Internet is home to a lot of information that is only growing and increasing with time. The case is the same with the organizations and companies of the modern era. There are multiple and simultaneous projects that keep on running and there are massive sets of information associated with these projects.
Big Data is a trending word and concept for the technological entities in the current times. It is a concept that is related with massive sets of data and consists of varied structures and a lot of data that may differ from one another. Organizations are making sure that they maintain the adequate pace with the elements of innovation and are therefore installing the tools that may implement Big Data as a practice and concept in the organizations (Venturebeat, 2016).
Business Intelligence which is usually known as referred as BI is a large concept that has many techniques defined under it. It is a mechanism to study and analyze the information intelligently so that there can be relevant patterns that may come out from the information under analysis (Google, 2016).
Use Case for Big Data
Organizations of the modern era need to make sure that they reach out to maximum number of people and for this purpose it is required to follow the required marketing strategy and techniques. Also, gone are the days when there was only a single marketing channel or medium that was used and now it has become essential to explore multiple channels in the marketing field. Use of multimedia in marketing and creating strategies and policies to set wings in all of these channels is termed as Multi-Channel Marketing.
Marketing activities are now required to be executed on all the channels and paths such as social media, tele-media, cellular communications, print media etc. With the presence of so many channels and mediums, there is ought to be a lot of exchange and presence of information. Big Data comes in to picture in this case to handle all the marketing related data with ease. There are also various devices that are used to carry out the marketing tasks. Handling of all these entities with the required form of tools along with the related information is made possible through the application of Big Data (Qubole, 2016).
Big Data: Strategy and Steps
The following is the strategy that shall be used and applied in case of the collaboration of Big Data and multi-channel marketing.
Step 1: Collect data and information from the sources of data
Multi-channel marketing is the area in which there are several data sources present which may be internal or external in nature. The information shall be collected from these sources of data and shall be collated to make sure that a defined structure is provided and meaningful patterns are devised out from the data.
Step 2: Business Process Identification
There will be a number of business processes that will be associated with the Multi-channel marketing and some of these processes may be already in existence and some may be new in nature. The business processes shall be identified with the aim to explore the existing instead of creating everything from scratch.
Step 3: Business objectives and customer relationship
It will be necessary to create the objectives and activities in such a manner that the customer is always kept at the top and the relationship with the customer is maintained. The business objectives shall be defined and there shall be a link and alignment formed between the two aspects.
Step 4: Adapting the required methodology for success and determination of factors
Implementation of Big Data in association with multi-channel marketing shall be done using the agile framework in which the decision around implementation shall be taken according to the situation. Also, there will be numerous internal and external factors that will be required to be considered in terms of the success rate.
Step 5: Business Initiatives
The initiatives shall be taken to ensure that the customer relationship along with the organizational policies and requirements related with multi-channel marketing are maintained.
Step 6: Continuous Improvement and Testing Processes
There will be many changes that will be introduced with the implementation of Big Data in multi-channel marketing. These processes shall be executed in such a way that the maintenance activities are included and executed with ease and there is always a continuous improvement that is carried out. It shall also be made sure that the testing practices are carried out so that any of the flaws and deviations can also be detected and the same are rectified.
Strategic Alignment of Business Objectives and Big Data Strategy
Business Intelligence and Big Data are the concepts that work on the information sets and have the main objective as the identification of important patterns from these sets and execution of the strategies for better handling and management of information. Collaboration of both of these principles will lead to many advantages in terms of achieving the objectives quickly. There are many techniques that come under BI which may be applied in relation with Big Data such as Data Mining. It is the technique in which identification of relationship between the data sets is done so that utility of the information attributes may be understood.
Information that is collected from the various data sources cannot be used and applied as it is. It is required to make certain modifications in the same along with various adjustments in association with the same. The technique as OLAP is the one that carries out and executes the strategic monitoring of the data and information that is stored in the data sets (Olap, 2016)
Big Data and Business Intelligence are the tools and techniques that work on the information sets and have the main objective as the identification of important patterns from these sets and execution of the strategies for better handling and management of information. Collaboration of both of these principles will lead to many advantages in terms of achieving the objectives quickly. There are many techniques that come under BI which may be applied in relation with Big Data such as Real time BI. Marketing is a practice that works on real time information and this concept under BI will make sure that the data experts have the real-time view of information with all the relevant patterns highlighted.
As discussed earlier, multi-channel marketing is composed of several entities and components. It is necessary to ensure that the relationship between these entities can be understood well and there are no loopholes present in this regard. The same can be ensured with the help of data warehouses. These warehouses can be in the physical and logical form and can be of great utility to the business organizations.
The main objective of Business Intelligence along with Big Data is the identification of important patterns from these sets and execution of the strategies for better handling and management of information. Collaboration of both of these principles will lead to many advantages in terms of achieving the objectives quickly. There are many techniques that come under BI which may be applied in relation with Big Data such as Business Process Management. It is the technique in which there are patterns and overall performance of the business activities is studied with the application of intelligence tools (Villanova University, 2016).
