Big data is one of the concept that has currently been leading in the world. This idea of this concept being chosen is because of the big data usage in business institutions that have been discussed significantly in the manners with what they portray and what it is associated with them. With this era of information massive volume of data nowadays have really been available to many makers of the decision. Big data can be defined to data sets that may not be big but also they have a high variety and velocity making them difficult in handling them when we use traditional tools and the techniques. This growth of data being rapid have led to more studies to be done to help provide knowledge in using this big data and hence the value extracted helping in informed decisions in this big business organizations.
Additionally, makers of the decision are also to gain a lot of valuable insights varying from our daily transactions to the customer we interacts with and the social network data. The values provided may help in the usage of big data analysis which is one of the application that is advanced analytics techniques on the big data (Zeng, 2010). The paper aim is analyzing the different analytics methods and how this tools are applied to big data in business organizations and much more the opportunities that arose when the big data is used in specific decisions domains
The objective of data mining in any company is discovering the inside unstructured data, extracting the meaning of data that is so noisy and much more discover patterns randomly, using the gathered data in knowing the trend to follow, correlations, probability and future possibility/predictions and the trends in competition that the company can use its own data in making the data to be more meaningful in bettering the position of the company on the current technology waving in and out each and every day (Marasoiu, 2016).
Big data influence in business organizations especially in the IT industry have grown very rapidly. So many questions has been raised that it’s very hard in managing and using big data in business organizations. Microsoft quoted that big data has potentially changed the government ways , business organizations ways have been conducting business and making discoveries and this has been seen like not to likely to change (Tek, 2013).
The mentioning or talking of big data has been seen as a new jargon that is very hard to understand but for easy understanding it is termed as the volume that is exponential with structured and unstructured data that consist vast amount of datasets of which is very hard in processing by the older traditional DBMS methods and their related software techniques. When we consider the volume of big data and the capacity of data encompassed in by carrying itself within the potential that it will help many business organizations. Big data review lie in many concepts and can be interpreted differently depending on the topic and the definition that corresponds.
Big data has been characterized by three V’s namely the volume, the variety and the velocity. The volume covers the size of the data and how enormous the data is. The velocity as a characteristic is the rate to within which data changes and often created. Lastly but not least is the variety which consists of the formatting and data types and the usage and how that data is analyzed. It’s good to note that big data primary attribute is data volume. The volume can be quantified by size in terms of terabytes which maybe inform of records, daily transactions, tables and files.in additional big data description may be based through its velocity or its speed which made on the basis on the frequency data is generated or delivered to the users. In business organization uses of big data the edge of it has been categorized much in streaming of that data and this collected and gathered in real-time from the websites. This has been termed as an additional characteristics named as veracity which focuses on the data quality. Veracity has been known for its characteristics in the quality of big data to be either bad, good or even undefined which may be caused due to the deception, a lot of approximations, inconsistency of data, latency, the ambiguity and lastly is the incompleteness.
Big data is terms to be as the data volume that is beyond the capability that a technology can be able to store, manage or even able to process in an efficient manner (manyika, 2015). Another review of big data is that it is termed as the high tech, speed, volume and complex that multivariate the available data in capturing storing, distributing, managing and enhancing the decision made and much more discovery of insights and optimization of processes (TechAmerica, 2012). Big data tech is new in the gen of the tech and the architecture which were designed for extracting value for multivariating high volumes of datasets where it provide high speed that helps to capture, discover and to analyze (Reinsel, 2018). Lastly is that big data is termed as a way of combining definitions that varies such as the cluster methods and the tech through which the forms which are new and how they are unified to re-counting the concealed values in diverse, showing some complexity and the high volumes of data sets (Hasheem, 2015).
Talking about data that is structured we try to mean that if the data is placed in the current data warehouse in RDBMS the structure of RDBMS being enforced on the specific current data warehouse system then there will be an understanding and the meaning that is associated with it. Here we can know the columns and rows associated within each table and the spaces in table. Format of such data can be in different forms that is numerical or text but the best thing to note is knowing the unique identifier that uniquely identifies the person in this era. The entire data will be organized in terms of the entities that is through the semantic chunks.
Semi structured
The movement from structured to semi-structured brings some little demarcation and often in differentiation lines that they may go blurry. Data is available in many formats when dealing with the semi-structured data such as the Db systems, file systems e.g. the web data and the data exchange formats. Another thing we need to know is that you don’t need to have the completely structured that is partially and most if it all it includes the similar entities being grouped and organized semantically , entities that don’t have same attributes in groups, the order the attributes that are not important and the attribute that may not be required.
This type of data is very difficult in indexing. If this is referred then we try to bring the purpose of queries, reference of relational tables and analysis. This has helped in including the file types and associated with videos, audios and the image files including such as.
