Big data. Data science. Predictive analytics. It can be hard to keep up with all the latest trends in data analytics, especially when they seem to change every day. But while the terminology may be new, the concepts behind these trends are not. In fact, many of them have been around for a long time.

We’ll explain what you need to know about data analytics to catch you up to speed, including the benefits and top 15 trends to look out for in 2022. 

What Is Data Analytics?

Let’s start by defining data analytics. There is no one-size-fits-all answer to this question, as the field of data analytics covers a wide range of activities and techniques. In general, though, data analytics can be described as the process of extracting meaning and insights from data. 

This can involve anything from simple descriptive statistics to more complex predictive modeling and machine learning.

Data analytics can be used to answer questions such as:

• What are the most important factors that influence customer satisfaction?

• How can we predict demand for a new product?
• Which marketing channels are most effective for acquiring new customers?

What Are The Benefits Of Data Analytics?

Data analytics can provide a number of benefits, including:

• Increased efficiency
• Improved decision-making
• Greater customer insight
• Improved risk management
• Enhanced competitiveness

When businesses analyze their data, they can identify areas where they are wasting time and resources. Making changes in these areas can lead to increased efficiency and productivity. In some cases, it may even be possible to automate certain tasks that are currently being done manually.

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When businesses have a better understanding of customer behavior and preferences, they can improve the decisions they make regarding product development, marketing, and sales strategies. This allows them to focus their resources on areas that are more likely to be successful, which can lead to increased profits. 

In addition, understanding customer behavior and gaining greater customer insights can help businesses to identify potential problems early on, as well assisting in improving conversions.

Risk management is an essential part of doing business, and data analytics can play a key role in helping businesses identify and mitigate risk. By understanding customer behavior and preferences, businesses can better assess the risks associated with new products or services. Data analytics can also help identify potential security risks, and enable businesses to take steps to avoid or minimize them

When businesses use data analytics, they are able to make better decisions and stay ahead of the curve, enhancing their competitiveness. In addition, data analytics can help businesses identify potential problems early on, which allows them to take steps to avoid or minimize them.

15 Trends That Will Reshape Data Analytics

The field of data analytics is constantly evolving, and new techniques are being developed all the time. As such, it is important to keep up with the latest trends and developments in the field.

Let’s dive into the trends that are slowly but surely changing data analytics, including how it’s used.

1. Increasing use of artificial intelligence and machine learning

As data analytics become more sophisticated, businesses are increasingly turning to artificial intelligence (AI) and machine learning to help them make sense of all the data they have. These technologies can automatically identify patterns and correlations in data, making it easier to find insights that might otherwise be hidden.

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2. More focus on real-time data

In the past, businesses would often base their decisions on data that was already a few days or even weeks old. However, with the rise of streaming data and the Internet of Things (IoT), businesses are starting to focus on using real-time data to make decisions. This can help them respond more quickly to changes in the market or customer needs.

3. Big data getting bigger

Big data is one of the most important trends in data analytics right now. With so much data being generated every day, businesses need to find ways to make use of all of it if they want to stay competitive. Big data analytics allows them to do just that, by giving them the ability to process and make sense of large amounts of data quickly and easily.

4. The rise of the Data Lake

A Data Lake is a storage repository that holds all kinds of data, both structured and unstructured. This kind of repository is becoming increasingly popular, as businesses realize the value of being able to store and access all kinds of data easily. Having a Data Lake gives businesses the ability to perform advanced analytics on all kinds of data, which can lead to valuable insights.

5. The growing importance of Streaming Analytics

Streaming analytics is a type of analytics that focuses on real-time data. This is becoming increasingly important as businesses seek to make decisions faster and react to changes in the market more quickly. Streaming analytics allows businesses to process data as it comes in, rather than having to wait for batches of data to be processed.

6. The rise of NoSQL databases

Traditionally, data has been stored in relational databases. However, with the rise of big data, this is no longer practical. Instead, businesses are turning to NoSQL databases, which are designed to handle large amounts of data. NoSQL databases are often more flexible and easier to scale than relational databases, making them ideal for big data applications.

7. The increasing popularity of cloud-based solutions

Cloud-based solutions are recommended by many popular IT support companies, as they offer a number of advantages over traditional on-premise solutions. They are often more scalable, more flexible, and less expensive. This is especially important for businesses that are dealing with big data, as they can avoid the need to invest in expensive hardware and software.

8. The rise of self-service analytics

In the past, analytics was often something that was done by a small team of experts. However, this is changing, as self-service analytics tools become more prevalent. These tools allow users to do their own analysis without needing to know how to code or use complex statistical methods. This makes it easier for non-experts to get insights from data, which can lead to better decision-making.

9. The growing importance of data visualization

Data visualization is becoming increasingly important, as it allows businesses to quickly and easily see patterns and trends in data. This is especially important for big data, as it can be difficult to make sense of large amounts of data without being able to visualize it. Data visualization tools allow businesses to create beautiful and informative visualizations that can help them understand their data better.

10. The rise of predictive analytics

Predictive analytics is a type of analytics that uses historical data to make predictions about future events. This is on the rise, as businesses seek to anticipate changes in the market or customer needs. Predictive analytics can help businesses make better decisions about where to allocate resources and how to plan for the future.

11. The growing popularity of mobile analytics

Mobile analytics allows businesses to track and analyze data from mobile devices, such as how customers are using their apps or what kind of searches they are doing. This helps businesses understand the mobile customer better and make decisions about how to optimize their mobile apps.

12. The increasing importance of social media data

Social media data providesinsights into customer behavior and preferences. Social media data can be used to track trends, understand customer sentiment, and even predict future sales. This makes it an essential tool for businesses that want to stay ahead of the competition and find unique ways to connect with consumers.

13. The rise of Internet of Things data

The Internet of Things (IoT) is a network of devices that are connected to the internet. This is resulting in a huge increase in the amount of data that businesses have to deal with. IoT data can be used to track the performance of devices, understand customer behavior, and even predict future demand. This makes it an essential tool for businesses that want to stay ahead of the competition.

14. The increasing importance of unstructured data

Unstructured data is a type of data that does not have a pre-defined structure. It includes things like emails, social media posts, images, and videos. Unstructured data providesinsights into customer behavior and preferences. 

15. The growing importance of data governance

Data governance is becoming increasingly important as businesses deal with larger and more complex data sets. Data governance helps ensure that data is accurate, consistent, and accessible, which is essential for making sure that data is being used effectively and efficiently. Some examples of the growing importance of data governance include the need for businesses to:

• Ensure that data is accurate: Inaccurate data can lead to incorrect decision-making

• Ensure that data is consistent: Inconsistent data can be difficult to interpret and use
• Ensure that data is accessible: Accessible data can be used more effectively and efficiently

Wrapping Up

As the amount of available data becomes increasingly overwhelming, it’s essential for businesses to have the tools and processes in place needed to manage it effectively. 

By understanding the trends listed above and implementing them into their business strategy, businesses can gain a competitive advantage in the ever-changing world of data.

Author bio

Travis Dillard is a business consultant and an organizational psychologist based in Arlington, Texas. Passionate about marketing, social networks, and business in general. In his spare time, he writes a lot about new business strategies and digital marketing for DigitalStrategyOne.