Large corporations like Amazon and Apple utilize something called Big Data Technology in our daily lives. They use it to help them with such tasks as monitoring sales, handling delivery, and informing them what occurs in the future. Big data assists companies in making sense of large quantities of data. There are two main kinds of big data tools. These tools are grouped into four major parts that help collect, store, process, and analyze large amounts of data.
What is big data technology?
Big Data Technology refers to employing unique computer equipment to process a lot of data. The equipment makes the data valuable for companies. It verifies the data, puts it in order, and discovers valuable facts. Big data is frequently combined with new technologies such as Machine Learning (ML), Artificial Intelligence (AI), and the Internet of Things (IoT).
Where is big data applied?
Big data is applied in numerous areas. Some of them include:
• Healthcare: It helps doctors view patient information to create better treatment strategies and identify disease outbreaks in a timely way.
• Finance: It finds strange activity that might be fraud and helps banks group customers by needs.
• E-Commerce: Big data informs consumers about products depending on their preferences. Education personalizes learning and keeps an eye on how students are doing.
• Retail: Retailers use big data to know what customers require, track products, and select better prices.
Types of Big Data Technology
There are two principal types:
1. Big Data Technology in Practice
This category uses information that people use every day. Some of them are:
- Examples of raw data include social media posts from sites like Facebook and Instagram, or when someone books a movie or flight ticket online.
- This kind of data hasn’t been changed or organized yet. It’s called unprocessed data, and it’s the very first step in working with big data.
- Later, other tools take this raw data and help turn it into smart ideas and decisions.
2. Big Data Analysis Technology
This type is sophisticated. It examines the raw data to allow a company to make important decisions. For example, it can help a company decide on what product to sell more or where to establish a new shop. It creates valuable reports from past data.
Top Big Data Technologies You Need to Know in 2025
Big data is a way to collect and study huge amounts of information. It helps people and businesses understand patterns, make better choices, and solve problems by looking at lots of data all at once. Companies use it to make better decisions, get things done quicker, and treat people better.
10 most popular big data tools in 2025 are:
1. Apache Hadoop
Apache Hadoop is free software that assists in the storage and processing of large amounts of data across multiple computers. It divides large jobs into little pieces and runs them simultaneously. This makes processing large data quicker and simpler even when it's disorganized.
2. Apache Spark
Apache Spark is very fast with big data. It can do things in memory, so it never has to refer back to the hard drive. Spark has support in a range of languages such as Python and Java. It's utilized for real-time data, machine learning, and big reports.
3. Apache Kafka
Apache Kafka is software utilized with real-time information, like messages or updates. It facilitates the transfer of data rapidly from one point to another. It is utilized mostly for applications concerning the processing of information in real time, like news feeds or online gaming.
4. Apache Flink
Apache Flink is a tool that helps study both live data happening now and old data from the past. It is fast and can process a lot of data simultaneously. It is employed in applications where things have to be monitored all the time, such as traffic information or current sports scores.
5. Google BigQuery
Google BigQuery is a service that helps you ask questions (in SQL) about large collections of data. It is cloud-based, so you don't have to install it.
6. Amazon Redshift
Amazon Redshift helps businesses look at large amounts of data using easy-to-use tools. It stores the data in intelligent ways so that it responds quickly. It can be easily integrated with other Amazon tools and is utilized to create business reports and data graphs.
7. Snowflake
Snowflake is a cloud platform used to store and analyze data. It can scale quickly as and when required and can be coupled with other applications. It can store any kind of data and is simple for teams to collaborate and query the data.
8. Databricks
Databricks is an Apache Spark-based collaborative data working tool that is used for machine learning and big data applications. It operates on notebooks in which a user can write and test code in order to analyze data.
9. MongoDB
MongoDB is a database that keeps data in a flexible format, like JSON. It is simple to modify and can expand as your data grows. It will be suitable for apps that are similar to a game, website, or something that needs current information.
10. Apache Cassandra
Cassandra is a database that stores a large amount of data and has it safe even if part of it crashes It distributes data evenly across many computers to make sure nothing is lost. It is suitable for applications such as online purchases or IoT where large amounts of data come in quickly.
How to obtain Big Data certification?
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The 10 top-paying certifications to target in 2025 are:
Conclusion
Big Data is revolutionizing how we live and work. To keep up, it is worth becoming acquainted with these new tools.
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