Business Intelligence Vs Big Data

Business Intelligence Vs Big Data

Big data can be defined as the data sets which are way wider to be processed through conventional data processing techniques and applications whilst it would be differentiated from data which can usually be managed or handled using the toolsets like Microsoft Excel. Be that as it may, big data could be described as an entity and that of business intelligence is a procedure about what would be done with the entity big data (Heet al.2017, p.552). In the field of data science, business intelligence involves data regardless of it is big or normal and is responsible for extracting the needful information from the same. Therefore, it would end up assorting methodologies, tools and application which continue allowing the accumulation of data from both the external as well as internal sources and systems, organising the same for analysis, developing and running queries against the dataset. In addition to that business intelligence also involves creating visualisations and reports for presenting the outcomes in an easily understandable manner (Deyet al.2018, p.2076). This essay is going to analyse the significant differences between big data and business intelligence. However, for doing so a comparative analysis in terms of both the benefits as well as drawbacks, between these two business data handling approaches is going to be done. In addition to that, the discussion is going to portray the inter-relationship between business intelligence and big data on to of that the interlink between data science and business intelligence would also be paid attention to in the following discussion.Additionally, the tools and techniques involved in the procedures of business intelligence and big data are noticed to differ also.

The Comparison Between Business Intelligence And Big Data In Terms Of The Technical Concepts Associated With Them

Big data are nothing but the larger data sets which outgrow the architectures of simple data handling and databases. For instance, data which cannot be handled easily in the excel spreadsheets might be considered as big data. In addition to that, it involves the procedure of storing, visualizing and process of data whilst it is significant to identify the effective tools to create the best data environment in order to obtain successfully the insights from the operational data. Notwithstanding that development of a viable data, the environment requires the utilization of infrastructural technologies which would store, facilitate and process data analysis (Heet al.2017, p.552). As per assignment tutor view modelling language programs, OLAP cubes and data warehouses are the applicable infrastructural technologies used in processing, storing and cultivating the process of data analysis. It is needed to be mentioned here in this context of the analysis that nowadays businesses at time utilize the multiple numbers of infrastructural deployments with the aim of managing different aspects associated with the business data. On the other hand, time and again big data would resolve the queries of the business organizations relating to the way the new human resource software is going to impact the performance of the employees and the standpoints of the target audience of the company regarding sales and so on like these. Therefore, it can be said that an analysis of the sources of big data ends up illuminating the link between various facets associated with the business. Subsequently, there must be inherent applications to the information which is gathered in big data on top of that the businesses ought to develop relevant parameters and objectives for gleaning impactful insights from big data (Deyet al.2018, p.2076).

Turning to the technical concept behind business intelligence, it can be said that it would encompass data analysis along with the capacity of uncovering insights, trends and patterns in the field of modern business and management. In addition to that, the findings on the basis of data are responsible for providing astute and accurate views relating to the business processes of a company whilst the outcomes of these procedures are yielding. However, beyond different standard aspects like financial assessments, a detailed business intelligence would reveal the effect of the present organizational practices and procedures on the performance of its workforce as well as the overall organizational satisfaction, media reach and conversions along with several additional factors (Frizzo-Barkeret al.2016, p.87). Be that like it may, assignment help experts extracted the application of business intelligence would forecast the upcoming organizational performance to present the information on the current organizational context of a business association. Even though the evaluation of the past and present information, the robust systems of business intelligence are responsible for tracking the trends as well as illustrating the way all these business trends are going to continue with the changing time. It is worth mentioning here that business intelligence not only encompass the observations but also it would move beyond the analysis whilst action would be taken on the basis of the findings. On the other hand, the capability of visualizing the quantifiable and real outcomes of the policy besides the impacts on the future of the business organization is considered as of the influential tool of business decision-making (Baggio, 2016, p.1132).

Business Intelligence Vs. Big Data

Figure 1. The Difference Between Business Intelligence And Big Data
(Source: Jin and Kim, 2018, p.1019)

Business intelligence is the combination of products and systems which have been applied in different business practices whilst it would not involve deriving information from the products and systems. On the other hand, big data is all about the vast size of a data set which is likewise used about particular approaches to the analytics. As the above diagram indicates business intelligence is associated only the traditional sources and that of business data analytics multiple numbers of sources. In addition to that business intelligence is used to draft the corporate reports whilst big data involves semi-structured data (Jin and Kim, 2018, p.1019). Apart from that business intelligence involves structured data whereas big data involves unstructured data. Notwithstanding that system of business intelligence is implemented for conducting descriptive as well as diagnostic analysis and that of big data is for predictive as well as prescriptive analysis. 

