Learn About The Best Tools And Technologies For Big Data Analytics

• By Henny Jones
• 01-07-2021
• Technology

In the world of data, businesses must accumulate as much knowledge as possible about the different data solutions such as data science, big data, data analytics, business intelligence, and a lot more. Especially if yours is a business generating voluminous data, you can grab the opportunity to draw insights from this data to deliver excellence in your business and earn more revenues.

Today we will go in-depth about big data analytics and the various tools and techs related to it which you can incorporate into your business to get great results.

Big data analytics is an intricate process of evaluating big data to explore information such as hidden data patterns, market trends, customer interests, correlations, and many more to help you make impactful business decisions.

Data analytics, tools, and techs provide companies a way to examine datasets and collect new info. BI solutions respond to basic questions about company performance and workflow.

In comparison, big data analytics is an enhanced analytics tool extracting useful information by evaluating different big data sets. It involves complex applications such as statistical algorithms and predictive models enabled by analytics solutions.

Topics covered

- Importance of Big Data Analytics
- Big Data Analytics Tools in 2021
- Final Words

Importance of Big Data Analytics

Businesses can use big data analytics solutions to make data-driven decisions that bring better business-related results. These benefits might include new revenue opportunities, enhanced workflow efficiency, customer personalization, and impactful marketing.

A better understanding of consumer needs, sentiment, and behavior leading to improved marketing insights and give information for product development.

Enhanced, more informed risk management techniques that choose from voluminous sample sizes of data.

Quickly make more insightful decisions for impactful strategizing that can benefit and enhance the supply chain, workflows, and other strategic decision-making.

The new business process optimization leads to cost savings.

Also Read: How Artificial Intelligence Redefine the Banking Sector?

Big Data Analytics Tools in 2021

Several different tools and technologies are available to support big data analytics processes. Below are a few tools you should be aware of for your business success:

1. Xplenty

Xplenty is a cloud-based tool for implementing, evaluating, and preparing data bringing all data sources together. This is a complete toolkit to build no-code or low-code data pipelines, offering solutions for marketing and distribution.

Key features-

- It provides an elastic & tailored API component.
- You can implement intricate data preparation functions by using the sophisticated Xplenty language.
- Its cloud network is scalable and flexible.

2. Hadoop

Big data cannot really be complete with this fantastic tool. Hadoop is an open-source big data tool offering vast storage for all sorts of data. This tremendous tool never lets your hardware fail with its incredible processing power & capability.

Key features -

- Manages massive amounts of structured and unstructured data
- Super handy for R&D purposes
- Super scalable
- Moreover, its key strength lies in its HDFS controlling all data, JSON, videos, images, and text.

Also Read: How Amazon Used Big Data to Rule E-Commerce?

3. KNIME

This open-source tool is short for Konstanz Informative Miner. KNIME is used for data mining, BI, business reporting, integration, and data analytics. This analytic tool helps you evaluate and model data via visual programming. It can integrate multiple components for machine learning and data mining.

Key features -

- There are no stability problems.
- Several manual tasks are automated
- Operations are structured and highly functional.
- It is well-integrated with other languages and technologies.

4. R

This is one of the most all-inclusive big data analytics tools. R is open-source, free to use, and a versatile tool. Data miners and statisticians widely use it, and its use cases include data manipulation, visualization, analysis, and data processing.

Key features -

- In-built plotting commands creating matchless graphical elements.
- R programming language is best for statistical analysis and data reconfiguration.

5. MongoDB

This is one of the top open-source big data analytics tools to operate on dynamic datasets or datasets that are semi or unstructured. The top uses of this tool include data storage from CMS, mobile apps, product catalogs, etc. However, to use MongoDB, you must learn the system from scratch.

Key features -

- This tool is affordable and powerful.
- It supports multiple platforms and technologies.
- MongoDB is a super scalable and flexible NoSQL database management platform.
- It renders fault tolerance by making duplicate datasets.

6. Tableau

Tableau is one of the top-notch Big Data Analytics tools for data exploration and visualization. This tool offers multiple integrated solutions to help the world’s largest businesses understand and envision their data. It renders tailored dashboards in real-time and can handle all the data sizes.

Key features -

- Remarkable and fast support for connection with most databases
- Flawless data blending

Also Read: How Artificial intelligence Shape Healthcare Industry?

Final Words

These are the six robust tools that you should definitely be aware of if you want to employ big data analytics for your organization. If you are looking for a big data solutions company, we are right here. HData Systems has a team of the best data scientists and analysts to help you with your big data quest.