Securing Higher Grades Costing Your Pocket? Book Your Assignment at The Lowest Price Now!

Business Intelligence Using Big Data : Business Operations

tag 4 Downloads15 Pages 3,741 Words tag Add in library Click this icon and make it bookmark in your library to refer it later. GOT IT


Describe about the Business Intelligence Using Big Data for Business Operations.




Big data is developing continuously as a result it helps in producing a large sum of income from the business operations. It is analyzed that the use case of big data requires some special operations and therefore the structure that is produced with the arrangement of hardware and software provides a technological effect. It is stated by Akerkar (2013 ), that big data analytics are very much useful for outlining new strategies, which helps in managing technology at a faster rate. It also helps in providing precise results from the skills used.

In this report, analysis of big data has been used for forming strategies that would help in supporting the decision-making system of a selected organization. IBM is chosen for implementing big data procedure.  The procedures or strategies of big data have been created for IBM. The report also discusses stack technology that is used for implementing data analytics. The procedure is associated with the recovery, storage and creation analysis of data. There are number of features that are provided by the big data, and those features include diversity, rapidity and volume in the examination of big data. The main objective of this report is to implement the big data framework for the usefulness of different business operations in IBM.

Identification, creation and discussion of business strategy for using of big data in IBM

Identification of business strategy framework

The implementation procedure of big data in any business needs a framework for understanding the basic operations (Assuncao et al. 2013). IBM needs to construct and implement a big data structure in the operational structure. The two dimensions on which big data framework is dependent include Business objectives and Data type.

 Strategy Framework of IBM for Big Data

Figure1: Strategy Framework of IBM for Big Data

Source (Assunção et al. 2015)

Creation of Business Strategy Framework

Transactional Data

Methods  used

Business Intelligence: The technique of business intelligence that is used by IBM is user friendly and thus it helps in interactive and multidimensional data analysis (Begoli and Horey 2012). It also provides different features such as rolling up, reporting the capabilities tools and many more.

Cluster analysis: It helps in analyzing those objects that have similar attributes and properties.

Data Mining: It is used by the organization for extracting as well as processing new patterns.

Predictive Models: IBM creates models in order to predict the results from an activity (Buhl et al.2013).

SQL: SQL is used for extracting, inserting and managing the values or data in a database.


 It helps in reporting the services and the analysis from the server with the help of Microsoft SQL (Chaudhuri 2012). It also helps in providing the business objectives from SAS, SAP, and Business intelligence by using Oracle.


Non- Transactional Data

Methods Used

Crowd Sourcing: IBM uses the technique of crowd sourcing for getting the required services, content or ideas by soliciting contributions from a huge mass of people (Chen et al. 2012).

Textual Analyzing: The organization uses the method of textual analysis for analyzing the different content of communication rather using the structure of the content.

Analysis of Sentiments: The organization uses the process of sentiment analysis for determining the results of analysis. The results can be positive, negative or neutral (Demirkan and Delen 2013).

Network Analysis: IBM uses the procedure of network analysis for calculating the relationship between the elements of networks and nodes.



Visible technologies, Watson services, Radian6 and many more;

Discussion of Business strategy framework of IBM

The different business strategy framework of IBM includes:

Performance Management: It is very much easy as well as helpful in accepting the analytics as well as database of big data. Performance management is useful in order to determine the multidimensional queries and related analytics in the organization (Gandomi and Haider 2015). For example, the big data strategy framework is used for analyzing the purchasing activity, expected turnover of the organization. It helps the managers in making short times and long time decision as well as plans. The functionality of different business intelligence tools is very much helpful for improving both the management and the business operations of the organization.

Data Exploration: The data exploration framework is helpful in using the different procedures of data analytics in order to experiment and answer the questions, which has not been properly thought by the management of IBM (Jagadish et al. 2014). It also helps in implying the different predictive models for managing the user-based behavior in different sections of operation such as management and in transaction department of IBM. Big data helps the organization by supplying information and by designing strategies that would help in retaining the various segments of the users.

