What Is Data Analytics? Definition and Examples

Introduction

Data analytics is a buzzword that gets thrown around a lot these days. But what does it really mean? In this post, we’ll explain what data analytics is and how it works.

What is data analytics?

Data analytics is the process of using data to make better decisions. It’s about finding insights in your data and using those insights to drive better business decisions.

Data analytics is not just about numbers; it’s also about making sense of them. In other words, it’s not just about crunching numbers but rather interpreting them so they can help you make smart business decisions based on evidence-based insights. This helps you understand what your customers want and how they behave, as well as where there are opportunities for improvement within your organization or industry sector overall (for example: if customers prefer one product over another).

Data analytics vs. data science

Data analytics is a subset of data science. Data analytics is the process of analyzing data to gain insight into your business, while data science is the process of applying scientific methods to solve problems that require large amounts of complex data.

Data science can be broken down into three main areas: statistics, machine learning and applied mathematics (statistics).

Types of data analytics

Data analytics is the process of deriving meaning from data. It can be divided into two categories: descriptive and predictive. Descriptive analytics is used to describe data, while predictive analytics is used to predict future outcomes.

Example 1: Let’s say that you want to know what your customers think about your product or service so that you can make improvements based on their feedback. In this case, descriptive and predictive data would both be helpful because they provide information about what has already happened (descriptive) as well as what might happen in the future (predictive).

Customer analytics

Customer analytics is the process of analyzing data to gain insights into customers, their needs and behaviors. It can be used to improve customer experience, optimize marketing campaigns and more.

Customer analytics is a subset of business intelligence (BI). BI refers broadly to any technology that helps companies make better decisions by providing them with information about their operations. This could include software tools like Tableau or QlikView that let users visualize data in different ways; dashboards that show performance metrics in real time; predictive analytics systems that predict future outcomes based on historical trends; or other related solutions such as text analytics software for searching through unstructured text documents like customer reviews on Amazon or Yelp reviews posted online by customers who have received service from your company recently.

Marketing or market intelligence

Marketing analytics is the use of data and statistics to help marketers make better decisions. It can be used to improve the effectiveness of marketing campaigns and improve customer experience. Marketing analytics can be used to analyze customer behavior, segmentation, and market trends.

The goal of marketing analytics is for companies to better understand their customers so that they can develop strategies for attracting new customers or retaining existing ones. The information gathered from this type of analysis helps businesses determine which products are selling well, who their target audience is (or should be), how much money should be spent on advertising and where it would have the greatest impact on sales growth potentials within geographic areas or markets served by specific vendors who provide similar products at competitive prices

Business intelligence (BI) & business analytics (BA)

Business intelligence (BI) is the process of collecting, analyzing and presenting data to help improve business decisions. It can be used to answer questions like “Who are my customers?” or “What do they want?” Business analytics (BA) refers to the use of advanced statistical techniques and models for predictive purposes.

Business intelligence focuses on collecting data from various sources and then analyzing it in order to make better decisions about your business. It’s often used by marketing teams who need information about their customers so that they can create more effective campaigns or offers. For example, if you have an ecommerce website selling shoes online then BI would tell you how many pairs of shoes were sold each day last week so that when planning out future promotions for next week’s sale cycle it will be easier knowing what type/size/color combinations should be featured most prominently throughout various channels like Facebook ads or email newsletters sent out each morning at 6am PST time zone (or whatever time zone works best).

Business analytics involves taking raw data from multiple sources such as surveys filled out by past customers who may have purchased items through Amazon Prime two years ago but never returned again after trying out those same products themselves once before making another purchase online today – thus giving insight into what kind of pricing strategy might work best depending upon whether someone has shopped at our site before versus having never heard anything about us before visiting today.”

Performance management

Performance management software, systems and tools are used to help companies manage their performance. Performance management is a way of measuring how well an organization or team is performing in relation to its goals. It involves setting targets for specific outcomes, and then measuring whether those targets have been met over time so that you can make adjustments if necessary.

The purpose of this type of software is to provide managers with the information they need to understand where they stand in terms of achieving their goals so they can make decisions about how best to move forward.

Business process optimization (BPO) / digital transformation (DT) / digitalization

Business process optimization (BPO) is the process of improving business processes by analyzing and optimizing them. It’s all about making your company run more efficiently by identifying inefficiencies, streamlining workflows, and increasing productivity.

Digital transformation (DT) is all about using technology to create new products or services that improve the customer experience. For example: If you have an existing product or service but want to enhance it with a new feature that will attract more customers–that’s digital transformation!

Digitalization refers to any activity that involves digitizing information so that it can be used in other applications like machine learning algorithms or artificial intelligence tools. This includes things like collecting data from sensors on equipment as well as manually entering data into spreadsheets

Data analytics helps you make sense of your data so that you can make better decisions.

Data analytics is a process that helps you make sense of your data. It helps you use the right tools, techniques and methods to turn your data into useful information.

Data analytics can be used in many different ways:

• To understand customer needs better so that companies can provide them with better products or services. For example, Amazon uses data analytics to recommend products based on what other customers have bought or searched for. This helps people find what they want faster–and saves them money because they don’t have to buy things they won’t use!
• To predict future trends in business so companies know when it’s time for an upgrade or change in strategy (like hiring more staff) before competitors do it first!

Conclusion

Data analytics is a booming field that has become increasingly important for businesses. It has many applications, from customer analytics and marketing intelligence to performance management and business process optimization. Data scientists use the tools of their trade to analyze large amounts of data in order to understand what it means and how it can be used for making better decisions.