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  • Data Analytics: 5 Books in 1

  • Bible of 5 Manuscripts - Beginner's Guide + Tips and Tricks + Effective Strategies + Best Practices to Learn Data Analytics Efficiently + Advanced Strategies
  • By: Daniel Jones
  • Narrated by: William Bahl
  • Length: 6 hrs and 59 mins
  • Unabridged Audiobook
  • Categories: Computers & Technology, Data Science
  • 4.0 out of 5 stars (4 ratings)

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Summary

It doesn’t matter if your business has three employees or 300, you are likely generating far more information that you may realize and certainly far more than you are likely tracking effectively. Understanding what this data truly means starts with managing it successfully, which is where the process of data analytics comes into play. If you like the sound of putting your data to good use but aren’t quite sure what the ins and outs of data analytics entail, then Data Analytics: Bible of 5 Manuscripts - Beginner's Guide + Tips and Tricks + Effective Strategies + Best Practices to Learn Data Analytics Efficiently + Advanced Strategies will be your perfect learning guide.

On average, there are roughly two quintillion bytes worth of new data created each and every day, which means that knowing what to do with it is easily a full-time job. Luckily, there are a wide variety of options out there when it comes to focusing in on the data that you want to use and using it in the most effective way possible. Inside, you will find all the tools you are going to need in order to do just that, regardless of if you are part of multinational conglomerate or are running your own start-up. 

Having the right data means being able to make the right decisions about your future because you know what your customers want, often before they do. Making the right decision in the moment means understanding the potential that this bundle of five audiobooks is offering and making the choice to go ahead and click "Buy Now"! Your future, more successful business will thank you. 

So, what are you waiting for? Grab this powerful pack of audiobooks that teaches you everything about data analytics.

©2018 Daniel Jones (P)2018 K.M. Kassi

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Business Analytics & Underlying Science Eplained

Big Data analytics needs to understand business objectives that have been put in place with the processes that help to grow the business and its profit.

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A businesses user's guide to data science

I have read the concepts in books and online. Here, the concepts are explained very clearly.

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  • Judith Hwang
  • 23-06-20

Beyond the big data hype

Don't worry. Big Data doesn't have a certain definition. The best definition I've seen came from an analytical genius, Josh Dreller. He says big data is anything that won't fit into an Excel spreadsheet. For others, it brings up images of a huge server farm where machines are just humming away.

You can find data everywhere. The quantity of digital data that is out there is growing at an alarming rate. There are more than 2.7 zettabytes of data in existence today. By 2025, this is expected to be at 180 zettabytes.

This data including the photos you take with your phone, to the financial stats of the Fortune 500, has just begun to be looked at to figure out the insights that will help businesses improve their organizations. This is why businesses and organizations are looking for professionals that can understand all this data.

Big Data is a lot broader and deeper than any of that. There are several areas that Big Data can be used to help businesses.

25 people found this helpful

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  • Craig
  • 24-06-20

Dipping your toe into the pool of data science!

Data analytics is much more than analyzing data. Especially on advanced projects, most of the required work will be done upfront, in preparing, integrating, and collecting data and again when revising, testing and developing models to make sure that the results they produce are accurate. In addition to data analysts and data scientists, analytic teams will include data engineers. Their job is helping get sets of data ready to be analyzed.

The process begins with collecting the data, then data scientists find what information is needed for a certain application, and then they work by themselves or with data engineers and IT workers to get it ready to be used. Data from many sources might need to be combined through data integration routines like a data warehouse, NoSQL database, or Hadoop cluster. There are other cases where the collection process might need to pull a subset out of the stream of data that goes into Hadoop and putting it into a separate section within the system, so it gets analyzed without hurting the complete data set.

When the needed data is put into place, they will next fix and find quality problems that might affect how accurate the analytic application is. This includes running data cleansing, and data profiling jobs that ensures all the information within the data set is constant, and duplicate entries and errors are gotten rid of. More data work is done to organize and maneuver the data for whatever use has been planned. Data governance policies are added to make sure the data is used in the right way and stays within the corporate standards.

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  • Melvin Tice
  • 25-06-20

Data Mining/Business Analytics/Data Science

Big Data is being used to optimize businesses. Retailers can optimize their stock by using predictions that were generated from social media data, weather forecasts, and web search trends.

Warehouse stores like Costco and Sam’s Club have begun using a process that is using Big Data analytics to optimize delivery routes and supply chain stores. Radio frequency identification sensors and geographic positioning get used to tracking vehicles or goods to optimize routes by giving them live traffic data. HR processes are being improved by using Big Data.

Big Data tools can be used to measure staff engagement. Sociometric Solutions put sensors in their employee's name tags that would show social dynamics in the workplace. These sensors reported the employee's movements around the workplace, their tone of voice when communicating, and who they spoke to.

Bank of America, one of Sociometric's clients, saw their top employees in the call centers would take breaks together. Bank of America then instituted a policy to take breaks in a group. Their performance improved by 23 percent.

