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Big Data Success is a Mixed Bag Featured

Big Data Success is a Mixed Bag Aylin Çobanoğlu
It is now over a decade since the leading global multinationals began embracing Big Data and Artificial Intelligence. A few years later, we began hearing about data scientists and other new careers and the divergence from the usual buzzwords to new, industry-shaping technology. After 2014, the topic of big data became a hype. Some saw it as a “passing cloud” that would leave many in disarray because of the exaggeration witnessed in what the cloud could do. About seven years later, big data is thriving, and businesses that have adopted it are making critical decisions accurately, thanks to the right tools and information at their disposal. Although it has had an immense economic and social impact, big data success is a mixed bag of success and failure.
Successes of big data Big data has, without doubt, changed the corporate landscape for the better. It is a crucial driving force of many businesses and their efforts to reach customers and understand them. As predicted by The Economist in 2017 that the “data economy” will be the major shift of many organizations and a main driving force for the success of any business, the investments that many companies are making on this new paradigm is evidence enough that data processing is a critical component in understanding and targeting customers. With the help of big data, organizations can have better customer information such as their preferences, devices they use, average time customers spend on a particular website, and their browsing habits, all of which are critical for proper targeting. There is also the aspect of optimization of business processes. Big data analysis is giving businesses an edge over their competitors in streamlining business processes. When businesses take time to understand their operations and find ways to tweak them to suit the customer needs, improvement in terms of cost management and customer satisfaction is attained. Companies are investing in good data analytics tools to help them optimize predictions, enhance product management through the promotion of the right product and increase sales. In short, using big data analytics to draw insights from data boosts business growth. Ecommerce companies have made analytics central in their retail operations for organizations. Failures of big data Despite massive growth and successes that have been witnessed in the big data industry, there are various lows, mainly in big data project implementations. Although coming across the correct number of failures is hard, the failure rate is something between 60% and 80%. This is undoubtedly a high failure rate considering the amount of money invested in big data projects. The reason for failure often lies with the project implementation team and too much expectation on the big data initiative. While many people claim to be big data experts, only a handful of them can oversee a successful big data project implementation. Often, the projects are spearheaded by data infrastructure experts who lack skills and understanding of business goals and how big data can help achieve them. Organizations should not be carried away by the impeccable credentials of the so-called experts because the reality is often different from theory. Successful big data projects often begin with understanding an organization's goals and the business problem(s) that the initiative is aimed at solving. This is followed by putting a team of super professionals that will develop a way forward and aligning the project to the goals, mission, and vision of an organization from top to bottom. This will ensure the success of the big data project. Unfortunately, many organizations rush to implement a project without thinking of these issues, often resulting in failure.
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Scott Koegler

Scott Koegler is Executive Editor for Big Data & Analytics Tech Brief

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