Posted on 2017-10-09, by manhneovn.
81 pages | Oct 2017 | English | ASIN: B07633HG74 | AZW3 | 1.27 MB
If you are convinced that the world today is producing more data than the previous decades, then you understand that processing yesterday's data for today's use at times is not enough. The level of data analysis that is needed in highly competitive business environment needs to be processed, analyzed and used immediately for businesses to be ahead of their competition.
Having this in mind, you need to understand from the ground up, what data is, the different types of data and how you should identify the right data for your business. To help you understand the simple basics of data and how it needs to be analyzed, then Data Analytics for Beginners is the book that you have been waiting for.
The size and type of business you are running doesn't matter because after all, it will depend on your ability to understand the data that your business is exposed to so as to make better business decisions for the current working environment and the future. Are there patterns in your business that you cannot see? Do you want to make sense of the shopping trends of your clients to better enrich their experience? Do you want to know your target market even more? Do you want to better derive insights from the feedback your clients give you? These questions can only be answered when you perform a data analysis for your business.
Collecting the data is one thing, analyzing them is another matter entirely as it is not something that can be done haphazardly by just looking at the data. If you hope to understand your data well, you need to understand the data you are collecting, the methods to use and the right tools to use when analyzing the data.
Inside you will find valuable steps and tools that will help make your information work for you. Do not let yourself get complacent, stop looking at the data that you collect each day and start analyzing your data to move your business up. Get started by buying this book today!
Inside you will find
How data should be understood?
Terms and concepts used in data analysis.
Data mining and the different kinds of databases used to store data.
How information can be retrieved and manipulated in the database to create a visual representation of what you want to know?
The life cycle of data analysis.
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