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Publisher : O’Reilly Media; 1st edition (September 17, 2013)
Language : English
Paperback : 413 pages
ISBN-10 : 1449361323
ISBN-13 : 978-1449361327
Item Weight : 1.49 pounds
Dimensions : 7 x 0.9 x 9.19 inches
Customers say
Customers find the book provides an excellent overview of data science concepts with a perfect mix of high-level explanations and technical details. They describe it as clear, concise, and written in easy-to-understand language. The book is described as helpful for beginners and a great entry level book. Readers appreciate the well-designed titles and pleasant writing style. Many consider it a valuable purchase and say it gives a solid grounding in both business and data.
AI-generated from the text of customer reviews
Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
In today’s data-driven world, businesses are constantly collecting and analyzing vast amounts of data to gain insights and make informed decisions. Data science has become an essential tool for organizations looking to stay competitive and drive growth. Two key components of data science that play a crucial role in business decision-making are data mining and data-analytic thinking.
Data mining is the process of discovering patterns and insights within large datasets using various statistical and machine learning techniques. By leveraging data mining, businesses can uncover hidden trends, relationships, and anomalies in their data that can inform strategic planning, marketing campaigns, and product development.
Data-analytic thinking, on the other hand, involves the ability to approach business problems with a critical and analytical mindset. It requires asking the right questions, framing problems in a way that is conducive to data analysis, and interpreting results in a meaningful way. Data-analytic thinking helps businesses make sense of their data and derive actionable insights that drive business growth.
To effectively harness the power of data mining and data-analytic thinking, businesses need to invest in the right tools and technologies, hire skilled data scientists and analysts, and foster a data-driven culture within their organization. By leveraging data science, businesses can unlock the full potential of their data and make smarter, data-informed decisions that drive innovation and growth.
In conclusion, data mining and data-analytic thinking are essential components of data science that play a critical role in driving business success. By embracing these principles and integrating them into their decision-making processes, businesses can gain a competitive edge and thrive in today’s data-driven marketplace.
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