Social Analytics: Social analytics framework is very much helpful for the organization as it helps in measuring the huge amount of non-transactional data such as reviews and platform of social media. The big data strategy is categorized by the social analytics (Katal et al. 2013). The three wide divisions of big data strategy include awareness, engagement and reach of the analysis. Engagement is helpful in measuring the level of interaction and involvement among the team members. Awareness helps in checking the exposure of knowledge in very group members. The members of the organization are quantified based on the level of knowledge and about any particular business function.

Decision Science: Decision science helps in analyzing the data that are not related in to the transaction. The big data helps in exploring the rules and regulation in order to focus on the hypothesis and field research (Lazer et al. 2014). It is very much helpful for the IBM for conducting different feedbacks from the community. It helps in fitting both the ideas and it is also used for developing the value of a product.  In order to perform the text analysis of sentiment, it needs listening tools (Liebowitz 2013). IBM uses the tools in order to measure the topics that are related with development and interested products.


Identification and aligning the business strategy’s initiative, objective and the task of IBM

Identification of Business strategy

Aligning the formed strategy with objective, Initiatives and task

Integration of multiple strategies of big data

 Big data can be implemented for multiple uses and thus the company can levitate for combining the strategies of big data (Lohr 2012). For example, Performance management is useful in gaining better production for forming synchronization with the demands and needs of the customers.

Building capabilities of big data

 It is a technology or a process that is required for supporting the initiatives of big data. A plan must be devised by the expertise in order to implement the strategy of big data (Mayer-Schönberger and Cukier 2013).The organization, IBM has to hire skilled managers for guiding the employees who take care of the big data. It is helpful for creating specific group structures in order to focus on the big data analytics and business management.

Proactive creation of big data policy

 IBM needs to update itself with the guidelines and policies for using the big data (Minelli et al. 2012). It is helpful in accessing non-transactional and social data for creating and accessing business operations. Therefore, IBM is greatly influenced by the security and privacy of the business operations.

Analysis of Technology Stack for IBM big data

The technology stack of big data analytics of IBM has analyzed some components, which are helpful in forming the analytics. Both external as well as internal data sources are required in the market analysis of IBM, which are shown by the different sources (Moniruzzaman and Hossain 2013). For analyzing data, it creates a lake of data. In order to perform the data analytics procedure, stack technology consists of 3V is which are variety, velocity and volume. Volume consists of various amounts of data that needs to be stored and managed. Variety consists of various types of data that are used in the analytics of big data (Raghupathi and Raghupathi 2014). Variety means the various types of data that are used in the big data analytics. Velocity is defined as a speed in which the data in stack technology are recorded and processed.

There are different kinds of stack technologies that are used in order to create the architecture of big data analytics in IBM.

PIG:  A scripting technology is used for processing and analyzing huge quantity of data sets (Sagiroglu and Sinanc 2013).In order to access the engines, apache pig consists of an architectural structure, which also helps in storing clusters of data.

YARN: It is one of the acronyms for resource navigator, which is helpful in large-scale data application for distributing the operating system (Shroff et al. 2013).It is very much helpful in combining both the synchronized as well as central resource managers for reconciliation.

Hive: This stack technology is useful in summarizing, querying and for analyzing the data which will be helpful for the business insights (Vera-Baquero et al. 2013).The tables that are present in hive are organized in the pattern of granular units for creating the taxonomy.


Data analytics and MDM for supporting the business intelligence and decision making of IBM

Data analytics: There are three challenges that are required in the management process of big data. The challenges are sorted with the help of the big data analytics. Right data is selected by them in order to handle the operations of data analytics and for using the insights that are gained for transforming the different operations of business (Waller and Fawcett 2013). Big data analytics helps in managing the big data and helps in advancing their analytics. It is very much beneficial in order to deal with the lack of analytical talent that is needed for implementing the big data analytics. It is helpful in creating new roles for job. Big data is acting as revolution in the fields of analytics measurement and administration.

 The big data analytics is helpful in driving data for the process of decision-making in the business operations of IBM. There is a lot of difference between the data driven and information collected in IBM. It is analyzed that the chances of data lose is more when the data are stored for longer period (Wixom et al. 2014). Big data analytics and business analytics helps in analyzing the data that were stored long before as a result they helps in creating effective results by using it. IBM is benefitted by the big data analytics because each data has role, which in turn helps in assisting the process of decision-making.

