10 Data Analytics Trends to Watch Out for in 2022-23

The field of data analytics is constantly evolving.  What was cutting-edge a few years ago is now commonplace, and what’s hot now will be old news before you know it.  That’s why it’s important to stay on top of the latest trends so you can stay ahead of the curve.  Here are 10 data analytics trends to watch out for in 2022-23: 

1. Automated machine learning: Machine learning is a type of artificial intelligence that allows computers to learn from data without being explicitly programmed. Automated machine learning automates the process of building machine learning models so that non-experts can use them. This trend will continue to grow in popularity as more and more businesses seek to take advantage of the benefits of machine learning without needing to hire expensive data scientists.

2. Natural language processing: Natural language processing (NLP) is a subfield of artificial intelligence that deals with understanding human language and extracting meaning from it. NLP is used for tasks such as automatic summarization, sentiment analysis, and topic modeling. As businesses increasingly look to automate customer service and other tasks that traditionally required human interaction, NLP will become more and more important. 

3. Predictive analytics: Predictive analytics uses historical data to make predictions about future events. It is used extensively in fields such as marketing, fraud detection, and risk management. With the increasing availability of data, predictive analytics will become increasingly accurate and therefore more popular in the coming years. 

4. Prescriptive analytics: Prescriptive analytics takes predictive analytics one step further by not only making predictions about future events, but also recommending actions that should be taken to achieve desired results. For example, a prescriptive analytics system might predict that a certain marketing campaign will be successful and then recommend which channels should be used to reach the target audience most effectively. 

5 . Artificial intelligence: Artificial intelligence (AI) is a catch-all term that refers to any computer system that can perform tasks that ordinarily require human intelligence, such as visual perception, natural language understanding, and decision making. AI is already being used extensively in fields such as healthcare and finance, and its usage is only going to increase in the coming years as businesses look for ways to automate more and more tasks.  

6 . Blockchain: Blockchain is a distributed database that allows for secure, transparent, tamper-proof transactions. Originally developed for cryptocurrency like Bitcoin, blockchain is now being applied to a wide variety of industries such as supply chain management, identity management, and asset management..  

7 . Internet of Things: The Internet of Things (IoT) refers to the growing trend of connecting physical devices to the internet so that they can communicate with each other and exchange data..  

8 . Augmented reality: Augmented reality (AR) superimposes computer-generated images on top of real-world images, thereby augmenting or enhancing reality..   

9 . Virtual reality : Virtual reality (VR) creates a simulated environment that can be experienced through sight and sound.  

10 . 5G : 5G is the next generation of cellular technology that promises higher speeds and lower latency than its predecessor   

As you can see, there are many exciting trends emerging in the field of data analytics. Some of these trends are well established while others are just beginning to gain traction; all of them have the potential to revolutionize the way we collect and use data.. So keep your eye on these 10 trends in the coming year; who knows, maybe one or two of them will change your business for the better!