{"id":12447,"date":"2023-12-05T18:18:41","date_gmt":"2023-12-05T18:18:41","guid":{"rendered":"https:\/\/lacountystore.com\/\/?p=12447"},"modified":"2023-12-05T18:18:41","modified_gmt":"2023-12-05T18:18:41","slug":"best-books-for-data-analytics","status":"publish","type":"post","link":"https:\/\/lacountystore.com\/best-books-for-data-analytics\/","title":{"rendered":"20 Best Books For Data Analytics (2023 Update)"},"content":{"rendered":"

Are you looking for the Best Books For Data Analytics<\/strong>? If so, you’ve come to the right place.<\/p>\n

Choosing the Best Books For Data Analytics can be difficult as there are so many considerations, such as Apple, Clever Fox, HP, Lenovo, Penguin Random House, WHSmith, Amazon.com. We have done a lot of research to find the Top 20 Best Books For Data Analytics<\/strong> available.<\/p>\n

The average cost is $39.49<\/i>. Sold comparable range in price from a low of $1.26<\/i> to a high of $102.00<\/i>.<\/p>\n

Based on the research we did, we think Data Analytics for Absolute Beginners: A Deconstructed Guide to Data Literacy [Book]<\/strong><\/a> is the best overall. Read on for the rest of the great options and our buying guide, where you can find all the information you need to know before making an informed purchase.<\/p>\n

20 Best Books For Data Analytics (19 Sellers)<\/h2>\n
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Product Image<\/span><\/th>\nProduct Name<\/span><\/th>\nFeatures<\/span><\/th>\nCheck Price<\/span><\/th>\n<\/tr>\n<\/thead>\n
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    • How to recognize the common data types every data scientist needs to master.<\/li>\n
    • Where to store your data, including big data.<\/li>\n
    • New trends in data analytics, including what is alternative data and why few people know about it!<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Wrangle-transform your datasets into a form convenient for analysis<\/li>\n
    • Program-learn powerful r tools for solving data problems with greater clarity and ease<\/li>\n
    • Explore-examine your data, generate hypotheses, and quickly test them<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Increase adoption and usage of data analytics with a step-by-step agile process to gain stakeholder buy-in and create actionable business value.<\/li>\n
    • Binding type: paperback.<\/li>\n
    • Number of pages: 232.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Highlight, take notes and search in the book<\/li>\n
    • In this edition, page numbers are just like the physical edition<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Explore a variety of statistical techniques to analyze your data<\/li>\n
    • Integrate your sql pipelines with other analytics technologies<\/li>\n
    • Perform advanced analytics such as geospatial and text analysis<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Don&#39;t simply show your data\u2014tell a story with it!<\/li>\n
    • Understand the importance of context and audience.<\/li>\n
    • Determine the appropriate type of graph for your situation.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Publisher: springer fachmedien wiesbaden<\/li>\n
    • Year published: 2020-05-14<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Publisher: packt publishing limited<\/li>\n
    • Year published: 20210830<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • A guide to the principles and methods of data analysis that does not require knowledge of statistics or programming.<\/li>\n
    • A guide to the reasoning behind data mining techniques.<\/li>\n
    • A unique illustrative example that extends throughout all the chapters.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Publisher: packt publishing limited<\/li>\n
    • Year published: 2022-06-24<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • It doesn't matter if your business has three employees or three hundred, you are likely generating far more information that you may realize, and certainly far more than you are likely tracking…<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Publisher: kogan page ltd<\/li>\n
    • Year published: 2022-06-03<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Four new chapters focus on predictive analytics, recognizing the importance of these tools in today&#39;s prediction efforts<\/li>\n
    • Examples of predictive analytics are based on historical data, much like what students may encounter in their own forecasts<\/li>\n
    • Techniques are explained as procedures, allowing students to replicate them with their own data<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: hardback<\/li>\n
    • Year published: 2020-01-10<\/li>\n
    • Number of pages: 134<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: paperback<\/li>\n
    • Year published: 2022-03-08<\/li>\n
    • Number of pages: 800<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: hardback<\/li>\n
    • Publisher: john wiley &amp; sons inc<\/li>\n
    • Year published: 20130308<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: hardback<\/li>\n
    • Publisher: john wiley &amp; sons inc<\/li>\n
    • Year published: 20130308<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Understand how data science fits in your organization\u2014and how you can use it for competitive advantage<\/li>\n
    • Treat data as a business asset that requires careful investment if you\u2019re to gain real value<\/li>\n
    • Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Turn textual information into a form that can be analyzed by standard tools.<\/li>\n
    • Make the connection between analytics and big data.<\/li>\n
    • Understand how big data fits within an existing systems environment.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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    • Binding type: hardback.<\/li>\n
    • Year published: 2017-04-21.<\/li>\n
    • Number of pages: 745.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n<\/div>\n<\/td>\n
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