Analysis is an important activity that is required to be carried out on the information sets associated with a business process or an activity. Analysis of the data refers to the practice in which the information sets are read and analyzed through the application of BI tools so that the relevant patterns can be achieved and highlighted through the same (SearchDataManagement, 2016)
There are several activities that are simultaneously carried out in the business organizations such as the ones in the field of multi-channel marketing. These activities are required to be tracked and monitored so that the status and the progress are known to the management and the associated entities. BI tools are present to carry out the reporting tasks and activities.
Multi-channel marketing is the area in which there are several data sources present which may be internal or external in nature. The information shall be collected from these sources of data and shall be collated to make sure that a defined structure is provided and meaningful patterns are devised out from the data.
Advantages
The following advantages will also be achieved.
Big Data is a concept which is required to be implemented through many automated tools that have the Big Data techniques implemented in them and can be customized as per the requirements of the organization. Hadoop is one of the popular tools which are used to implement Big Data. There is abundant storage that is offered through this tool and it comes at costs that are not very high. Many of the BI concepts and techniques are also included in Hadoop and the necessity to install additional tools for the same purpose is also avoided. These are also easy to operate and understand and therefore do not require the need to provide additional trainings to the users.
Organizations are looking for new methods and practices to bring in innovation in their processes and activities. These processes lead to gaining competitive edge among the competitors which is further made possible through Big Data. It allows the gathering of data from a lot many sources which is then analyzed and studied to look for patterns and behavior involved with the data (Qubole, 2016). In such a manner the organizations achieve a lot of data that is relevant and explore the unexplored areas.
There are also newer business opportunities that are created with the implementation of Big Data. It has been observed that the organizations succeed only when they have the element of innovation present in their processes. Big Data allows the exploration of the areas that are not visited previously and it leads to the highlighting of some of the newer practices and opportunities to adapt to. There are profits and revenues that are earned in these areas which lead to the overall benefit for the organizations.
Hadoop is written in JAVA as the programming language that offers it the inherent advantages associated with this language in terms of inter-operatibility, robustness and scalability. Big Data is a concept which is required to be implemented through many automated tools that have the Big Data techniques implemented in them and can be customized as per the requirements of the organization. Hadoop is one of the popular tools which are used to implement Big Data. There is abundant storage that is offered through this tool and it comes at costs that are not very high. Many of the BI concepts and techniques are also included in Hadoop and the necessity to install additional tools for the same purpose is also avoided. These are also easy to operate and understand and therefore do not require the need to provide additional trainings to the users (ITProPortal, 2013).
There are many security attacks and risks that the data and information on the network channels and organizations are exposed to. However, in case of Big Data the storage architecture that is used is in the form of Hyperscale Storage Architecture. It makes sure that the data is always protected and there is no single point of failure involved with Big Data. In this architecture, the data is stored in numerous locations so that its safet and protection is always ensured and maintained (Computerweekly, 2016).
NoSQL stands for the category of the databases that do not require or involve SQL in their architecture and functionality. There are certain limitations that are associated with the SQL based databases which is not associated with NoSQL. Also, there are certain unique features that are offered in this database which is not present in any of the SQL database engines such as enhanced visual appeal, extraction of customized reports, flexibility and scalability of the database etc. There can also be application of BI tools and concepts that may be applied to the data which goes missing from the rest of the databases (Pentaho, 2016). Due to the presence of so many unique features and concepts, the growth of NoSQL databases has been massive (Goes, 2016).
Data Analytics along with MDM: Support to DS and BI
Enterprises and organizations have a lot of data and information associated with them which has led to the coining of a term called Master Data Management (MDM). It is a concept that is further classified in two categories.
Collaboration of MDM and data analytics is required to have following benefits:
List of NoSQL Databases
The database is open source and therefore there is no cost associated with it. The base of this database engine is Agile Framework and because of this the database is extremely flexible in nature.
There are organizations and entities present in the market that are now demanding RESTful web services and interfaces which are offered and supported by this one.
Indexes play an important role in association with the databases which can be queried through this one.
The availability that comes with this database is non-stop which makes it easy for the users to use and access it at any time.
The storage capacity that comes with this database is sufficient enough to support the data that is associated with the enterprises.
Consistency of information is extremely necessary for the databases which is made possible and made easy with this NoSQL database (Bigdata-madesimple, 2014).
Social Media: Role in Decision Making
Social media has evolved and has widely spread at a large scale. There are organizations that are using social media in their business activities and marketing is one activity that is being done actively through the use of social media. It allows the organizations to easily reach out to the customers and gain their perspective and expectations.
Social media networks and accounts can be used to study the user patterns, their choices that are made by them, purchases cycles, likes and dislikes etc. All of these factors lead to the process of identifying the demands of the users from each of the target area and the decisions can be accordingly made to achieve better revenues.
Big Data: Value Creation Process
Value that is generated through Big Data can be analyzed from two aspects that are the one associated with customers and the one associated with the organization itself. Also, the data sources that are related with Big Data have varied types and structure.
The value creation process can therefore be understood from the levels such as market, brand and customer (Hull, 2016).
There are two models used to further understand the value creation process.The activities that are associated with the organization can also be understood through the model that has been explained and illustrated below.