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  • Mattie
  • 27-06-20

Like you never thought possible

It is important to keep in mind that data analytics in general, not to mention the bleeding edge deep learning technologies, are an ever-evolving field of study which means that the only way to ensure that you ever grasp everything that it has to teach is if you commit yourself to becoming a lifelong learner. Anything else would ultimately result in a less than optimal use of the skills you have learned, which will lead to inferior data and poorer choices in the long run. The next step is going to be to stop reading already and to get ready to get started using data analytics in the way that is going to benefit you the most in both the short and the long-term. While the steps outlined in the proceeding chapters likely seem complicated now, in time they will become much easier to wrap your head around. Luckily, utilizing data analytics is a skill which means that it will improve every time you use it. This doesn’t mean that these skills will materialize overnight, however, using them effectively is going to be a marathon, not a sprint, which means that slow and steady wins the race.

17 people found this helpful

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  • Samantha Brown
  • 28-06-20

For better use!

When it comes to putting data analytics into play in order to complete a task, the first thing you will need to consider is if the process that you are about to utilize is actually going to be worth it in the long run. Data analytics costs are often quite high, especially if you are going either very wide or extremely granular, and it is possible that the costs are going to end up outweighing the benefits. For example, if you plan to go through all of the company’s old sales data in order to find out the most profitable product that you sold last year in order to more effectively realign your business moving forward. This is likely going to be a worthwhile use of your time, assuming you end up with results that you can build on moving forward, even if you find nothing useful, that is still worthwhile information to have as it shows you would need to pivot into products that have a more dramatic following. On the contrary, however, if you spend the same amount of time to determine the number of sales you made on days with either 1 or 0 in the date, you likely could have put that money to better use elsewhere. In the first instance, assuming you found actionable information, you would then be able to look at the market conditions around your best sellers and strive to recreate them in as many different ways as possible. With this clearly outlined you will then be able to shift the direction that your business is going to move in for the better in both the long and the short-term. The first example provides you with greater insight by making it clear what products your customers are interested in, but also those that they are not interested in in the least. This will then provide you with several different alternatives as to how you can more effectively utilize company resources. With the right groundwork laid, regardless of the outcome, you will be virtually assured to cut down on waste in at least one area while also being able to more easily focus on the parts of the business that are going to do the most to increase sales revenue.

15 people found this helpful

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  • Kathleen Carr
  • 30-06-20

A gateway into the world of data science

Analytics in the modern sense of the word were first refined by a man by the name of Frederick Taylor, an engineer, who created a number of different exercises to encourage time management. He was very interested in the concept of industrial efficiency along with the potential benefits it could bring to businesses of all types. He started off by determining how his team at Midworld Steel Works could work as efficiently as possible without taking any undue safety risks at the same time. The insights he gleaned helped to create the field of scientific management and his most pertinent observations are still in use today. Perhaps most notably used directly by Henry Ford when it came to tuning the speed of his assembly lines, the real potential for analytics was not unlocked until computers became an everyday part of the workplace as a whole. Eventually, however, the computers became powerful enough to understand what truly large amounts of data were really saying, and were able to determine a wide variety of likely outcomes from the results. Thanks to computer science, data analytics has been able to rapidly become a part of several different common applications and regularly shows up in everything from data warehouse to the resource planning systems utilized by major enterprises.

9 people found this helpful

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  • kenneth crawford
  • 27-11-18

Excellent Book

The language of this book was a very simple, interesting and eye opening. It covers very broad subjects starting from how data is related to businesses to the upcoming next generation of data science.

3 people found this helpful

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  • Lillie Goodrich
  • 02-07-20

Summary Of Data Science

Understanding what all this data is trying to tell you is the key to getting ahead in the marketplace and understanding the ways big data can help you do just that is key to finding success no matter how fierce the competition. The following chapters will discuss everything you need to know in order to get started preparing yourself for the process of data analytics, starting with explain just what it is all about. From there you will learn all about the many benefits of predictive analytics, and how it can be put to use to help you plan out future business plans with relative certainty. Next you will learn how to set up a discrete choice model and the ways it will help you determine the products you are selling are always going to be a hit. Then you will learn all about the ways in which machine learning is changing the world of big data forever with deep learning and neural networks. There are plenty of books on this subject on the market, thanks again for choosing this one! Every effort was made to ensure it is full of as much useful information as possible.

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  • MARK BRODY
  • 27-11-18

Nice Book in the field of Big Data Science.

This book is a very sensible and easy approach for anyone interested in the field of data analytics. I covers the broad areas that Data analytics such as tools that can be used and the overall application of data analytics.

2 people found this helpful

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  • Yolanda Headen
  • 25-11-18

This book helps me to understand the modern trends

The language of this book was a very simple, interesting and eye opening. It covers very broad subjects starting from how data is related to businesses to the upcoming next generation of data science. Now the world has changed into a whole new era. This book helps me to understand the modern trends of data analysis.

1 person found this helpful