Master Data management: A method helps in identifying the most important as well as critical data of IBM in order to create a singular source of data for managing the business. It involves different technological solutions to improve the big data processing as well as management, which includes data integration, quality, and management (Wu  et al. 2014).The following characteristic of MDN is helpful in supporting the decision-making system of the organization and its business intelligence.

Standard Data view: It is helpful in creating single view in order to authorize the critical business management. The MDN process is used by the IBM data analytics in order to resolve the issues such as data disputation, duplication and many more (Begoli and Horey 2012). For example, two people having the same first name will create a trouble in entering the data as a result big data analytics can be used for drawing their last name and addresses in order to distinguish between the two individuals.

Complete overview of the relationship: MDN is a big data analytics that helps in identifying the relationship among the different data entity. It will help the organization in combining one data entity with the other based on the relationship of the coefficient. For example, IBM uses MDN to store the names of the purchaser.

Managing interactions: It is used in order to integrate the occurrence and transaction of social interaction between the clients and the operators of the business (Chaudhuri 2012). It will create a bridge between the customers and data channel partners in order to complete the views of the customers of IBM.

Design features: The factors behind the efficient and proper management of big data analytics include flexibility of the design model, Variability of model operation and scalability functions (Demirkan and Delen 2013). IBM uses all this features in order to use its data analytics. The MDN system does not need coding for its implications therefore and thus it can be easily applied in IBM. The agility of the software process is helpful in creating the focus of the database on the success of the customers.

Analyzing support of NoSQL for big data analytics in IBM

NoSQL or non-related SQL is helpful in giving various facilities for the big data analytics, which includes scalability, observable alternative different association of strengths, many multinational organizations like Amazon (Gandomi and Haider 2015). Google uses big data NoSQL for working with the operational database.

NoSQL has different characteristics for user-friendly advance, which helps in creating and easing the operations of the business database administration properly (Liebowitz 2013). NoSQL is helpful in empowering most of the organizations.

NoSQL consists of various systems such as payroll systems, reluctance system and data processing system.

NoSQL will be helpful in processing unpredictable as well as unstructured information system in order to provide help to the big data information management of IBM (Lohr 2012).

NoSQL assists in solving different bottleneck errors by processing the unstructured database System (Minelli et al. 2012). Hence, the big data purpose of IBM can be managed by using the system of NoSQL.

NoSQL is not required for knowing the structure beforehand. This is because the system does not lack schema orientation (Raghupathi and Raghupathi 2014). The system is helpful in solving the data, which is arised due to acid property of the data analytics.


Different types of NoSQL databases and its use in big data of IBM

Various types of NoSQL databases


Use in Big Data use case of IBM

Key value store

 It consists of big hash based table of keys and values

Example: Riak used by Amazon

 The schema format of this NoSQL database is helpful in forming the database that is value based. This type of key is helpful in creating as well as generating auto type of data base system (Sagiroglu and Sinanc 2013). IBM can use the system for creating auto-generated database in big data analytics.

Document based store

 It helps in storing elements that are made up of tagged elements

Example: couchDB

 The database of NoSQL format uses various types of key and value pair in order to store the values of the data (Shroff et al. 2013). It is very much helpful for IBM for creating structure and encoding for managing the big data analytics

Column based store

Each block of storage consists of data that is formed from one column of the system table

Example: Cassandra and HBase

 In this type of database schema, the data is stored in row cells instead of column cells. It is helpful for IBM as it provides the organization with the ease of accessing and fast searching (Waller and Fawcett 2013).The big data that is stored in this type off scheme is helpful in aggregating the data on a single column.

Graph based

 It is a type of database that uses nodes and edges for storing and representing data over the system table

Example: Neo4J

 Graph based NoSQL database schema is pictorial representation of database that in based on the structure of flexible data values structure (Assuncao et al. 2013). It is helpful as it provides IBM the ease of transformation of scheme from one model structure to different model structure (Begoli and Horey 2012). The graph consists of edges and nodes therefore it in helpful in creating elation among the nodes of the data.

Role of social media in the decision making process of the organization

The social networking plays a crucial function in big data analytics and management of database. It is very much helpful in creating advertisement of the database administration of big data analytics (Buhl et al. 2013). It is helpful in the process of proficient decision-making processes, which became social. The habitual influential cycle of the functions is disrupted with the help of social media and networking. The manager uses the social networking for informing as well as validating the decisions that are related with the big data.

