What Is Data Analytics? A Beginners Guide to the Basics
In today’s digital market, companies are getting more and more data-driven. Those who can use data to their advantage, will thrive. Those who cannot, will fail. However, not everyone understands what exactly data analytics is and how it can help them succeed in the market. This blog post will help you get familiar with the basics of Data Analytics. By reading through this article, you’ll learn what Data Analytics is and why companies use it to make better decisions. Let’s get started!
What is Data Analytics?
Data Analytics is a process where data analysts, data scientists, and data engineers work together to extract insights from data to help make better business decisions. At a more advanced, level, it is the practice of finding predictive models to better understand the past and help predict the future.
Let’s look at an example to better understand what data analytics is all about.
A healthcare startup is interested in discovering how many patients have been coming to their clinic in the last few days. These data can be found in a number of places, such as patient records, the clinic’s calendar, or even the internet.
However, the start-up doesn’t have access to the data, so they have to extract it from somewhere else. What does the start-up do? First, they sift through their data to figure out what information is relevant to their research, such as the clinic’s address and the patients’ names. Next, they find the days when the clinic was open for business and then determine the number of patients who visited at that time. Once all the variables are found, the start-up can then use them to find the future instances when they’ll have the data they’re looking for, allowing them to create an algorithm to predict the number of patients that will visit in the future.
Advantages of Data Analytics
Just like any other business strategy, data analytics has its advantages, too. These advantages include helping you gain a competitive edge and make better decisions. Let’s take a look at how data analytics can help you get ahead of your competitors.
- Competitive Edge: When your competitors are facing unexpected issues, you will be able to make up some ground. For example, your competitors might be running behind in production or making some serious mistakes in their work. Data Analytics can help you stay on top of the situation and make sure you don’t miss out on this opportunity to gain a competitive edge.
- Better Decision Making: If you have the ability to make better decisions, you will have more success. Data Analytics can help you understand past events and predict what’s going to happen in the future.
This can help you make better decisions, such as deciding whether to hire or invest in a product or service.
Understanding the Need for Data Analytics
As mentioned above, data analytics is a process where data scientists and data engineers work together to extract insights from data to help make better business decisions. However, you can’t make those decisions without a reason. That reason is the need for data analytics.
What is the need for data analytics? It is the reason why companies are investing in data analytics. The need for data analytics refers to the fact that data analytics is needed to make better decisions in order to increase profitability.
For businesses to be profitable, they need to make decisions that are going to improve their profitability. A profitable business will thus be more likely to survive while a losing business will not.
If a company is losing profits, it is not going to be around for long. On the other hand, if a company is profitable, it has a good chance of staying in business for a long time.
Examples of Data Analytics
When it comes to data analytics, there are many types, each one with its own benefits. Let’s take a look at the examples of the most popular types of data analytics and their benefits.
- Predictive Modeling: Predictive modeling is a type of data analytics that helps you create models that can predict future events. These events are the number of patients that are going to visit your clinic or the number of sales your company is going to get. Basically, predictive modeling is all about making predictions with the help of data.
- Customer Retention: Customer retention is a type of data analytics that helps you understand why customers leave your business. For example, if a customer doesn’t return after a few weeks, you might want to know why they left. Customer retention can help you do that by teaching you how to keep your customers happy so they stay with your business.
- ROI Analysis: Return on investment analysis is a type of data analytics that helps you figure out how much it will cost you to implement a certain strategy. For example, if it will cost your company $100 for you to implement a certain strategy, you want to know if it is worth it. With ROI analysis, you can find out how profitable the strategy is and decide whether to implement it or not.
- Predictive Maintenance: Predictive maintenance can be thought of as a type of data analytics that helps you predict when your existing systems are going to break down. This can enable your company to implement proactive maintenance strategies.
Data Analytics is the process of applying statistics and mathematics to extract information from data to make better business decisions. It is a critical aspect of marketing, sales, and IT departments, and can help you gain a competitive edge and make better decisions.
There are many types and examples of data analytics, each with its own benefits. Predictive Modeling, Customer Retention, and ROI Analysis are some of the most popular types of data analytics, and they can help you gain an advantage in your industry.
Now that you know what data analytics is, why it is important, and some of its types, hopefully, you feel a bit more educated on the subject. Data Analytics is an important part of business, so make sure you invest the time to learn more about it.