Big Data Basics
Big data and analytics
In this blog, the category has been developed for those who are willing to master big data technology. It explains several tools and methodologies of performing operations on a large pool of data. The main focus of this section is to clarify the differences between the rivals to make it clear that which technology has to be used to meet different requirements. Apache Storm vs Apache Spark, Apache Hadoop vs Apache Storm, MapReduce vs Apache Spark, Hadoop vs SQL Performance, and Business Intelligence vs BigData is some of the topics that have been covered here. While topics, like What, is Splunk, Uses Of Splunk, What is MapReduce, Hadoop Ecosystem and so on are also has been described.
The five main reasons to study big data are:
1. The decisions that are driven by data are of competitive advantage
The organizations make use of big data to identify trends and detect patterns to predict the future. This way organizations know more than their competitors.
2. Big data is the foundation for Artificial Intelligence
The techniques and capacities required in big data organizations and artificial intelligence are similar. The organizations benefit greatly by building a sound big environment first and then set up artificial intelligence with big data as the base.
3. The demand for big data skills is high
With the current trends in big data, the requirement for big data professionals is rapidly growing. As a result, there are large increases in the salaries of the people working on big data.
4. There is growth in investments in big data everyday
Studies show that big data investments are growing year after year. The International Data Corporation (IDC) predicts that the data-related hardware, software, and services are expected to grow at the rate of eleven percent by the year two thousand twenty.
5. Our horizons will broaden by studying big data
The fun investment of our time is studying big data. Our analytical and reasoning skills improve by studying big data because the domain of big data is full of puzzles to solve.
The applications of big data are spread out in several areas and domains. Some of the domains and areas where big data is applicable are:
The universities have an ocean of data, and analytics and data visualizations have been used to draw patterns of data related to students' information in the universities.
The reader must have knowledge of the GNU or Linux operating system, programming language proficiency like Java, Scala or Python in order to learn Big Data.
Beginners can refer to this tutorial to understand Big Data basics. This tutorial is helpful for people who want to pursue a career in the field of Big Data. This tutorial is good learning for all other readers.