According Demirkan and Delen (2013), the facilities that the social media provides includes:

Helps in searching the feedbacks and responses of the customers or clients

It helps in enhancing the partnership with others.

The reliability of the information is improved (Gandomi and Haider 2015).

Business decisions are researched over the global market

Helps in accessing information or data that are unavailable everywhere

It helps in keeping eye on the co-worker and colleagues (Lazer et al. 2014)


Evaluation of Big Data Value creation process

The big data formation process is vast probable in any business. The procedure is very much useful in forming a link between the providers and the customers. The procedure of big data consists of various processes, which includes inventory, manufacturing distribution and marketing (Lohr 2012).The products or services have to go through number of procedures in order to meet the needs and necessities of the customers. It is stated by  Demirkan and Delen (2013), that the steps that are helpful for the company includes:

Manufacture of goods

Creating inventory of products and services

Study of physical resources (Waller and Fawcett 2013).

delivery to retail shops

Mass advertising of goods

It is stated by Moniruzzaman and Hossain (2013), the value creation procedure of IBM   includes:

Increase in the number of clients

Improving the techniques of the market

Optimizing the supply chain (Sagiroglu and Sinanc 2013).

Reducing the price of the stir

Increasing the turnover of the inventory

Enhancing the effectiveness of hiring


It is concluded from the report that big data analytics is used in order to increase the revenue of an organization. Both hardware as well as software technology have affected the operations of the business. The big data analytics is very much useful in meeting the demands of the customers.  It is analyzed that in this assignment IBM is selected for the implementing procedure of big data analytics. The strategies that are used for big data analytics are created using the formation or creation procedure. It is concluded that the big data analytics is very much helpful in creating new technologies and it is extremely helpful in meeting the demands of the customers.



Akerkar, R. ed., 2013. Big data computing. CRC Press.

Assuncao, M.D., Calheiros, R.N., Bianchi, S., Netto, M.A. and Buyya, R., 2013. Big Data computing and clouds: challenges, solutions, and future directions. arXiv preprint arXiv:1312.4722.

Assunção, M.D., Calheiros, R.N., Bianchi, S., Netto, M.A. and Buyya, R., 2015. Big Data computing and clouds: Trends and future directions. Journal of Parallel and Distributed Computing, 79, pp.3-15.

Begoli, E. and Horey, J., 2012, August. Design principles for effective knowledge discovery from big data. In Software Architecture (WICSA) and European Conference on Software Architecture (ECSA), 2012 joint working IEEE/IFIP conference on (pp. 215-218). IEEE.

Buhl, H.U., Röglinger, M., Moser, F. and Heidemann, J., 2013. Big data.Business & Information Systems Engineering, 5(2), pp.65-69.

Chaudhuri, S., 2012, May. What next?: a half-dozen data management research goals for big data and the cloud. In Proceedings of the 31st ACM SIGMOD-SIGACT-SIGAI symposium on Principles of Database Systems(pp. 1-4). ACM.

Chen, H., Chiang, R.H. and Storey, V.C., 2012. Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), pp.1165-1188.

Demirkan, H. and Delen, D., 2013. Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud.Decision Support Systems, 55(1), pp.412-421.

Gandomi, A. and Haider, M., 2015. Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management,35(2), pp.137-144.

Jagadish, H.V., Gehrke, J., Labrinidis, A., Papakonstantinou, Y., Patel, J.M., Ramakrishnan, R. and Shahabi, C., 2014. Big data and its technical challenges. Communications of the ACM, 57(7), pp.86-94.

Katal, A., Wazid, M. and Goudar, R.H., 2013, August. Big data: issues, challenges, tools and good practices. In Contemporary Computing (IC3), 2013 Sixth International Conference on (pp. 404-409). IEEE.

Lazer, D., Kennedy, R., King, G. and Vespignani, A., 2014. The parable of Google flu: traps in big data analysis. Science, 343(6176), pp.1203-1205.

Liebowitz, J. ed., 2013. Big data and business analytics. CRC Press.

Lohr, S., 2012. The age of big data. New York Times, 11.

