Data is the new currency. Embrace this reality or be ready to be lost in oblivion in this digital world. But why the whole new world is putting so much influence on data analytics tools. Because new-age customers want personalized, reliable, and durable products and services at the time and the exact place.
Fortunately, it is possible because of the tons of quantified data being available by the billions of connected devices out there. Now it comes to the unfortunate part of data. Data is like barren soil until it gets unearthly or analyzed with designated data analytics tools. But choosing the right big data analytical tool is always challenging, as no tool is perfect for every task.
This write will underline the best big data analytics tools and their key features based on their performance and usability.
“ Information is the oil of the 21st century, and analytics is the combustion engine. ” – Peter Sondergaard
Have a look at the top 10 data analytics tools and analytics:
1.Xplenty
Pricing Model: It comes with a free trial for 7 days with some limited features. One has to subscribe to access the entire features.
Xplenty is known for its data integration, ETL, and an ELT platform that can combine multiple data sources.
Talking about building data pipelines, then Xplenty is a perfect tool. The platform comes with cloud compatibility so that it can integrate, process, and prepare data for analytics on the cloud.
It could be beneficial for multiple purposes like managing sales, marketing, customer support, and more.
Have a look at its attributes:
- It can centralize all the sales metrics, manage CRM and process all the customer data to deliver actionable insights.
- When it is integrated with the customer support solution, it can equip businesses with the informed business solutions, and allow them to automate upselling & cross-selling.
- Design and automate marketing campaigns and strategies
- It can be integrated with the current legacy systems as it comes with features like data transparency, and easy migration.
2. RapidMiner
Pricing model: It comes with a free trial for 30 days with some features. RapidMiner as a best data analytics tools and features multiple user abilities and has a subscription model to unlock all the features.
It is based on predictive modelling and comes with a complete life cycle of the product. Plus it comes with functionalities like data preparation, model building, validation, and deployment. It also delivers a comprehensive graphical user interface.
Have a look at its attributes:
- It can prepare, visualize data and deliver a statistical representation of it.
- It servers has central repositories to fast processing
- It comes with analytical ability for informed insights
- Like XPlenty, it is cloud-based repository
3. Data Robot
A perfect for automated machine learning. A professional tool and a good fit for professionals among all classes, data architects, engineers, and other IT professionals.
Have a look at its features:
- Easy deployment in organizations
- Inbuilt Python SDK and APIs
- Parallel processing
Website: Datarobot
4. Apache Hadoop
Price: Available for free
Another open-source framework created by using Apache Hadoop. It can analytically handle distributed data across multiple data clusters.
Have a look at some of its features:
- High scalability
- Debugging can be detected and handled at the application
- Multiple modules of Hadoop
Website: Apache Hadoop
5. Trifacta
Pricing Model: It comes with three pricing plans: Wrangler, Wrangler Pro, and Wrangler Enterprise. One can get a Wrangler plan for free, while the other two come with a paid subscription.
Trifacta as a top data analytics tool can be used by individuals, teams, and organizations for data wrangling and data preparation.
Have a look at its features:
- For data preparation, it is self-serving platform
- It can be used on different levels
Website: Trifacta
6. Altery
Pricing Model: Alteryx Designer is available for $5195 per user per year and its server is available for $58500 for year. You have to subscribe to access other features.
The best among data analytics tools is to discover and analyze the data. It provides insights from any amount of data through its analytical ability
Have a look at its feature:
- It discover the data and collaborate it across various layers
- It effectively manages multiple users and data from various platforms
- It can embed R, Python, and Alterteryx models together
Website: Alteryx Designer
7. KNIME
Pricing Model: It is available for free.
It is especially customized for the data scientists to assist them in blending and analyzing different data sets. Use any tool you want and expand its capabilities.
Have a look at some of its features:
- Useful for repetitive sets of data
- It can work with Apache and Big Data
- It can work with multiple sets of data and platforms
Website: KNIME
8. Excel
Pricing Model: It comes with three different pricing models. For personal use, for office use, and a third plan for both purposes.
A basic but effective tool for data analysis. Even beginners can use it for basic purposes and command it by the time.
Have a look at some of its features:
- It effectively organize and summarize the data
- It comes with multiple formatting features
Website: Excel
9. Java
Pricing Model: Free with all the libraries
It is considered as an object-oriented programming language. It comes with multi-threaded features with platform-independent ability.
Have a look at its features:
- It comes with multiple tools and libraries for data science
- Supports large data science projects with Lambdas
- Scala support
Website: Java
10. Python
Among open-source data analytics tools, it comes with a large standard library, Python is considered as a good fit for beginners. It is object-orientated, dynamic, and has in-bulilt procedures.
Have a look at its features:
- It is free and comes with many useful packages
- Free libraries for data analysis
- Easy coding and debugging
Website: Python
A Road to Conclusion
This write-up has encircled the top 10 tools used by data analysts, architects, scientists, and other professionals. Each tool has some specific attribute that makes it a perfect fit for a specific task. So choose wisely as per your business requirement, type of data, volume of data, expertise in analytical thinking.
