Before bouncing on to the Big Data and its future trends, let’s drop our needle first on to what exactly is data and why it carries so much of importance in the real world.
What is data?
When you have a collection of alphabets (A-Z, a-z), numbers (0-9) & special characters (!@#$, etc.), then such collection of characters is known as data.
Now you will ask why do we collect this data? And whether all the data is essential or not?
Firstly, data is collected and stored for analysis and processing. Analyzed and processed data gives rise to information which is a useful entity and all the present generation organization.
Secondly, this information gives rise to a pattern which helps the organization to analyze their strategies in place. This analysis gives them a perfect picture of whether there is any need for change in the strategy to improve their business, which affects their growth and income.
This initial introduction now prompts us to discuss the traditional way of database management, why there was a need for Big Data, and what all things we might see in future w.r.t. Big Data, i.e., Big Data Trends.
Traditional Database Management System
Relational Database Management System (RDBMS) is a traditional way of managing and maintaining the data. It is a collection of programs, functions, and capabilities that ensures the creation, updating, and deletion of data from the database. It helps IT teams to manage their data effectively with security, integrity, accuracy, and consistency.
What falls short in RDBMS?
With the introduction of wireless connectivity, free internet, and other application, it becomes nearly impossible to manage and analyze such big data sets. So there was a need to have a technology that can make the life of the IT team safe and secured.
So, Big Data was introduced to reduce the effort and time invested by database managers and increase the efficiency of analysis.
What is Big Data?
Big data refers to datasets that are too large and complicated for processing and managing the amount of data generated in this mobile world.
Why Big Data so important?
Consumers live in the digital world. Data is getting generated every single Nano-second like consider data generated by geolocation apps, social media apps, gaming apps, etc. To manage this massive collection of data, Big Data is essential.
Now, understanding the amount of data generated every Nano-second, Big Data Architecture, and other criticalities, we feel it is vital to know where will this world take us in the coming years.
Big Data Trends
Keeping an eye on Big Data Trends is like monitoring the daily shifts in the wind. The minute you stop monitoring, it changes its direction. Yet, we have found some of the top 5 known and famous trends which might be useful and helpful for you to understand the future of Big Data.
- Open-source applications in combination with Big Data
Open-source applications like Apache Hadoop, Spark have joined come to join their hands and dominate in the big data space, and the trend seems to continue. According to one survey, more than 60% of the enterprise has started accepting and implementing Hadoop clusters in their production in place of a traditional database. And one study suggested that there is a 33% increase in the usage of Hadoop ever year. Figures suggest that we are into a Big Data world.
2. Usage of In-Memory Technology
The traditional database used to store its data in the hard drives. But, considering the climatic conditions, space limitations, and security issues, it is essential to bring in a technology that can reduce all these issues. In-memory technology will use RAM instead, which is very, very fast to store the data and retrieve it. According to one study, if In-Memory Technology goes successful, there is a chance that we will see a 30% increase in its usage every year.
3. Machine Learning
Understanding and analyzing the data trend on its own and reacting accordingly is what machine learning does. With the invention of Big Data, it becomes effortless to process the massive amount of data that is getting generated, and it becomes easy for a machine to judge the trend and respond. One of the Machine Learning technology is Python.
4. Predictive Analytics
When big data analytics evolved, organizations were looking into the past data to analyze what had happened, and later, using the analytical tools, they were trying to conclude. But, using Machine Learning and Big Data, Predictive Analytics evolved, which uses the capabilities of Machine Learning and Big Data Analytics to predict the future.
With all the new devices and applications coming online, organizations are going to experience faster growth of data as compared to what they have seen in the past. Many organizations have started deploying AI and IoT solutions, and it is assumed that there is a 30-40% rise in such deployments every year. Many will need new technologies to handle this huge amount of data coming from their IoT deployments.
When we say that there will be an increase in the use of big data analytics and architecture, it is necessary to understand that there will be a direct impact on the number of resources organizations will need to work on the technology. Every organization looks for a smart and intelligent individual having knowledge of technology as well as its applications or someone who has a certification in big data courses. At Simplilearn – one of the best online certification training providers, our trained and working professionals make sure that they give you every insight into the industry, which is very important to understand when you are learning new technology.
We have seen in the last decade that organizations have hired more and more individuals who have kept a mutual understanding of the technology trends.