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Data Is the Next Frontier, Analytics the New - Essay Example

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This paper "Data Is the Next Frontier, Analytics the New" focuses on the fact that the author of the LUMS Report, David Wong is a researcher at the Big Innovation Centre (BIC). BIC is an initiative of ‘The Work Foundation’ and Lancaster University that was launched in 2011. …
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Data Is the Next Frontier, Analytics the New
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Data Is the Next Frontier, Analytics the New The author of the LUMS Report, David Wong is a researcher at Big Innovation Centre (BIC). BIC is an initiative of ‘The Work Foundation’ and Lancaster University that was launched in 2011. It is a creation of several companies’ universities and trusts and it is for researching and proposing reforms to make UK a global innovation hub (Wong, 2011). Wong is the leader of the organizations and Business Models research streams. His other roles include organizational culture, cross-cultural management and relational analytics. David has served as a researcher at Relationship Foundation and developed Europe’s first ever-family pressure index and behavior based model to assist policy makers develop family proof policy. He wrote this article to inform the reader on the emerging trends on big data. The article begins by providing the backgrounds on the use of big data from big companies that relied on analysis using technically trained staticians. The author provides an objective overview of big data and the concepts related to it such as analytics and the five trends. The article shows how the old trend is slowly being overtaken by the new trends that uses big data and advanced analytics to gain competitive advantage and encourage innovation. The article identifies five trends that have arisen from the revolution of big data that has moved from the structured to unstructured (Wise, 2012; Pg. 06). Increase in applications and services resulting form open data, development of open source platforms by organizations as a way of amassing important data through innovations; proliferation of unconventional data; and convergence of information architecture. The article begins by providing insights into the increase for data in the past few years. According to Wong, the world’s data storage capacity is expected to reach 100 zettabytes by 2020 from seven exabytes from 2003. The Annual Consumer Internet Traffic Flow will reach 1.16 zettabyes by 2016. Companies must find new ways of harnessing the potential power of data in order to gain a competitive advantage and increase innovation (Smolan and Erwitt, 2012). The article introduces analytics that it defines as the practices of utilizing data to create useful insights to enable organizations make better fact-based decisions with the aim driving strategy and improving performance. According to the article, analytics is applicable in every aspect of an organization and can be used to analyze consumer trends, price adjustment in the market, improve performance and change management processes and redeploying resources to gain competitive advantage (Bulusu, 2012: Pg. 17). The current era of big data requires well designed analytic structure so as to reduce information latency, and automate low-risk analytical and decision-making process. This would equip leaders with comprehensive insights gained from up-to- date information to make decisions on complex risk scenarios. Evaluation Criteria based on the five trends The first trend mentioned is the exponential increase in applications and services originating from open data. It credits the European Commission with the launching of Open data strategy for Europe and list the benefits already experienced as a result. These benefits include, increase in the applications and the redefinition of the structure of these applications. Expected benefits include; advanced visualization capabilities for both mobile and enterprise analytics through Web 3.0 resulting to ‘smart data’. Public sector data (open data) is worth £16 billion and is expected to boost the economy by £40 billion (Big Innovation Centre, n.d; Pg. 01). It has also provided innovation opportunities for content developers and information services providers that will provide localized information to consumers. Gradual opening up of data in the private sector is the second trend. The private sector is known for its reluctance to open up data to the public due to privacy and accountability concerns and intellectual property protection and data quality. However, the increase in open source by the government is slowly encouraging them to open up. Encouraging open data will enhance better service to customers, increase market share and competitive advantage. Some private organizations are already sharing data to enhance innovation especially in the medical and insurance sector. Open source and platforms are the new trend that is slowly being adopted. It was shunned originally due to the complexities of putting it into practice. However, the emergence of new collaborative networks has enabled collaborative innovation from a myriad of sources. Open source platforms enable partnership at a large scale, through wider community via social media platforms. This is called crowdsourcing and is beneficial to both the business community and the public sector. According to Wong, the world has moved from numerical data and through advanced analytics the increase in unconventional data (unstructured data). Unstructured data come in form of text, captured conversations and videos. This data provides predictive insights through Complex Event Processing (CEP). The fifth trend in the article is the convergence of information architecture. Real analytics is enables companies to amalgamate disparate data and screen enormous amounts of information to make sense of data. Nevertheless, business must align analytics capabilities with business needs. Businesses must increase analytics infrastructure to capture the entire aspects of the. Review and critical evaluation The article is well organized with proper introduction followed by comprehensive explanation of the important points in the body. The executive summary gives a brief overview of the entire article (Wong, 2012; pg. 02). The author is clear and consistent. He has included two charts the first one shows global internet protocol traffic, the second chart shows the global mobile data traffic, 2011-2016. He has also included two illustrations; Box 1 is open data and innovative apps in New York City and box 2 is titled ‘insights from customers matter’. The article is useful for businesses, governments and private sector. It is relevant to the techno-savvy youths who are the innovators of apps and the leading consumers of social media. Application to organization IBM is a dedicated software provider and service – led company providing a vast set of capabilities around assisting companies develop data driven decisions. It is one of the companies that has utilized the big data trends and reaped the benefits. IBM has transformed itself into a big data and analytics powerhouse in the past few years. The investment of $24 billion in big data has led to a growth target of $20 billion by 2015. The company hit its target of $16 billion. As a leader in big data and analytics, IBM now assists governments and businesses throughout the world to make sense of data and gather important insights from structured and unstructured data emerging from all sources such as blogs, social media and videos. They provide these services in every industry such as healthcare ad automotive as well as telecommunications among others. IBM’s success is due to the fact that big data is the technological phenomenon. Eighty percent of the 2.5 exabytes of data produced per day around the world is unstructured and untapped. IBM assists companies and organizations around the world make sense of this data and improve their performance in the current economy. IBM expects to grow as its business expands across the globe. Advantages and Disadvantages The benefits of big data and analytics to companies include; Attract, retain and grow clients. Transform management practices from implementation of analytics. Optimize fraud and threat through focus on security. Big data analytics detect flaws in the system and block potential breaches. Improve operational data in real time ensuring efficiency in information gathering and decision making. The downside to analytics is the increase in surveillance and breach of privacy of the customers. As companies try to understand their consumers, they are gathering personal details that breaches the clients privacy and often results in law suits or harm to the customers when such information get to the wrong hands. List of References WONG, D. (2012). Data is the next Frontier, Analytics the new. Retrieved April 29, 2014, from Tool BULUSU, L. (2012). Open Source Data Warehousing and Business Intelligence. NY: CRC Press. VIKTOR MAYER-SCHÖNBERGER, K. (2013). Cukier Big Data: A Revolution That Will Transform How We Live, Work, and Think. Houghton Mifflin Harcourt. POLICY EXCHANGE (n.d.). The Big Data Opportunity: Making government faster, smarter and more personal. NY: CRC Press WISE, L. (2012). Using Open Source Platforms for Business Intelligence: Avoid Pitfalls and Maximize ROI. Newnes. SMOLAN, R. & ERWITT, J. (2012). The Human Face of Big Data. Against All Odds Productions. NY: University Press BIG INNOVATION CENTRE. (n.d). Retrieved on 29th April, 2014 from http://www.biginnovationcentre.com/Aboutus/Our-People/85/David-Wong. Read More
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