Table of Contents SWOT Analysis StrengthsWeaknessesOpportunitiesThreatsData Analytics in the Manufacturing IndustryConclusionBibliographyData analysis is the process of examining sets of data in order to draw conclusions about the information they contain. This is done using specialized systems and software. In this report, I will talk about data analytics and discuss some of the strengths, weaknesses, opportunities and threats associated with it. Finally, I will discuss the importance of data analytics in the manufacturing industry today. Data analytics technologies and techniques are widely used in business industries to enable organizations to make more informed business decisions and by scientists, engineers and researchers to verify or disprove scientific models, theories and hypotheses. Data analytics can help businesses increase revenue, improve operational efficiencies, optimize marketing campaigns and customer service efforts, respond more quickly to emerging market trends, and gain a competitive advantage over competitors , all with the ultimate goal of improving business performance. Depending on the application, the analyzed data may consist of either historical records or new information processed for real-time analysis. Additionally, it can come from a mix of internal systems and external data sources. Say no to plagiarism. Get a tailor-made essay on “Why Violent Video Games Should Not Be Banned”? Get the original essay Strengths of SWOT Analysis The fundamental strength of data analysis or big data lies in the three Vs it represents: volume, velocity and variety. The volume, speed and variety of data collected opens up a new range of business opportunities across all functional areas of marketing, operations, accounting, finance and human resource management, and in all kinds of industry organizations. government and non-profit. In short, data itself is an opportunity for innovation. Weaknesses As big data analytics becomes increasingly popular and becomes a more standard part of modern business processes, there will be a need for more training and knowledge transfer for small and medium-sized businesses so they can analyze the data they collect to get a better idea of ​​what their customers want and need. It was highlighted that there are not enough people comfortable with large amounts of data and that big data should be integrated into all aspects of an undergraduate degree so that more of graduates have at least a moderate level of understanding in the field. Another major problem with data analysis is the risk of unintentional or deliberate violation of individuals' privacy. As businesses analyze large amounts of data, the risk of this happening can be high. Opportunities Data analytics offers an exciting set of opportunities across many different industries, including healthcare, education, manufacturing, supply chain and transportation. Likewise, the promise of Big Data spans all functional areas, including marketing, accounting, finance, operations and human resource management. Big Data can be used to identify unique customer needs and wants and develop products and services that meet those needs. Another area in whichdata analysis could benefit a good majority of the population would be that of education. Having the ability to crunch data to see if teachers are effectively improving their students' performance would not only increase test scores, thereby improving the reputation of the school system, but also provide a workforce future work more productive and more educated. the more data is collected, there is a risk that some of this data will be used inappropriately. For example, in healthcare, if a third party analyzed data, it would have to be stripped of certain identifying information. Leaving someone's name or other personally identifiable information in a data set sent outside the company could not only put the customer at risk, whether through identity theft or of a certain type of fraudulent scheme; but it could also have an impact on the company that published the information. Data Analysis in the Manufacturing Industry Data analysis is extremely important for the manufacturing industry today, as it is essential to achieve productivity and efficiency gains and discover new information to drive innovation. Using Big Data analytics, manufacturers can uncover new insights and identify patterns that allow them to improve processes, increase supply chain efficiency, and identify variables that affect production . Manufacturing business leaders understand the importance of data analytics in today's industry. A study from Honeywell Process Solutions-KRC found that 67% of manufacturing executives plan to invest in data analytics, even in the face of pressure to reduce costs. The majority understand that data analytics is necessary to succeed in a data-driven economy, and they are investing in data integration and management assets to achieve digital transformation and gain a competitive advantage. With the right analytics, manufacturers can focus on each segment of the production process and examine supply chains in detail, taking into account individual activities and tasks. This ability to narrow the scope allows manufacturers to identify bottlenecks and reveal underperforming processes and components. Data analysis also reveals dependencies, allowing manufacturers to improve production processes and create alternative plans to address potential pitfalls. Data analysis also helps to accurately predict demand for personalized products. By detecting changes in customer behavior, data analytics can give manufacturers more lead time, providing the ability to make personalized products almost as efficiently as goods produced on a larger scale. Innovative capabilities include tools that enable product engineers to collect, analyze and visualize customer feedback in near real time. By giving manufacturers the tools they need to examine processes, data analysis allows them to identify points in the production process where they can cost-effectively insert custom processes using internal capabilities or postpone production to allow a partner to run the customization before completion. of the manufacturing process. According to a Deloitte study on the rise of mass customization, the ability to postpone production provides manufacturers with new flexibility that allows them to:: 27/09/18.