Mayer-Schönberger, V. and Cukier, K., 2013. Big data: A revolution that will transform how we live, work, and think. Houghton Mifflin Harcourt. Zaman, N., Seliaman, M.E., Hassan, M.F. and Marquez, F.P.G., 2015.Handbook of Research on Trends and Future Directions in Big Data and Web Intelligence. Information Science Reference.

Minelli, M., Chambers, M. and Dhiraj, A., 2012. Big data, big analytics: emerging business intelligence and analytic trends for today's businesses. John Wiley & Sons.

Moniruzzaman, A.B.M. and Hossain, S.A., 2013. Nosql database: New era of databases for big data analytics-classification, characteristics and comparison. arXiv preprint arXiv:1307.0191.

Raghupathi, W. and Raghupathi, V., 2014. Big data analytics in healthcare: promise and potential. Health Information Science and Systems, 2(1), p.1.

Sagiroglu, S. and Sinanc, D., 2013, May. Big data: A review. In Collaboration Technologies and Systems (CTS), 2013 International Conference on (pp. 42-47). IEEE.

Shroff, G., Dey, L. and Agrawal, P., 2013. Social Business Intelligence Using Big Data. CSI Communications, pp.11-16.

Vera-Baquero, A., Colomo-Palacios, R. and Molloy, O., 2013. Business process analytics using a big data approach. IT Professional, 15(6), pp.29-35.

Waller, M.A. and Fawcett, S.E., 2013. Data science, predictive analytics, and big data: a revolution that will transform supply chain design and management. Journal of Business Logistics, 34(2), pp.77-84.

Wixom, B., Ariyachandra, T., Douglas, D., Goul, M., Gupta, B., Iyer, L., Kulkarni, U., Mooney, J.G., Phillips-Wren, G. and Turetken, O., 2014. The current state of business intelligence in academia: The arrival of big data.Communications of the Association for Information Systems, 34(1), p.1.

Wu, X., Zhu, X., Wu, G.Q. and Ding, W., 2014. Data mining with big data.IEEE transactions on knowledge and data engineering, 26(1), pp.97-107.


Cite This Work

To export a reference to this article please select a referencing stye below:

My Assignment Help. (2018). Business Intelligence Using Big Data : Business Operations. Retrieved from

"Business Intelligence Using Big Data : Business Operations." My Assignment Help, 2018,

My Assignment Help (2018) Business Intelligence Using Big Data : Business Operations [Online]. Available from:
[Accessed 10 December 2019].

My Assignment Help. 'Business Intelligence Using Big Data : Business Operations' (My Assignment Help, 2018) <> accessed 10 December 2019.

My Assignment Help. Business Intelligence Using Big Data : Business Operations [Internet]. My Assignment Help. 2018 [cited 10 December 2019]. Available from:

With time, has become one of the best college essay writing services. Our all rounded services give students the confidence to overcome assignment related issues. Our services are fast enough to meet most urgent deadlines. We are capable of delivering fast essay writing services with the help of our specially designed provisions and writers' teams. Our urgent essay help services guarantee most rapid delivery of assignment solutions. Some of our most popular essay services are application essay help, exploratory essay help, literary review essay help and argumentative essay help.

Latest It Write Up Samples

HI5019 Strategic Information Systems 4

Download : 0 | Pages : 16

Answer: Introduction Westpac Banking Corporation is an Australia based bank and other financial services, provider. This organization is commonly known as Westpac Bank. Company headquarter is located at 275 Kent St, Sydney, New South Wales. Name of the bank Westpac is a Portmanteau of Western and Pacific. Bank is reported in the list of Australia’s “Big Four” Banks. As per 2018, the bank has around 4 million customers served...

Read More arrow

HC1041 IT For Business 4

Download : 0 | Pages : 9

Answer: Introduction Implementation of the information technology has been acting as one of the major technological advancement in today’s society. The usage of the information technology has been proven beneficial in the case Small and Medium sized enterprise. This is the main prospect that leads to increase in efficiency of the commencing of the business processing. This report deals with the advantages and disadvantages that are pres...