Conclusion
Innovation is a key element for success of the organizations in the current times. Big Data is a trending word and concept for the technological entities in the current times. It is a concept that is related with massive sets of data and consists of varied structures and a lot of data that may differ from one another. Organizations are making sure that they maintain the adequate pace with the elements of innovation and are therefore installing the tools that may implement Big Data as a practice and concept in the organizations.
Also, use and application of Business Intelligence (BI) along with Big Data is equally important. There are also newer business opportunities that are created with the implementation of Big Data. It has been observed that the organizations succeed only when they have the element of innovation present in their processes. Big Data allows the exploration of the areas that are not visited previously and it leads to the highlighting of some of the newer practices and opportunities to adapt to. There are profits and revenues that are earned in these areas which lead to the overall benefit for the organizations. BI techniques such as data mining, real-time BI, data sources etc. shall be used and applied in the organizations for achieving the business objectives.
References
Ap-institute. (2016). How is Big Data Used in Practice? 10 Use Cases Everyone Must Read. [online] Available at: https://www.ap-institute.com/big-data-articles/how-is-big-data-used-in-practice-10-use-cases-everyone-should-read.aspx [Accessed 24 May 2017].
Bigdata-madesimple. (2014). A deep dive into NoSQL: A complete list of NoSQL databases. [online] Available at: https://bigdata-madesimple.com/a-deep-dive-into-nosql-a-complete-list-of-nosql-databases/ [Accessed 24 May 2017].
Computerweekly. (2016). [online] Available at: https://://www.computerweekly.com/feature/Big-data-storage-choices [Accessed 24 May 2017].
Goes, J. (2016). How to choose a NoSQL analytics system. [online] InfoWorld. Available at: https://www.infoworld.com/article/2983953/nosql/how-to-choose-a-nosql-analytics-system.html [Accessed 24 May 2017].
Google. (2016). Business Intelligence | Information Builders. [online] Informationbuilders.com. Available at: https://www.informationbuilders.com/business-intelligence [Accessed 24 May 2017].
Hull, (2016). [online] Available at: https://www2.hull.ac.uk/hubs/pdf/NEMODE%20big%20data%20scientist%20report%20final.pdf [Accessed 24 May 2017].
InformationWeek. (2016). MDM for Operations and Analytics – InformationWeek. [online] Available at: https://www.informationweek.com/software/information-management/mdm-for-operations-and-analytics/d/d-id/1042903? [Accessed 24 May 2017].
ITProPortal. (2013). Big data: 5 major advantages of Hadoop | ITProPortal.com. [online] Available at: https://www.itproportal.com/2013/12/20/big-data-5-major-advantages-of-hadoop/ [Accessed 24 May 2017].
Olap. (2016). What is Business Performance Management? BPM Definition. [online] Available at: https://olap.com/learn-bi-olap/olap-bi-definitions/business-performance-management/ [Accessed 24 May 2017].
Pentaho. (2016). Pentaho and NoSQL Databases. [online] Available at: https://www.pentaho.com/big-data-analytics/nosql-databases [Accessed 24 May 2017].
Qubole. (2016). Big Data Use Cases | Qubole. [online] Available at: https://www.qubole.com/resources/solution/best-use-cases-for-big-data-analytics/?nabe=5695374637924352:0&utm_referrer=https%3A%2F%2Fwww.google.co.in%2F [Accessed 24 May 2017].
SearchDataManagement. (2016). What is data analytics (DA)? – Definition from WhatIs.com. [online] Available at: https://searchdatamanagement.techtarget.com/definition/data-analytics [Accessed 24 May 2017].
Venturebeat. (2016). Big Data implementation mistakes to avoid. [online] Available at: https://venturebeat.com/2014/11/25/5-big-data-implementation-mistakes-to-avoid/ [Accessed 24 May 2017].
Villanova University. (2016). Business Intelligence (BI) Overview of Major Components. [online] Available at: https://www.villanovau.com/resources/bi/overview-of-business-intelligence-bi-components/#.VzordTB97IU [Accessed 24 May 2017].
Essay Writing Service Features
Our Experience
No matter how complex your assignment is, we can find the right professional for your specific task. Contact Essay is an essay writing company that hires only the smartest minds to help you with your projects. Our expertise allows us to provide students with high-quality academic writing, editing & proofreading services.
Free Features
Free revision policy
$10Free bibliography & reference
$8Free title page
$8Free formatting
$8How Our Essay Writing Service Works
First, you will need to complete an order form. It's not difficult but, in case there is anything you find not to be clear, you may always call us so that we can guide you through it. On the order form, you will need to include some basic information concerning your order: subject, topic, number of pages, etc. We also encourage our clients to upload any relevant information or sources that will help.
Complete the order form
Once we have all the information and instructions that we need, we select the most suitable writer for your assignment. While everything seems to be clear, the writer, who has complete knowledge of the subject, may need clarification from you. It is at that point that you would receive a call or email from us.
Writer’s assignment
As soon as the writer has finished, it will be delivered both to the website and to your email address so that you will not miss it. If your deadline is close at hand, we will place a call to you to make sure that you receive the paper on time.
Completing the order and download