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Over the past decade, the growth of several social media platforms has revolutionised methods that individuals and industries use to interact and carry out business. Individuals generate data unprecedented by sharing, interacting, and using content via social media. Processing such data to extract actionable patterns leads to several opportunities and challenges for developing tools, novel algorithms and interdisciplinary research.
The Customer Analytics and Social Media course integrates customer profiling and behaviour, social media and network analysis, and data mining or analytics. The system provides a coherent and convenient platform for students to easily grasp the basic concepts and potentials of the field. The students are also introduced to software tools for visualising and analysing real-world social networking data.
Students are allotted heaps of assessments that require a sound understanding of social media analytics, various models, methodologies, behaviour analytics, community detection, and several software. Students generally don’t possess complete knowledge and get stuck so they look for BUS5CA Customer Analytics and Social Media academic assistance.
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The aforementioned universities in Australia are renowned for their quality of teaching and research, and theyoffer different inter-related degree courses.
The Customer Analytics and Social Media program cover various areas of social media and customer profiling and analysis by allowing you to understand your domain in-depth and its interconnection with other disciplines. The following units are most commonly included in the course:
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This BUS5CA Customer Analytics and Social Media course is vast and involves discussions, action planning, and activities along with theoretical concepts and analytics tools and techniques. After completing the course, students will acquire real-world knowledge, problem-solving skills, critical thinking skills, and improvised communication skills. Thus, the learning outcomes, of course, are listed below:
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The customer analytics and social media graduates can pursue various roles in industries, including:
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Discussion forums including TIBCO Analytics Forum, Reddit, Analytics Vidhya, DataQuest, Data Science Central, etc., are well-moderated social media analytics community forums. Such forums serve as premier online platforms to get in contact with business leaders and analysts, customers, innovators, and managers throughout the world. The community is highly qualified and they are very active and usually shares their experiences, latest news, information, and also discuss the latest data analytics tools and methodologies.On such platforms, you have the greatest opportunity to ask your queries from such great people. You may also get access to numerous tools, events and services for understanding, development, and practice.
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Since a huge portion of the population uses social media daily, social media data is analysed in several distinct disciplines. The process of social media analytics involves four steps: discover, collect, prepare, and research (Sebei et al., 2018).
In each step, plenty of challenges are encountered, including volume of data, data variety, data format, and unstructured data (Stieglitz et al., 2018 ). Since conventional tools fail with such data, new computational approaches, programming languages, software architecture, and algorithms tend to solve this issue (Goyal & Goyal, 2020).
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Our highly qualified and experienced experts are managers and leaders of reputed organisations, and they have a firm grip on the subject. They encourage students to follow the below-mentioned approach to draft a perfect assessment solution:
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Obtain the best BUS5CA Customer Analytics and Social Media academic assistance or guidance with coursework from Sample Assignment. Our highly qualified and experienced subject matter experts will help you earn the topmost grades in this course by systematically assisting you with your task. A few perks of our services are listed below:
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Goyal, S. J., & Goyal, R. (2020). Social Media Analytics–Challenges during the Data Analysis.Artificial & Computational Intelligence,1(2).
Sebei, H., Taieb, M. A. H., & Aouicha, M. B. (2018). Review of social media analytics process and big data pipeline.Social Network Analysis and Mining,8(1), 1-28.
Stieglitz, S., Mirbabaie, M., Ross, B., & Neuberger, C. (2018). Social media analytics–Challenges in topic discovery, data collection, and preparation.International journal of information management,39, 156-168.
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