The importance can be defined to how efficient the notion has always been for many organizations to improve in their most used KPI’s, however this is with the data an organization has where they have the insights they use in helping to generate. Data is really taken in multiplying different multiple sources and the integration across the environments in which analysis help us in answering the following scenarios.
The business decisions to be made in a business are to used and considered in the following basis of data and the analytics that are associated and the simple terms hence being defined as Big Data,. The combination with motorized analytics and the lot of businesses that is related to the tasks to be accomplished and this may include (Ms. Vibhavari Chavan, 2014).
There are techniques that drive the use of big data and that could be used when one is starting a project. This tools are summarized and explained briefly as follows
Association rule learning which used for discovering the interest in relationships. Some of the association rules are among the variables that are in large in Dbs. The other technique is data mining which is one of the terms that is related with the data-driven in making of the decisions and much more it’s described as a tool for searching or digging in to (Laney, 2011).
Cluster analysis is another technique which is a data mining type that subdivides the large group in to groups that are small but similar and the characteristics of how similar they are is known in advance. Crowd sourcing is used for gathering data technique from a group that is large through calls that are open and it is usually web2.0 tool. Crowd sourcing is used for collecting data rather than analyzing the collected data.
The same case with techniques in analytical there are many software packages and the available technologies in facilitating the big data analytics (Cebr, 2012). The following list is of the used technologies in big data.
Usage areas of big data in most business organizations. Big data usage has be welcomed and effectively applied in many meadows and disciplines as follows.
Each and every tool in tech world comes with benefits. The organizations have to lay down strategy in the management and dealing of the big data and this is knowing where, and the lace of storage once the acquisition of that specific data is done (Bakshi, 2012). Some of the old methods of storage of data and the way they data that is structured are retrieved includes RDBMs, data marts and the data warehouses in general. The way big data works is just uploading to the store area from the already stored operational data where we use the Extract-Transform-Load (ETL) or also Extract-Load-Transform (ELT) tools which is are used in extracting the outsiders data, transforming that outsider data in fitting the operational needs and finally loading that data in to the db or to the data warehouse (Cuzzocrea, 2009).
The benefits of such application of big data can be discussed in many ways but here are some of the benefits and the way a business organization can feel and be helpful in all ways. The following are some of the ways a company can get implement and put in to place the usage of big data in the business operations in daily to daily lives.
One of the use of big data in business organization is that the company get to know the customer and much more knowing all of them in real time. Traditionally we used to use questionnaires and the focus groups in knowing where the customers are .this was always termed to be outdated and the time the results were analysed then it would have been like obsolete as so many changes may have happened in between. The introduction has made it possible in real time and hence the use such traditional methods is not necessarily helpful in all ways. The big data has gone to the extent of allowing the business organizations of mapping the DNA of their clients in all fields. This understanding and having the knowledge of the customer has helped the business organizations in selling will and much more effectively.
This understanding of knowing one customer has given so many recommendations and showing so many advertising that are custom-made to ones needs. Amazon is a business organization that has mastered in the perfection of giving recommendations to its customers and hence to them this is not a coincidence. Some of the engineered functions are such as the virtual shopping cart that have been highly rated and viewed by many clients to be very effective and efficient.
Secondly is that big data has led to co-creation, improving and much more innovating one’s products in real-time (Manyika, 2011). Traditionally customers had panels for discussion to what they want and showing them the finished products and finding what they think of it. Emergence of big data has helped many organisations in getting a better understanding what customer will think of the product. When we listen such on social-media on what people says or talk about a given item we happen to understand the concept and more information is given to than it would have been if questionnaire were to be applied. The allowing of these big data in companies has led to running real time simulations where thousands of test or testing a new or any improved product in a digital manner.
Thirdly is that big data helped the business organization in determining the risk an organization faces. In determining the risk the risk of a customer who is potential or any supplier there must be placement in a certain category where each have to be determined according to its category. Big data has helped in determining the risk class for each potential client on the basis of data they may have collected from the past and what they have currently in the real time. Considering the insurance company the prognostic analyses are always used in determining the amount of money in future the client will be costed. Usage of big data techniques such as the pattern-recognition, analysis-in-regression, textual-analysis, aggregation-of-social-data and lastly is the sentiment-analysis with view of the potential customer created.
Fourth is that the big data has been used to personalize the website and the prices in real time. Company have used split-tests and the A/B tests for many years in determining the best layout to be used by their customers. Big data have effected on the prices ordered. The use of algorithm have become possible in reaction to events in the market or actions of the rivals in real-time as adjusting prices accordingly.
The other use of big data in business organizations is that it has helped improving the service support for customers. This has been made possible in monitoring machines from great distance and checking how they are performing. Nowadays it is easy to send data to the manufacturer and they will be stored for real-time analysis immediately.