When it comes to comparing these two, it can be analysed that big data is responsible for supplying external information relating to the own data sources of a company, serving as one of the expensive resources. This, it is one of the potential elements of business intelligence, is responsible for providing a comprehensive aspect of the business processes. However, big data at times would constitute the information that is going to lead to the insights associated with business intelligence (Balachandran and Prasad, 2017, p.209). For more latest information, you can contact cheap assignment help where experts will help you to learn the tactics and tool of big data and control management.

Then again, it can be said that big data would end up existing in business intelligence what it means it that the two vary in the type and amount of data which they would include. Be that as it may, business intelligence is considered as an umbrella term whereas the data which is signified as a part of business intelligence would be relative all-inclusive while comparing with the one that comes under big data. In addition to that business intelligence consists of all the information from sales reports that are hosted in the excel spreadsheets to the wide online databases. On the other hand, big data would comprise the wider data sets only (Ramet al.2016, p.288).

In addition to that, the tools used in the processes of business intelligence and big data are noticed to differ alongside. It is noticed that the fundamental software of business intelligence holds the capability of processing the standard information sources whilst might not be equipped enough for managing big data. However, the base-level big data systems are essentially developed for processing big data (Liang and Liu,2018, p.1013).

It is quite evident that in the discussion of business intelligence versus big data, there is certain overlap implied in the application of comprehensive systems of business intelligence which are designed for handling the large data sets. There are a large number of business intelligence software vendors that continue offering the tiered price models that end up increasing operationality depending upon the price. Additionally, the capability of big data might likewise be offered due to an add-on to a software system of business intelligence (Dedićand Stanier, 2016, p.375). 

The Difference Between Business Intelligence And Big Data In Terms Of Their Applications

Applications In Retail

The advancement of e-commerce continues providing the consumers with multiple options with every passing day. However, business intelligence is used to track the way, the consumers would interact with the online stores whereas this information is emphasized for enhancing the consumer experience and services. For instance, a consumer might receive recommendations based on the items they have viewed recently. Business intelligence likewise allows retailing organizations to make efficient, smart decisions considering consumer behavior. However, this information would be visualized in real-time resulting in allowing the businesses to adjust the prices at once with altering commodities offerings (Liang and Liu,2018, p.1013). German assignment help categorizes the broad perspective of big data application which is current available at SourceEssay portal.

On the other hand, it is important for the retailers knowing the marketing trends with handling transactions and implementing strategies for improving revenue depending on the big data interpretation. For example, lingerie company name Ultimo based on Glasgow managed to increase its sales dramatically through analysing data relating to weather against data on the purchasing patterns of the consumers leading to the insights into consumer behaviour across which Ultimo brought about modifications in its business procedures (Ramet al.2016, p.288).

Applications In Education

The software of business intelligence for academic organizations is organised and specialized. Additionally, business intelligence software is applied in the educational institutions for reducing the administrative management complexities and thus for enhancing the level of their academic performances. Notwithstanding that the academic systems have been getting critical in the international industry with increasing options whereas there are billions of amounts have been expensed without having the skill of process analysis. Business intelligence software is the technology that is responsible for making the entire academic system less complex through dealing with multiple functions with a single system providing more information to the users (Sunet al.2018, p.322). 

On the other hand, big data analysis is responsible for tracking and showing the progress of the learners involving which learners are doing good and which would be at risk. Therefore, this would lead to an enriched system associated with supporting and assessment of the staff and teachers (Larson, D. and Chang, 2016, p.344).

Applications In Manufacturing And Production

The application of business intelligence in manufacturing involves analysis such as sales analysis, profit and loss analysis, assets analysis and inventory analysis and so on. Therefore, the manufacturers can have an idea regarding the exact return on investment from every stage of manufacturing. Furthermore, it would allow executing a detailed cost-benefit evaluation which ends up enabling the companies managing the manufacturing costs through different layers of information (Muntean, 2018, p.998).

Be that like it may, the insights gained from big data is responsible for enriching the manufacturer output with improving the products manufactured by them with reducing the manufacturing wastes. It is analysed that with changing time, the contemporary manufacturing sector has been becoming more analysis-driven and thus the manufacturing businesses are capable for solving the issues faster as well as making highly lucid decisions to serve their business purposes (Larson, D. and Chang, 2016, p.344).

