The Latest Trends in The Data Analytics World

With the recent surge of the influx of information and data, enterprises are struggling to meet the demands of customers by making the best use of collected data. Businesses that adopted the latest technology and digital trends with the use of data analytics have become productive and more successful. Data analytics is the modern practice that helps businesses and organizations to make better decisions driven by key data insights. They can make and adjust their business models and processes based on valuable trends and logical information received through data analytics in real-time.  

The knowledge of the latest trends in the data analytics world allows businesses to stay ahead in the competitive and highly volatile consumer markets, so let’s have a look at the topic.

  1. Big Data on the Cloud 

The most arduous task of today’s times is to handle a lot of data that keeps on generating daily. It becomes difficult to collect, store, analyze, clean, tag, and organize huge volumes of data in a single place. Data scientists keep on exploring the best ways to store and retrieve data for later use. 

In such challenging situations, artificial intelligence and cloud storage facilities come to the rescue. The use of cloud platforms to store and make the best use of data is becoming increasingly popular. Businesses and companies are shifting towards cloud storage services for big data storage and processing. 

  1. Growth of Hybrid Cloud Services

The role of artificial intelligence and machine learning is evident in the automation of cloud services in the public and private sectors. It becomes easier to perform several IT operations due to the increased use of artificial intelligence. At present, enterprises are empowered to handle big data with more data security and scalability at low costs.  

One of the trends in the 2020 Data Analytics and Beyond is the growth of hybrid cloud services. A hybrid cloud is a combination of both public and private cloud platforms, thus allowing businesses to get the benefits of both types of services. Public cloud service providers can compromise on high data security and have reasonable costs. On the contrary, private cloud services are more secure for data protection but are not pocket friendly. So, to keep it balanced, the hybrid cloud platforms provide better performance with optimization at affordable costs. 

  1. Conversational Analytics and Natural Language Processing 

Conversational analytics and natural language processing are gaining immense popularity in the world of digital analytics. Voice-enabled devices make the interaction between business and end-users easier and seamless. This technology allows businesses to provide personalized products and services with the help of sentiment analysis and social listening. In addition, it also helps in the chatbot’s functionality and other conversation-based user interfaces resulting in meeting the customers’ demands. 

  1. Hyper Automation 

Hyper automation is another latest trend in the data sciences that will begin to rise in the coming years. According to information technology and data analytics experts, hyper-automation is an unavoidable and irreversible process, and the primary goal of automation should be to improve efficiency. 

Automation with the integration of other high-end technologies such as machine learning, artificial intelligence, and smart business processes can lead to a digital transformation of the business landscape. The core components of hyper-automation include business process management, advanced analytics, and robotic process automation (RPA). The most promising area of hyper-automation is estimated to be RPA in the coming years. 

  1. Augmented Analytics 

Augmented analytics is not a new technology. It is a branch of data analytics that relies on machine language, artificial intelligence, and NLP to automate the analysis of huge amounts of data. Augmented analytics makes the work of data scientists easier as they don’t have to use complex math and computer science tools. With the help of augmented analytics, data processing and distribution have become amplified by automating several critical tasks such as preparation, creation, and analysis of accurate models. By using augmented analytics, business owners can create simple and more manageable analytics models. The market of augmented analytics is expected to reach $29,856 million by 2025.

  1. Combination of IoT and Analytics 

The Internet of Things (IoT) is one of the emerging areas of the data analytics industry. The Internet of Things (IoT) is the device embedded with the latest technology, sensors, and software. The internet facility allows these devices to exchange and share information. With the help of data analytics and machine learning, data gathered through these devices can be easily analyzed. Several large-scale enterprises are already using IoT to handle data and make customers’ experiences better. However, this trend is going to see accelerated growth in small and medium-level businesses. 

  1. Generative Artificial Intelligence for Deepfake and Synthetic Data

The generative AI technology can help in creating new content from using previously available and existing data. This trend is going to enter businesses and other industries where it will help in training the machine language algorithms based on synthetic data. 

Synthetic data is artificially produced and not taken from real-life events. This type of technology will play an integral role in deepfake technology expansion where convincing images, videos, and audio of people are created with the help of artificial intelligence. Though, privacy and ethical concerns arose due to this technology. Analytical experts are improving their mechanisms to address these issues.  

  1. Blockchain Technology 

Blockchain has entered the IT industry after it has become successful in the healthcare sector. With the help of blockchain technology, data scientists can manage to apply analytical applications directly on the decentralized data from their personal devices. In addition, it is easy to validate and track the origin of data due to blockchain technology. Moreover, blockchains are a source of data and do not act as a database, so they will not replace data management systems and technologies. 

Data science and data analytics are the future of the IT industry that will continue to meet the increasing demands of businesses and organizations. It is essential to become adaptable with the latest innovations and developments to make the best use of data analytics practices. The growing demand for data analytics will pave the way for the recruitment of data analytics and data scientists who can guide businesses in making the best choices. 

About the author

Ariaa Reeds

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