Read More arrow

ITC561- SLA Management For Its Proposed IaaS And PaaS Instances

Download : 0 | Pages : 6
  • Course Code: ITC561
  • University: Charles Sturt University
  • Country: Australia

Answer:   Remote Server Administration Tools: This is a special requirement since the Windows 8 is any need of the incorporation for server manager systems, the Microsoft management control snap-ins the Windows PowerShell cmdlets and the other suppliers. The entire arrangement for remote server administration tools for the organization also would like to include the tools that incorporates command-line and helps in controlling the fea...

Read More arrow

HC3152 E Business Applications

Download : 0 | Pages : 9

Answer: Introduction  Vodafone Australia is also known as Vodafone Hutchison Australia is a telecommunication which provides internet service to the Australian people (Mitra et al. 2016). After merging with Hutchison 3G Australia in the year 2009, it has become third largest mobile store with more than 6 million subscribers. The organization comes up with 3.5 billion annual revenues which makes it as third largest organization after Tels...

Read More arrow

SIT717 Enterprise Business Intelligence

Download : 0 | Pages : 6

Answer: Introduction This activity is intended to give the great chance to utilize the data mining and machine learning in strategy in discovery knowledge from a dataset and investigate the applications for business knowledge. This task investigation the health news dataset to investigate the weka data mining applications. This task partitioned in to 10 reasonable. In First, we will introduce the weka programming and download the Data archive...

Read More arrow

Save Time & improve Grades

Just share your requirements and get customized solutions on time.

We will use e-mail only for:

arrow Communication regarding your orders

arrow To send you invoices, and other billing info

arrow To provide you with information of offers and other benefits




Overall Rating



Our Amazing Features


On Time Delivery

Our writers make sure that all orders are submitted, prior to the deadline.


Plagiarism Free Work

Using reliable plagiarism detection software, only provide customized 100 percent original papers.


24 X 7 Live Help

Feel free to contact our assignment writing services any time via phone, email or live chat.


Services For All Subjects

Our writers can provide you professional writing assistance on any subject at any level.


Best Price Guarantee

Our best price guarantee ensures that the features we offer cannot be matched by any of the competitors.

Our Experts

Assignment writing guide
student rating student rating student rating student rating student rating 5/5

610 Order Completed

100% Response Time

Cheryl Zhao

PhD in Statistics

Singapore, Singapore

Hire Me
Assignment writing guide
student rating student rating student rating student rating student rating 5/5

265 Order Completed

97% Response Time

Ken Campbell

MSc in Electrical Engineering

Wellington, New Zealand

Hire Me
Assignment writing guide
student rating student rating student rating student rating student rating 5/5

416 Order Completed

95% Response Time

Tyler Moore

MBA in Accounting

Washington, United States

Hire Me
Assignment writing guide
student rating student rating student rating student rating student rating 5/5

2279 Order Completed

97% Response Time

Zachary Perez

PhD in Computer Science and Information System

Washington, United States

Hire Me

FREE Tools


Plagiarism Checker

Get all your documents checked for plagiarism or duplicacy with us.


Essay Typer

Get different kinds of essays typed in minutes with clicks.


GPA Calculator

Calculate your semester grades and cumulative GPa with our GPA Calculator.


Chemical Equation Balancer

Balance any chemical equation in minutes just by entering the formula.


Word Counter & Page Calculator

Calculate the number of words and number of pages of all your academic documents.

Refer Just 5 Friends to Earn More than $2000

Check your estimated earning as per your ability




Your Approx Earning

Live Review

Our Mission Client Satisfaction

Thank you for the professional writing and the time-efficient. I would recommend to my friend for sure


User Id: 349555 - 10 Dec 2019


student rating student rating student rating student rating student rating

It was very well written and a good assignment with the amount of time that was allotted.


User Id: 235137 - 10 Dec 2019


student rating student rating student rating student rating student rating

DO NOT USE THIS COMPANY.... Hopeless, poor grammar and unable to meet brief. A week of arguing and finally redid work which was just as hopeless as first attempt.


User Id: 303057 - 10 Dec 2019


student rating student rating student rating student rating student rating

The report was well written and helped me get the mark which I would have got If I had the time to do it. thank you for helping me pass the unit.


User Id: 318318 - 10 Dec 2019


student rating student rating student rating student rating student rating
Have any Query?