TOP BIG DATA TECHNOLOGIES TO FOCUS ON :
HADOOP
The Hadoop ecosystem is an open-source framework with many products dedicated to storing and analyzing big data. For example, some of the more popular products include MapReduce for big data processing, Spark for in-memory data flow.
BIG DATA PROGRAMMING LANGUAGES
Python – Python is particularly useful with machine learning and data analysis.
R – This open-source language is widely used for big data visualization and statistical analysis, it’s more used by data miners and scientists for deeper analytical tasks.
Java – This programming language is great for businesses that regularly work with big data.
Scala – This language is part of the Java Virtual Machine ecosystem, and earned its name from being highly scalable.
NoSQL DATABASES
Unstructured data has no pre-defined structure. Images, audio, videos, webpage text, and more multimedia are common examples of unstructured data. This type of data cannot be worked using conventional methods, which is why NoSQL databases are on the rise.
DATA LAKES
Data lakes are essentially the opposite of data warehouses, which make use of mostly structured data. Data lakes are also much more scalable because of its lack of required structured, making it a more optimal candidate for big data.
ADVANCED ANALYTICS
Both predictive and prescriptive analytics are types of data analytics that will gain in prominence each passing year. These are considered advanced analytics that will be key for providing insight into big data.