Applications In Healthcare

When it comes to discussing the applications of business intelligence in the field of healthcare and medical science, it can be said that though providing the foundation for the evidence-oriented healthcare decision-making process, business intelligence ends up nurturing patient outcomes along with enabling the physicians and the other healthcare practitioners and service workers monitoring better as well as forecasting the diagnosis of the patients. However, business intelligence would enable the providers of healthcare optimizing the pricing, streamlining the claim procedures, controlling costs and improving the operation efficiency (Muntean, 2018, p.998).

On the other hand, big data would just not be applicable for the business sectors which desire to turn as high the profitability as possible. However, Essay writing help opined all the different aspects associated with the healthcare necessities to be as accurate and fast as it could, that involves dealing with a large number of datasets. However, when this data would efficiently be managed, the providers of healthcare would end up discovering the insights which would add value to the entire patient care system (Labonte-LeMoyneet al.2017, p.267).

Applications In The Government Sector

By means of the implementation of the business intelligence technology, nowadays an enormous quantity of information can be analysed with the aim of interpreting the diverse behavior and habituation of the population through the process of statistical modelling. Therefore, this in turn adds value to the understanding of the needs of the general people across the country. However, the potential applications of business analytics, as well as business intelligence, would be manifold, varying from the scope of healthcare systems to taxation and transport. Apart from that, now it is possible to access, analyse and consolidate data easily from the fragmented and disparate sources which would take place in the single agencies along with around different multiple government entities by dint of business intelligence (Pappaset al.2018, p.1092).

Turning to the implication of big data in the government sector, it can be said that it would improve significantly the management of the agencies and utilities as well as dealing with the jobs like the reduction of crime and traffic congestion these days. However, the government got the most important responsibility of maintaining privacy and transparency during handling the confidential people’s information (Williams, 2016, p.109).

A Comparative Analysis Between Business Intelligence And Big Data In Terms Of Their Significance In Business Management

Figure 3. The Implications Of Big Data In Business Management
(Source: Marianiet al.2018, p.244)

When it comes to portraying the implications of business intelligence in business management, it can be said that business intelligence enables the business organizations making impactful business decisions through showing the historical and current data associated with the organizational context of them. In addition to that, analysis is responsible for leveraging business intelligence for providing competitor and performance benchmarks in order to make the companies run smoother as well more effectively. Furthermore, business intelligence procedures help companies organise their data so that they can easily be analysed and accessed. Additionally, enriched business decision-making is one of the considerable advantages of business intelligence. It is evaluated that the decision-makers would be capable of digging in and getting the information they require quickly resulting in empowering them in making the informed business decisions (Mashingaidze and Backhouse, 2017, p.1021). On the other hand, business intelligence involves an approach to make sense of the meaning of the data points along with turning them into valuable business insights which the organisations can apply in the real-world decision-making. Business intelligence systems receive raw data sets and apply the same for informing everything from strategy development to implementation for the probable future setbacks applying the analysis software. In addition to that to solve my assignment business intelligence can intensify the organisational efficiency through accelerating the decision-making procedure for making it easier and faster, enabling businesses deploying their employees more effectively along with helping the companies analyse and improvise their business procedures besides adding value to the information technology efficiency (Power and Heavin, 2017, p.1131).

Figure 3. The Implications Of Big Data In Business Management
(Source: Marianiet al.2018, p.244)

In the management of the business, big data plays an influential role in advancing the business through making effective business decisions, enhancing consumer involvement, improvising business procedures, preventing the unauthorized operations and identifying and acquiring profitability from the emerging revenue sources. However, organizational behavior, market trends and competitiveness and the other parameters which would influence various business actions whilst the consumer decision-making patterns would also be explored for adding value to the overall business efficiency of the company through figuring out when the target market of the business is highly active as well as the factors that would influence the decision-making to a larger extent (Marianiet al.2018, p.244). On the other hand, big data enables the business associations creating emerging growth opportunities as well as totally types of organizations which can analyse and combine the market data. However, these organizations have ample information relating to the services and products, suppliers and buyers and customer preferences and expectations which can be gathered and analysed. Be that as it may, big data got the potential of improving the internal operations and efficiencies by means of the robotic automation process. In addition to that, a large amount of real-world data would immediately be analysed and built into the business procedures for automated decision making (Penget al.2017, p.352).

The Inter-Relationship Between Business Intelligence And Big Data

As discussed previously, big data is considered as an entity and that of business intelligence is a process. However, by dint of technology, business intelligence would involve with data whether big or normal with extracting the valuable information from the same. On one hand, business intelligence helps deliver accurate and essential reports through directly accessing the information from the data source. On the other hand, big data is responsible for capturing, processing and analyzing both the unstructured and structured data for improving the consumer outcomes (Stylos and Zwiegelaar, 2019, p.405). You can also get coursework help  from SourceEssay if you are finding problems in understanding business intelligence and big data tools requirements.


