The collected data is of no use to the business until it is analyzed. Basic data analytics tools like MS Excel cannot process Big Data due to the excess volume and complex nature of data. Big Data needs tools designed explicitly for the purpose. Big Data Analytics is a type of advanced analytics where statistical algorithms, what-if models, and predictive analysis are used to identify the patterns, trends, and correlations between different elements. https://www.datatobiz.com/blog/best-big-data-tools/

1. C H E C K O U T T O D A Y !
Best Big Data Tools
15

2. What Are Big Data Tools?

3. Big Data tool is a software used to clean, format, and
process vast data in real-time. It is an analytical
system capable of understanding complicated
information and deriving actionable insights from it. Big
Data tools help enterprises make data-driven decisions
and increase returns.

4. The Best Tools for Big Data
Analytics

5. The HDFS (Hadoop Distributed File System) can store data in all
formats and structures in the same file system.
Hadoop is highly scalable software that delivers efficient results in a
single server and multiple servers.
The software allows for faster and flexible data processing.
It can be used for free under the Apache License.
Hadoop is robust and a perfect Big Data tool to process Big Data from
a cluster of devices.
Be careful to prevent excessive use of disk space due to data
redundancy.
Apache Hadoop is one of the best open-source Big Data analytics tools in
the market. It’s written in Java and is used to handle clustered file systems
through the MapReduce programming model. Hadoop is cross-platform
software used by more than half of the Fortune 50 companies.
1. Apache Hadoop

6. Storm can process one million 100-byte messages per second per node.
It is fast, reliable, and scalable.
Data processing is guaranteed with Apache Storm. Every unit of data is
processed at least once.
The processing will restart automatically on another node if the current
node dies.
Storm can run parallel calculations across thousands of computers.
It can be used for ETL, real-time processing, continuous computation, and
log processing.
Strom can be a little different to understand, though it is one of the
easiest software tools to use once deployed.
Apache Storm is another open-source Big Data tool that offers the best real-
time processing capabilities. The Storm has cross-platform abilities and
provides distributed stream processing. It’s written in Java and Clojure and is
fault-tolerant.
2. Apache Storm

7. Atlas.ti can be integrated with data for processing and analytics.
Export data across the devices and machines.
It is creates network diagrams and data visualizations in the desktop
versions.
Atlas.ti codes and analyzes huge amounts of transcripts/ notes/
research data.
It is easy to understand and use in an enterprise and provides full
support to the R&D department.
Atlas.ti is known as a comprehensive all-in-one software for research. It is
used to research markets, understand user experience, and help with
academic research and qualitative analytics. The software is available in
two versions- desktop for on-premises use and web version for cloud
applications.
3. Atlas.ti

8. Tableau is flexible, scalable, and works on multiple platforms, including
mobile devices.
Many Big Data consulting companies like DataToBiz are partners of
Tableau and offer offshore data analytics and visualization services.
There’s no need to code or use a programming language to work on
Tableau.
The templates are easy to use and can be customized to create reports in
countless formats.
The tool offers an array of features to bridge the gap between data and
employees/ management.
Tableau falls in the category of leading tools for Big Data visualization and is
available in three versions- Tableau Desktop, Tableau Server, and Tableau
Online for cloud solutions. The open-source version of the software is known
as Tableau Public. The data visualization tool works with data of all sizes and
formats and provides real-time reports through the interactive dashboard.
4. Tableau

9. The tool allows for linear scalability with an increase in data volume
and requirements.
Data replication is automated across numerous data centers in the
enterprise for fault tolerance.
It has a simple ring structure and can effortlessly handle huge loads of
data.
There’s no single point of failure when using Cassandra. Even when the
systems and data centers are down, you won’t lose the data.
Apache Cassandra is a free, open-source software that deals with vast
volumes of data on several servers connected to one another. The NoSQL
DBMS uses CQL (Cassandra Structure Language) to share information with
the databases in the enterprise. Low latency is one of the significant
advantages of using Cassandra.
5. Apache Cassandra

10. It comes with Java core and allows cross-platform integrations.
Rapidminer works with APIs and cloud systems just as effectively.
The tool allows you to choose multiple data processing methods to
analyze the data.
Choose between GUI or batch processing, depending on your
requirements.
Interactive dashboards and an easy interface make Rapidminer a
worthy Big Data tool even for remote analytics.
Rapidminer is an open-source Big Data analytics tool that SMEs and large
enterprises alike can use. It’s a perfect choice to use with data science
models, predictive analytics, and new data mining models in the business.
Rapidminer helps with data preparation, implementing machine learning,
and deploying models.
6. Rapidminer

11. It is one of the simple yet highly effective Big Data ETL tools (Extract
Transform Load tool).
It works with other systems and several languages through seamless
integration.
Manual and repetitive work is automated by using Knime. It saves time
and resources.
The tool is known for its stability and ability to organize workflows
within the enterprise.
Knime is Konstanz Information Miner, open source Big Data software used
for analytics, reporting, and data integration. The tool helps integrate
machine learning and data mining models. Knime is the best choice for
research, BI, CRM, etc. It has a rich algorithm set and is still easy to use in
the enterprise. It is a free tool that comes with GNU General Public License.
7. Knime

12. MongoDB has been designed to work with modern data applications.
It is a cost-effective tool with reliable features and services.
MongoDB is perfect for those who want Big Data analytical tools that
are easy to install, use, and maintain over time.
It is suitable to store structured and unstructured data and can be
quickly scaled to meet the increasing demands of the enterprise.
MongoDB is written in C, C++, and JavaScript. It is a NoSQL and document-
oriented database that works with multiple operating systems. It is a free
open-source Big Data tool that processes massive amounts of data and
develops file systems for storage.
8. MongoDB

13. It can help develop and train data models in the enterprise for Big
Data analytics.
It delivers real-time insights and reports that are used to monitor
and detect changes in the business.
Cloudera is a multi-cloud software app and delivers high
performance.
Data security is the biggest advantage of using this software tool.
It allows for a node-based subscription where you pay only for what
you use but can be slightly expensive as well.
If you’re looking for quick and secure data platforms, Cloudera is the
answer. Cloudera is free and open-source software that works with any
data environment and encompasses Apache Hadoop, Spark, Impala,
etc. Data collection, processing, managing, modeling, and distribution
are easily performed using Cloudera.
9. Cloudera

14. The software documents machine learning methodologies used in the
enterprise.
It supports the development and deployment of various ML models and
increases the speed of workflow.
The software is secure and scalable to suit the growing demands of the
enterprise.
Oracle Data Miner works with Big Data SQL to gather data from several
data sources, including Apache Hadoop.
Oracle Data Miner is used by data scientists for business and data
analytics. It provides the easy drag and drop feature to make changes to
the editor interface and customize the reports. The Big Data tool is an
extension of the Oracle SQL Developer and deals with graphical workflows.
10. Oracle Data Miner

15. TO CONTINUE YOUR READING, CLICK ON
THE BELOW LINK
https://www.datatobiz.com/blog/best-big-data-tools/