Big Data stands for data that arrives in greater quantity, volume, and increasing velocity. To put it simply, big data is more complex and large data sets come especially from new data sources. Big data sets are too huge in volume for traditional, regular data processing software to manage. But if this data can be tapped and used properly, it can address huge business problems that one could never have tackled before this.
Interested in pursuing a career in Big Data and want to enroll in a big data course? Read this article to learn what are the emerging trends in Big Data in 2022.
Artificial intelligence or AI has been a gamechanger for data analytics ever since it came to the fore. With companies generating huge data – both structured and unstructured- most automated types of analytics can hardly get through. Today, AI has changed the way we look at such data. It is used in machines, software, and computers that are capable of learning on their own. If a business wants to know which of its customers is most valuable, it can do so with the help of AI. But if it had the regular, traditional computing available to them, they might be able to see who makes the most purchases. But what if a first-time customer spends $100 on the very first day, is that person more valuable to the business than an old customer who spends $100 in a period of 6 months?
To understand that a lot more data needs to be made available to the business – like average customer’s lifetime purchases, some personal data like their age, spending habits, or even income levels could be extremely useful. Interpreting such data and drawing insights from them is a highly complicated task. But AI is useful here because it attempts to interpret all this data and come up with predictions that were not possible even a few years back.
Newer ways of exploring and interpreting data
Data visualization is the final step of the analytics process before any action is taken based on the findings. Traditionally, communication between devices and human beings is carried out via visualization – – graphs, dashboards, charts, etc. that highlight the key findings and help business leaders determine what changes are to be made as per the suggestions from the data.
One area that has seen a massive breakthrough is the use of human language. Analytics tools allow us to ask data questions in clear, human language and to receive answers in the same language. This will greatly increase access to such data and improve the overall data performance of an organization. This technology field is popularly known as natural language processing (NLP). VR can be very useful for creating newer types of visualizations that allow more people to gain richer meaning from the data, whereas AR can directly show how the results of data analytics are impacting the world.
Constant developments are at work and newer technologies are coming up to the fore with each passing day. Join a program today and get started with your training.