A look into Big Data Statistics

A look into Big Data Statistics

Stats are used to gather information about the world around us. They are collected, analyzed, and often make their way into news reports or other means of publishing statistical data. Although some statistics are based on hard facts (such as birth rates or death tolls), many others are not very precise because they’re most likely based on surveys that can be affected by human nature, bias, and error in reporting. A significant amount of big data statistics is also machine-generated using analysis of large databases. 

Types of analysis

This type of analysis has given rise to new kinds of questions that need to be answered with the help of stats. Here are just a few examples:

What makes users engage with certain advertisements more than others?

What do people want in their pizza?

What time of day is my business most profitable? 

All of these questions can be studied using large datasets. Moreover, they can be answered in real-time as they happen. Although big data statistics have been criticized for being too shallow and not providing enough contexts to draw meaningful conclusions from them, it’s usually safe to say that the benefits outweigh the downsides. For example, plenty of reports about how increased connectivity among devices has made it possible to collect various stats on people’s habits and behavior pattern (how many people use a specific product or what percentage of people prefers one pizza over another). The same principle also applies to businesses: with proper analysis and aggregation tools, companies can better understand their customers and competitors’ customers.

What you just read is a summary of what this article is about: big data statistics. Let’s get to it! In the following paragraphs, we’ll be going over how companies use them to reach business goals and add value to their services/products or simply learn more about their target audience(s). We’ll also touch on the pros and cons of this kind of statistics.

What is Big Data?

Big data refers to massive datasets or high-volume data sets that are too big for traditional (or standard) database tools and techniques to capture, manage, and analyze. That usually means any dataset that isn’t limited by computing hardware because it’s got an ever-growing volume, variety, or velocity. Big data can be structured or unstructured; however, most experts agree that anonymized transactional data like logs are mostly machine readable (and thus qualifies as big data). 

That makes big data statistics possible because there’s enough info in those massive datasets to conclude users’ behavior patterns. Moreover, companies can combine their datasets with third-party ones to gain insight into their target audiences, competitors’ customers, etc. That’s why many companies are investing in big data analysis and storage tools and use salesforce devops certification

An Overview of Big Data Statistics

However, it’s crucial. As mentioned before, the most significant benefit (thus the reason behind the investment) is that big data statistics can provide answers to questions like “what do people want in their pizza?” or “how many people use my product?” Moreover, they can tell you how many users prefer one mobile phone over another type of mobile phone, which mobile carriers work best for your business, what percentage of users place an order via a mobile device every day, what time of day is most profitable for your business, etc.

About Alex

Check Also

2 Real-Time Examples of Artificial Intelligence in Successful Startups

With the technology giants pumping billions of dollars to fund AI projects, it may seem …

Leave a Reply

Your email address will not be published. Required fields are marked *