Big Data Tools You Need To Know In 2021

By Author: Nikita Vasiliev
Total Articles: 2
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Big Data and Five Best Analytics Tools In 2021
A decade ago global data started to boom, promoting business opportunities along with improved customer experience. Today, Big Data still keeps its foot down on a global arena and shows no signs of abating. The lion’s share of it is collected via the Internet, whereas IoT-enabled devices and sensors account for the other part. Besides, the growing number of virtual online offices is another major factor in driving growth.
With that being said, Big Data is now motivating employees to recruit experts in big data consulting and people well-versed in analytics tools. Company leaders are on the lookout for employees who are competent in their skill sets and demonstrate talent and cognitive abilities that would become valuable assets for the company's niche responsibilities. The once-coveted skills have now sunk into oblivion and if there’s something hot today, it’s Big Data analytics.
Anyway, what is Big Data?
We constantly produce a mind-boggling amount of data via social media, public transport, and GPS. But it goes way beyond that. Daily we upload 95 ...
... million pictures and videos, 340 million tweets, and 1 billion documents. In total, we produce 2.5 quintillion bytes a day and that's a lot of zeros. We call that Big Data. So we can tell for sure that Big Data has permeated almost every niche today and serves as a major motive power behind the companies' success. But can you tell exactly what Big Data is? I doubt that.
The term Big Data has been in the game for not so long. Thus, Google Trends demonstrates a search interest in the use of this word combination since 2011. Today, the term Big Data is on heavy rotation, being one of the most overused corporate word combinations. This overused term with an underused value has been often associated with:
the data that is more than 100Gb (500Gb, 1TB, whatever you like)
the data bits that can't be processed with Excel.
the information that can't be processed by a single computer.
And even this:
Big Data is any data at all.
Big Data doesn't exist, it is a fictional character that marketers use to trick companies into spending money.
So what is this concept, anyway?
Essentially, Big Data is a series of approaches, tools, and methods used for processing structured and unstructured data of huge volumes and significant diversity to produce human-perceived results that prove effective in continuous growth. Big Data serves as an alternative to traditional database management systems and solutions within the Business Intelligence framework.
Thus, Big Data doesn’t refer to a specific amount of data or even the data itself. Instead, the term stands for methods of data processing, which allow for the distributed information processing. These methods can be applied both to huge data sets (such as the content of all pages on the Internet) and to small ones (such as the content of this article).
Big data is essential for global businesses since more data results in more accurate analysis, which, in its turn, accounts for better decision making, enhanced operational efficiencies, and cost reductions.
The three V’s of Big Data
When we bring up Big Data, we cannot but mention the three key concepts that describe the notion: volume, velocity, and variety. These three vectors allow us to understand how big data compares favorably with old school data management.
Volume
The amount of data is important. With Big Data, you’ll have to crunch massive amounts of low-density, unstructured data. And the size of the data is the most important indicator in determining the possible extractable value. Clickstreams, system logs, and stream processing systems are what usually generate massive volumes of big data.
Variety
Long gone are those days when data was collected from one place and returned in a unified format. Today, data comes in all shapes, forms, and sizes, including video, text, pdf, tech, and graphics. Therefore, Big Data provides opportunities for leveraging new and existing data and coming up with brand new ways of capturing future data.
Velocity
Velocity measures how fast the data is coming in and acted upon. Some data bits may pop up in real-time, some may be sent in batches. Since most platforms process the incoming data at a different speed, it’s important not to turbo-speed the decision without having all the information.
Top Ten Big Data Tools
Big Data Analytics software is broadly implemented for effective data processing and achieving a competitive edge in the market. These software analytical tools assist in tracking current market changes, customer needs, and other valuable information. With this in mind, let’s go over the most popular Big Data analytics tools in 2021.
Hadoop
Apache Hadoop sits comfortably on top of our list. Big Data is sort of incomplete without Hadoop and expert data scientists are well aware of that.
Hadoop is a 100% open-source set of utilities, libraries, and a framework for developing and executing distributed programs running on clusters of hundreds or thousands of nodes. This foundational Big Data storage and processing technology is a top-level project of the Apache Software Foundation.
Hadoop consists of four parts:
Hadoop Distributed File System: Also known as HDFS, it’s a distributed file system designed to run on commodity hardware.
MapReduce: a programming pattern used to access big data stored in the HDFS.
YARN: technology designed for cluster management.
Libraries: To help other modules to work with Hadoop.
X-plenty
This cloud-based scalable platform is among the forward-runners in its niche, offering cloud-based ETL solutions and data pipeline tools. Boasting a user-friendly interface and powerful transformations, Xplenty's transparent pricing structure makes it a standout among its competitors. Among the main features of X-plenty are:
Easy data transformations
REST API
Destination flexibility
Superior Security
Diverse data source and destination options
Customer-centric approach
Spark
Today, this powerful open-source analytics tool is a staple in companies' toolbox, including Amazon, eBay, and Yahoo!. Apache Spark is a lightning-fast cluster computing technology designed for fast computing. It is based on Hadoop MapReduce and extends the MapReduce model to leverage it for other types of computing, including interactive queries and streaming processing. The main feature of Spark is in-memory cluster computing, which increases application processing speed.
Spark is created for a wide range of workloads such as batch applications, iterative algorithms, interactive queries, and streaming. This makes it a perfect option for both amateur use and professional data processing aimed at a huge volume.
Cassandra
If you are familiar with the NoSQL databases, you must’ve come across Cassandra. It is a free open-source NoSQL database, but it stores values in the form of key-value pairs. This tool is the perfect choice when you require scalability and high availability without sacrificing performance.
Due to its architectural features, Apache Cassandra has the following advantages:
Scalability and reliability due to the absence of a central server
Flexible data schema based on the combination of Column Families into the keyspace
High throughput, especially for write operations
Own SQL-like query language
Configurable consistency and replication support,
Automatic conflict resolution
Talend
Talend is an open-source analytics software that simplifies and streamlines big data integration. ETL simplifies turning raw data into information that can be used for actionable business intelligence (BI). The software boasts features like a cloud, big data, enterprise app integration, data quality, and master data management. It also hosts a unified repository to store and reuse the Metadata and checks the data quality.
Features:
Faster development and deployment
Less expense and free download

Future proof
Unified platform
Huge dedicated community
Overall, there is a wide range of Big Data tools that help store, analyze, report, and do a lot more with data. This software turns scarce data bits into powerful fuel that stimulates global business processes and facilitates knowledge-driven decision making.
The Bottom Line
The use of Big Data has once revolutionized the field of Information Technology. Today, companies harness valuable data pieces and implement Big Data tools to surpass their rivals. In the competitive market, both established businesses and newcomers enforce the strategies leaning on the crunched data to lock horns, trail the blaze, and capture value.
Big Data allows the organizations to identify new opportunities and brings into existence new types of companies that can combine and analyze industry data. Clean, relevant, and visual data then provides actionable insights into the products, optimizes business operations, and entails significant cost advantages.