.
WWW documents which may include graphic images, video clips and sound clips
are formatted in special programming languages such as Hyper Text Mark-up
Language (HTML) and Extensible Mark-up Language (XML) that allow for displaying
to linking and sharing of information on the internet.
9. TOP QUALITATIVE DATA ANALYSIS SOFTWARE IN 2018
• Nvivo,ATLAS.ti, QDA Minor, MAXQDA, HyperRESEARCH,WebQDA, Xsight,
Focus On, Raven’s Eye,Annotations
• Omnia Pricewatch , QuestionPro , Dub InterViewer , DataPlay ,The
Survey System
10. SOME SOFTWARE USED IN BUSINESS RESEARCH
• Groupware
Groupware is software that runs on a network so that teams can work on joint
projects, and it allows people from different departments to access data jointly.
For example, if the accounting, finance, sales, and production departments have
to coordinate their efforts to come up with a viable product within a tight
budget, they will be served well by groupware.
This software is of immense use for efficient and effective completion of specific
team projects.
11. • Neural Networks
Neural Networks are designed to trace patterns in a set of data and generalize there
from.
This software enables sales forecasts, stock market predictions, detection of weather
patterns, and the like.
Neural networks offer a number of advantages, like requiring less formal statistical
training, ability to implicitly detect complex non-linear relationships between
dependent and independent variables, ability to detect all possible interactions
between predictor variables, and the availability of multiple training algorithms.
13. • CAM/CAD
Computer-aided manufacturing (CAM) software helps engineers to design the
manufacturing components and directs the production of the product.
Computer-aided design (CAD) software creates and displays complex drawings with
precision, enabling experimentation with different designs.
Design sophistication and product development are made possible by this
programme, and this software is extensively used by manufacturing organizations.
14. • Enterprise Resource Planning
Enterprise resource planning (ERP) is business management software that a
company can use to collect, store, manage and interpret data from many business
activities, including product planning, cost, manufacturing or service delivery,
marketing and sales, inventory management and shipping and payment.
15. • ERP provides an integrated view of core business processes, often in real-time,
using common databases maintained by a database management system. ERP
systems track business resources—cash, raw materials, production capacity—and
the status of business commitments: orders, purchase orders, and payroll.
• The applications that make up the system share data across the various
departments (manufacturing, purchasing, sales, accounting, etc.) that provide the
data.
16. • The advantage of ERP packages is their capability to provide comprehensive
solutions to all the needs of an organization in its day- to-day work.
• This is so because they provide complete support for the executive support
system and the Management Information System (MIS), and can work with all
existing data bases built on different platforms.
• Software developers use various tools to build and modify data tables and
develop custom functionality.
17. • Data Analytic Software Programmes
Software programmes are available to obtain, store, and analyze raw data collected
through surveys, using Statistical Package for the Social Sciences (SPSS), Statistical
Analysis System (SAS), Excel, and the like.
Sophisticated business presentations of the results obtained from data analysis
are also possible through computer graphics and interactive CDs.
18. i. Gathering data is facilitated through audit capabilities in software that track and provide
information on the extent of usage of any function or feature.
ii. It is now feasible to analyze online purchase requisitions for office supplies to determine
frequency, volume, and type of purchases.
iii. A company can track the number of times its web site has been visited and the duration of
such visits, so as to evaluate its appeal and improvise it, as needed.
With a little more programming effort and the co-operation of the visitors to the site, more
information on user profile can easily be obtained to assess buying preferences and market
demographics information useful for developing marketing strategies.
19. Multimedia computers combine text with sound, video animation, and graphics— all
vital in business communication and presentations. Connectivity, which enables even
incompatible software and hardware to share information and resources through the
use of a communication network, will enable us to access information even more easily
in the future.
Designing questionnaires, collecting data, data analysis, and web and e-mail surveys are
facilitated by several software programmes, including SumQuest or SQ Survey Software,
Professional Quest, and Perseus.
20. • GroupVideoconferencing
Group videoconferencing reproduces the face-to-face meeting effect by using large TV
monitors or multimedia projectors.
Videoconferencing systems have the advantage of integrating with other vital business
technologies like spreadsheets and presentation software. Thus, much data (including
numerical figures) can be exchanged during videoconferencing as organizations try to
engage in consultative decision making and further research and analysis.
Videoconferencing has become even more attractive in the post terrorist business
environment on considerations of cost and safety.
21. • Virtual Reality
Virtual reality creates 3-D environments in which to create a product in a computer and
show it to prospective interested groups with details regarding price, materials, and
other relevant information.
Greeting messages with virtual flowers can compete with Hallmark cards in a big way in
the future.
22. • Linkage of PCs to Electronic Devices
One of the latest efforts being made by Microsoft and Sony is to link PCs and consumer
electronic devices.
For instance, a company can plug a camcorder to a PC or to a TV set top box for
sending video mail over the Internet.
Business transactions, communication, and research through this mode will be
accelerated multifold when the device is perfected.
23. INFORMATION SYSTEMS AND MANAGERIAL DECISION MAKING
• Data Warehousing, Data Mining, and Operations Research
Data warehousing and data mining are aspects of information systems. Most companies are
now aware of the benefits of creating a data warehouse that serves as the central repository
of all data collected from disparate sources including those pertaining to the company‘s
finance, manufacturing, sales, and the like.
The data warehouse is usually built from data collected through the different departments
of the enterprise and can be accessed through various on-line analytical processing (OLAP)
tools to support decision making.
24. • Data warehousing can be described as the process of extracting, transferring, and
integrating data spread across multiple external databases and even operating systems,
with a view to facilitate analysis and decision making.
25. • Complementary to the functions of data warehousing, many companies resort to data
mining as a strategic tool for reaching new levels of business intelligence.
• Using algorithms to analyze data in a meaningful way, data mining more effectively
leverages the data warehouse by identifying hidden relations and patterns in the data
stored in it.
• Data mining helps to clarify the underlying patterns in different business activities, which
in turn facilitates decision making.
26. • Operations research (OR) or management science (MS) is another sophisticated tool used to
simplify and thus clarify certain types of complex problems that lend themselves to
quantification.
• OR uses higher mathematics and statistics to identify, analyze, and ultimately solve intricate
problems of great complexity faced by the manager.
• Areas of problem solving that easily lend to OR include those relating to inventory, queuing,
sequencing, routing, and search and replacement.
• OR helps to minimize costs and increase efficiency by resorting to decision trees, linear
programming, network analysis, and mathematical models.