You’re seeking to explore the best destinations for your next travel. You look for better travel destinations with lots of information to consume. Perhaps you’ve logged into your social media account, what do you see?

Do you see the advertisement of a travel destination popping up on your screen? Is your answer yes? If so, you need to know that smart digital assistants are already tracking your search providing the best information to make your dream come true.

This is where big data and data analytics tools come to play. These tools help you unfold the hidden world yet with the targeted information. As big data professionals, analyzing data is a crucial skill, especially to make informed business decisions. And for this, you will need expertise in learning the tools to assist data-driven decision-making processes. With multiple data analysis tools, it can get challenging for big data professionals to choose the right tool. Below are the top eight tools for you to choose from:

1. KNIME

KNIME also referred to as the Konstanz Information Miner is an open-source, free, integration and reporting data-analytics platform. The data analysis tool is a must-have skill set for someone looking to grow in a big data career. It is an ideal tool for users to leverage scripting languages like Python and R while developing data science apps. The best advantages of using KNIME includes multi-threaded data and in-memory processing. The drag and drop GUI of KNIME is easy and simple to use. As a beginner, you can easily analyze and model data using visual programming.

2. RapidMiner

RapidMiner emerged as a leader in the Gartner’s 2019 Magic Quadrant for data science and machine learning continuously for six years in a row.

Being one of the most popular data science platforms, it is now being used by more than 40,000 organizations worldwide. RapidMiner is more than just a data cleaning tool. Its expertise extends in building machine learning models while also supports data scientists or big data engineers using R and Python to build models.

RapidMiner provides more than 1500 algorithms and data functions. Besides this, this platform also provides great support for advanced analytics, integration with R and Python, and third-party machine learning libraries.

3. Sequentum Enterprise

Sequentum enterprise serves as one of the best tools used for advanced data extraction, especially for web crawling.

This tool facilitates testing, development, and production while making large scale data extractions. Sequentum was specially designed for organizations that completely relied on legal compliance and structure web data. Thus, users can easily debug and control crawlers by writing scripts or by using VB.NET, and C#.

In-depth knowledge regarding the latest tools and platforms is a must-have for professionals building a big data career.

Since the platform provides advanced features, the user is advised to have extensive knowledge of programming and data analysis.

4. Looker

Every organization is looking for new ways to get to the cloud. Looker offers the support of a multi-cloud strategy and is best suited for deployment methods and the use of multiple data sources. The best benefits this tool provides are features like advanced data visualization, analytics and management, and business intelligence. Looker can easily stay connected with a large set of databases along with Amazon Redshift and Snowflake.

5. OpenRefine

OpenRefine is an open-source data analysis tool formerly known as Google Refine. On completion of data cleaning, the dataset is further extended to the external web services. OpenRefine also supports multiple file formats for import and export purposes. The tool imports files like XML, JSON, CSV, TSV and further exports the data in readable formats like HTML table, Microsoft Excel, CSV, and TSV.

6. Lexalytics

The business intelligence platform called Lexalytics is best for organizations to better understand employees’ or customers’ experience with their products or services by leveraging text data. This platform helps gather information from multiple posts, comments, tweets and helps the big data analyst infer the most updated insight. The software identifies the feelings or attitudes of the user through the combined feature of machine learning, natural language processing, and text analytics.

7. NodeXL

The NodeXL tool is also known as the “MSPaint of Networks.” This tool composes of two versions – NodeXL Basic and NodeXL Pro.

The basic version is free and is an open-source tool. The basic version also allows data scientists to analyze and visualize network graphs in excel. While the pro version of NodeXL provides additional features such as sentiment analysis and AI-powered text.

NodeXL can be a preferred choice for analysts seeking to import data, represent data, or for graph visualization.

8. Talend

Talend allows professionals and managers to make better-informed decisions quickly. The tool helps in exploring the data and support them in decision making. Simply said, it is a data collaboration tool ideal for cleaning, transforming, and visualizing the data.

One of the best features includes saving and redoing your previous task on a new data set. This feature is unique and cannot be found in the other tools. Thus, allowing for auto-discovery and smart suggestion to the user to boost data analysis.