In the end, it is concluded that both big data and business intelligence aim at helping the business make effective organizational decisions by analyzing the wide datasets for business expansion and cost optimisation. However, this data analysis would not only trigger the business decision-making system but also would play an active role in the development of methods and strategies which ensure the success of the business organizations. This data analysis is termed as business intelligence whilst big data is responsible for sorting data on a system of the distributed file which is much flexible and safer. Be that as it may, it is analysed from the discussion thatbig data is responsible for supplying external information relating to the own data sources of a company, serving as one of the expensive resources. This, it is one of the potential elements of business intelligence, is responsible for providing a comprehensive aspect of the business processes.


Baggio, R., 2016, April. Big Data, Business Intelligence and Tourism: a brief analysis of the literature. In IFITT workshop on Big Data & Business Intelligence in the Travel & Tourism Domain (pp. 9-17).

Balachandran, B.M. and Prasad, S., 2017. Challenges and benefits of deploying big data analytics in the cloud for business intelligence. Procedia Computer Science112, pp.1112-1122.

Dedić, N. and Stanier, C., 2016, November. Towards differentiating business intelligence, big data, data analytics and knowledge discovery. In International conference on enterprise resource planning systems (pp. 114-122). Springer, Cham.

Dey, N., Hassanien, A.E., Bhatt, C., Ashour, A. and Satapathy, S.C. eds., 2018. Internet of things and big data analytics toward next-generation intelligence (pp. 3-549). Berlin: Springer.

Frizzo-Barker, J., Chow-White, P.A., Mozafari, M. and Ha, D., 2016. An empirical study of the rise of big data in business scholarship. International Journal of Information Management36(3), pp.403-413.

He, W., Wang, F.K. and Akula, V., 2017. Managing extracted knowledge from big social media data for business decision making. Journal of Knowledge Management.

Jin, D.H. and Kim, H.J., 2018. Integrated understanding of big data, big data analysis, and business intelligence: a case study of logistics. Sustainability10(10), p.3778.

Labonte-LeMoyne, E., Leger, P.M., Robert, J., Babin, G., Charland, P. and Michon, J.F., 2017. Business intelligence serious game participatory development: lessons from ERPsim for big data. Business Process Management Journal.

Larson, D. and Chang, V., 2016. A review and future direction of agile, business intelligence, analytics and data science. International Journal of Information Management36(5), pp.700-710.

Liang, T.P. and Liu, Y.H., 2018. Research landscape of business intelligence and big data analytics: A bibliometrics study. Expert Systems with Applications111, pp.2-10.

Mariani, M., Baggio, R., Fuchs, M. and Höepken, W., 2018. Business intelligence and big data in hospitality and tourism: a systematic literature review. International Journal of Contemporary Hospitality Management.

Mashingaidze, K. and Backhouse, J., 2017. The relationships between definitions of big data, business intelligence and business analytics: a literature review. International Journal of Business Information Systems26(4), pp.488-505.

Muntean, M., 2018. Business intelligence issues for sustainability projects. Sustainability10(2), p.335.

Pappas, I.O., Mikalef, P., Giannakos, M.N., Krogstie, J. and Lekakos, G., 2018. Big data and business analytics ecosystems: paving the way towards digital transformation and sustainable societies.

Peng, M.Y.P., Tuan, S.H. and Liu, F.C., 2017, July. Establishment of business intelligence and big data analysis for higher education. In Proceedings of the International Conference on Business and Information Management (pp. 121-125).

Power, D.J. and Heavin, C., 2017. Decision support, analytics, and business intelligence. Business Expert Press.

Ram, J., Zhang, C. and Koronios, A., 2016. The implications of Big Data analytics on Business Intelligence: A qualitative study in China. Procedia Computer Science87, pp.221-226.

Stylos, N. and Zwiegelaar, J., 2019. Big data as a game-changer: How does it shape business intelligence within a tourism and hospitality industry context?. In Big data and innovation in tourism, travel, and hospitality (pp. 163-181). Springer, Singapore.

Sun, Z., Sun, L. and Strang, K., 2018. Big data analytics services for enhancing business intelligence. Journal of Computer Information Systems58(2), pp.162-169.

Williams, S., 2016. Business intelligence strategy and big data analytics: a general management perspective. Morgan Kaufmann. Protection Status
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