Top Data Analytics Trends in 2018

Data science has been one of the most talked about topics for quite some time now. Though the theoretical knowledge and concepts of data science were present for a long time, its proper usage began almost a decade ago when huge sets of data became available to work upon. 

IT industry is gaining highly from data analytics. With the increase in the availability of data from all around the world, technologies such as big data, machine learning as well as deep learning that are applied in analyzing huge data sets are becoming tremendously popular.

If you plan to build your career in big data analytics and have a clearer idea of data analytics strategy, it is essential to have a deep understanding of customer behavior along with system performance. So if you have decided to pursue a data analytics certification, we have compiled a list of current data analytics trends for you to expand your knowledge on the subject.

1.    Internet of Things

IoT is on its way to becoming the biggest supporter of customer value in the future. Taking on to intelligent agents such as Google Assistant and Amazon Alexa has become quite common nowadays. All this has provided marketers with new means of interacting. According to research, the market of Internet of Things will grow by approximately USD 392 Billion from 2017 to 2022.

2.    Hyper-Personalization

Today, we live in a world where almost everyone is a tech-savvy and understands the usage of various devices as well as platforms to fulfill their needs. So, businesses are expanding their methods of interaction in order to create a more intuitive together with a personalized relation with the customers. Hyper-personalization involves the construction of highly targeted messages that can only connect with a particular group out of the whole audience. So basically companies prefer to create various separate campaigns for separate groups of people.

3.    Artificial Intelligence

Many organizations will make use of Artificial Intelligence in order to make decisions, provide to the customers and also give instructions to the staff in real time. Text analytics platform from the older generation was extremely complicated. Not all companies were able to make sense out of text data. With the in-depth knowledge of artificial intelligence, it has become much easier to analyze structured as well as unstructured text data.

4.    Machine Intelligence 

A combo of computer systems along with human intelligence is known as machine intelligence. A simple example of machine learning is face recognition that is generally applied to gadgets such as laptop and smartphones. It makes it possible for devices to perform independently. Machine learning is applied for product targeting in actual time, visual search, conversational commerce, integrated online as well as in-store analytics, marketing and analytics based on location, and also predictive merchandising.

5.    Behavioral Analytics

This is a means of evaluating consumer behavior. It helps you get a deeper understanding of the actions of the consumers. This is incredibly beneficial for organizations that wish to analyze what their customers actually need and how will they react in the coming time. Furthermore, it helps to come up with new concepts related to operational risks as well as opportunities by evaluating interactions along with dynamics between equipment, processes moreover macroeconomic trends.

6.    Graph Analytics

This is a useful analytical tool that provides graphs evaluate, codify as well as visualize the existing links between devises or databases in a network. As many companies are facing problems with their present set up of data analysis, they are shifting towards graph analytics.

We hope that by providing this list, we have helped you in your endeavor of earning a certification in data science and building a prosperous career ahead.