The other major use of big data in business organizations is finding the new markets and opportunities in new businesses. Many governments have stimulated companies in making use of the massive amounts of open data that is collected by the government in one way or another (Sreedhar C, 2014). When we do pattern regression analysis we own our data and this might finds the need and much more the wishes of the customers one never knew about (Newgen, 2017).
Use of big data has led to many organizations understanding one competitors and to always stay and be ahead of them. Use of big data analytics can help in finding out the examples if ones competitor changes their prices and this can help in on changing the prices automatically in order to stay competitive in the market (EMC, 2012). One can also monitor the other actions of the competition such as new tastes and preferences and how this has responded to the competitive market (Datafloq, 2018).
Lastly is the use of big data in helping business organizations in organizing one’s company in a way that is effective and the business organization can save money and time. This logistics in an industry can be efficient when they use them in ways that they may use the big data in sources that are available in the supply chain. The discussed usecases are just a small part of the vast possibility of big data, however it may show that there opportunities which are endless and taking the advantage of it. This has made to think of figurimg how an institution can benefit for big data and hence able to know if one has big data and whether one might be willing to share with others on the big data platform. In everything that discussed and invented to be used globally it always have some challenges. Big data has been noted to have some diverse set of challenges and many obstacles that lies from the management to use of it (White, 2012). Some of this challenges have been contributed by this large amount of data and they may be termed like the collecting and retrieving the big data and the overall visualization of data that is very complex when being accessed and used (Stough, 2014).
Conclusion
This study about the use of big data in business organizations there before was seen as a new jargon but after understanding the study the whole concept from the techniques and technologies and the importance and benefits of using the big data the concept has sink in and very easy to understand and even implementing it. The understanding of such has made me to know how to define the models and categorize the elements that are associated with the big data. Lastly the big data analytics techniques have made this topic on big data to be easy and much more appealing and interesting who now have the whole concepts of what big data can do or can help the business organizations (Elgendy, 2013).
References
Bakshi, 2012. Architecture and Approaches. In: Proceedings of the IEEE Aerospace Conference, s.l.: s.n.
Cebr, 2012. Data equity, Unlocking the value of big data, s.l.: SAS Reports.
Cuzzocrea, 2009. New Analy-sis Practices for Big Data. Proceedings of the ACM VLDB Endowmen. MAD skilss, 2(2), p. 1481–1492.
Datafloq, 2018. Different Big Data Use Cases For Your Organisation, s.l.: s.n.
Elgendy, N., 2013. MSc Thesis German University in Cairo. Big Data Analytics in Support of the Decision Making Process, 5(2), p. 164.
EMC, 2012. Data Science and Big Data Analytics., s.l.: In: EMC Education Services,.
Hasheem, 2015. Information Systems. The rise of “big data” on cloud computing: Review and open research issues, Volume 47, pp. 98-115.
Laney, D., 2011. META Group Research Note. 3D Data Management: Controlling Data Volume, Velocity and variety, Volume 6, pp. 70-75.
manyika, 2015. A Data-Placement Strategy Based on Genetic Algorithm in Cloud Computing. International Journal of Intelligence Science, Volume 5.
Manyika, J. C. M. B. B. B. J. D. R. R. C. B. A., 2011. The Big data Next Frontier for Innovation, Competition, and Productivity. , Newyork: McKinsey Global Institute Reports.
Marasoiu, N., 2016. What is the main objective of data mining with big data?, LA: MongoDb.
Ms. Vibhavari Chavan, P. R. N. P., 2014. International Journal of Computer Science and Information technologies. JSPM’s Imperial College of Engineering and research, 5(6), pp. 7932-7939.
Newgen, 2017. Benefits: Competitive Advantages of Big Data in Business, Newyork: s.n.
Reinsel, G., 2018. Investigating the business intelligence in the era of big. big data in the banking sector from a transactional cost theory, Volume 3, pp. 45-56.
Sreedhar C, D. D. K. K. A. R., 2014. International Journal of Advanced Research in Computer Engineering & Technology. Big Data and Hodoop”,, 3(5), pp. 47-90.
Stough, R. &. M. D., 2014. Review of Policy Research,. Big Data and U.S. Public Policy, 31(4), pp. 339-342.
TechAmerica, 2012. Demystifying Big Data. TechAmerica Foundation paper, Volume 2, pp. 14-17.
Tek, 2013. The true scope of big data, LA: TekSystems.
White, M., 2012. Business Information review. Digital Workplaces Vision and Reality, 29(4), pp. 205-214..
Zeng, D. H. C. L. R. L. S., 2010. IEEE Intelligent Systems. Social Media Analytics and Intelligence. , 25(6), pp. 13-16.
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