Top 10 Big Data Technologies You Must Know in 2021
Blog: Think Data Analytics Blog
Big data has many digitalized area and one of the most evolved area in big data is big data technologies. Big data has the new technology opportunities for optimize the business.
- Big data is a huge volume set of distinct and complex set of data from the new data sources.
- Big data is a massive amount of data with the types of structured data, unstructured data and semi structured data.
- Big data is the analysis of perception and leads to make better decisions and take moves on business by analyze the strategy of market.
Learn more about: Top Big Data Companies in USA
Characteristics of big data
- Big data characteristics are Volume, Velocity, Variety, and Veracity.
- Big data has many applications and some of the application is banking, transportation, telecommunications, healthcare, IT, retail and so on.
- Big data has many case studies and they are Wal – mart, QStream, T – Mobile, EBay, Delta, Basis, Aetna and so on.
Big Data Technologies We Must Know
- Big data technologies is used in the make use of software with share the data, store the data, mining the data, visualization of data and analytics of data with various types of data volume, variety of data, unreliable data and data velocity.
- There are many big data technologies are used in big data. Here we discuss about some of the big data technologies and they are
- Apache Hadoop
- Apache Spark
- R programming language
- Blockchain Technology
- Artificial intelligence
- Apache Cassandra
- Apache Flink
- Apache Kafka
- Data lakes
a) Apache Hadoop:
- Apache Hadoop is a popular and open source big data software (or framework) developed by the Apache software Foundation. Hadoop written in java and works on cross platform and it has the type of distributed file system of hadoop.
- Hadoop framework for quick process of set of data in separated and it stores huge volume of data with a cluster of machine or computer.
b) Apache Spark:
- Apache Spark is an another open source software like Hadoop, used to increase the speed of the process of data in hadoop and it’s more faster than the hadoop engine, map reduce. Spark is written in scala, java, SQL, python, c# and also works on Microsoft Windows, Linux and macos.
- NoSQL means Not only SQL or Not SQL. NoSQL is a non – relational database with the scale in horizontal. It works for huge set of distributed data with the effective performance.
- It has a dynamic schema with the unstructured data. NoSQL is work for the unstructured data like document, audio, message and so on. Some of the NoSQL example is mongodb and so on.
d) R programming language:
- R is an open source, free, supports multi – platform and it is a most popular programming language, which is used for envision, operate and analysis of set of huge data and also have best analysis for statistical data in big data.
e) Blockchain Technology:
- Blockchain Technology has stores the data of transaction in records depend on peer to peer network. It stores the data in structure of block and blocks are intermixing together into a sequence of chain. It is used to point out and preclude the transaction from risk or fraudulent activity.
- It is a digital records of data and it’s decentralized database of DLT (Distributed Ledger Technology).
f) Artificial intelligence:
- Artificial intelligence is used to create the machine has intelligent. It is a branch of computer science, the goal is to the computer will think like humans. It is used to make better decisions.
- It’s point out the optimum solution for the problem. It care about to increase the chance of success and not about its accuracy. Some of the artificial intelligence is chat bot, siri, Amazon alexa and so on.
g) Apache Cassandra:
- Apache Cassandra is a open source, free, separated, Nosql DBMS (database management system). It provides the huge amount of data with an efficient and effective performance of management.
- Apache Cassandra written in java and it is a cross platform and it’s type is NoSQL database. Some of the features are fault tolerance of replication, scalable and so on.
h) Apache Flink:
- Apache Flink is a open source with fully distributed of the specific framework of the stream and batch data processing of efficient performance and computation of cluster. It is more popular framework in upcoming years for the data stream process. It’s written in java and scala language with the cross platform and it’s type is the algorithm of machine learning, analysis of data and so on.
i) Apache Kafka:
- Apache Kafka is the more popular framework in upcoming years for stream data process and it is a open source software, which is developed by Apache Software Foundation. Its required the support of external distributed.
- Apache kafka is written in java and scala and its works on cross platform and also it’s type of process the stream, broke the data and so on.
j) Data Lakes:
- Data lakes are store in fresh format, raw structure of data with purpose is not determining and it has high accessibilities and fast revise.
- It has a massive volume of data can be collect and organized the set of data from various sources and stack in natural state. Compare with data warehouse, data lakes are same but storing the data is different data lakes stack in natural state where as data warehouse stacks in structure.
Big data technologies, evolving day to day in big data it’s gives new opportunities for companies to optimize their business in right way. Big data has many technologies, which is useful for securing the data, process, store, mining the data, analytics of the data for making better moves in business by the strategies of market analysis.
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