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10 Top Data Analysis Tools for 2021

By Simplilearn

10 Top Data Analysis Tools for 2021

While data is a necessary resource in business today, it’s also virtually useless in its raw form. There are zettabytes of data being generated every year now. Most of that data will be useful, but only through the work professionals with proper data analytics skills can do.

Companies that aren’t making business decisions based on insight gathered from data are already losing out to the competition in today’s commercial world.

It takes a qualified data analyst proficient in the latest data analysis tools to take that massive amount of data, glean what’s essential, prepare it in a form that’s easy for others to understand, and then create a plan of action.

But just like the data itself, there’s also a copious amount of data analytics tools at the analyst’s disposal. Depending on your needs, goals, and what types of data analysis you need to do, it’s worth learning about the various options you have.

Here is the list of top 10 data analysis tools that we will discuss in detail:

  1. Sequentum Enterprise
  2. Datapine
  3. Looker
  4. KNIME
  5. Lexalytics
  6. SAS Forecasting
  7. RapidMiner
  8. OpenRefine
  9. Talend
  10. NodeXL

 

Top Data Analysis Tools to Learn

Data analytics tools are applications and software used by data analysts to develop and perform the necessary analytical processes that help companies make better, more informed business decisions while lowering costs and increasing profits.

1. Sequentum Enterprise

Suppose you need an advanced data extraction tool for web crawling. In that case, Sequentum Enterprise is an excellent tool that enables development, testing, and production, geared towards large-scale web data extractions. Enterprise was designed with corporations that depend heavily on structured web data and legal compliance. Users can control and debug the crawler with C# or VB.NET, or they can write scripts.

Sequentum Enterprise offers advanced features that aren’t typically available in other solutions, such as the ability to monitor data extraction success criteria, legal compliance, and production failover.

However, this data analysis tool may be a bit overwhelming for those who only know the fundamentals of data analysis and programming. If you’re a beginner, you may want to hold off on using Sequentum Enterprise until you gain more career experience.

2. Datapine

Datapine delivers simple yet powerful analysis features for both beginners and advanced users alike. This popular business intelligence tool boasts a drag-and-drop interface, powerful predictive analysis features, and interactive dashboards and charts. It also features an advanced SQL mode that helps advanced users build their own queries. Datapine’s defining characteristics are speed and simplicity.

3. Looker

Cloud-based Looker provides an intuitive drag-and-drop interface that’s easy to use. It offers data analytics and management, business intelligence, and advanced visualization capabilities. The tool’s multi-cloud strategy supports the use of various data sources and deployment methods. Looker also easily connects with an array of databases, including Snowflake and Amazon Redshift. It has a built-in code editor that allows data analysts to modify generated models.

4. KNIME

This open-source data analysis tool enables users to leverage powerful scripting languages like R and Python to build data science apps. It provides in-memory processing, as well as multithreaded data processing. Its drag-and-drop GUI is simple to navigate and easy to learn for beginners and provides users with an excellent way to analyze and model data via visual programming.

5. Lexalytics

The Lexalytics Intelligence Platform is perfect for businesses that want to better understand their customers’ or employees’ experiences with their products and services by leveraging the power of text data. Lexalytics collects information from posts, tweets, and comments and helps analysts gain the best possible insights. The software helps identify attitudes and feelings through a combination of text analytics, machine learning, and natural language processing, and more. Professionals with can deploy Lexalytics in public, private, and hybrid cloud environments.

6. SAS Forecasting

Data analysts working on business solutions need to understand the potential variables involved and how events may unfold in the future. That’s where forecasting and data analytics tools come in. SAS Forecasting for Desktop offers a good selection of forecasting methods, including “what-if” analysis, event modeling, scenario planning, and hierarchical reconciliation. This powerful data analysis tool provides scalability and modeling, easy-to-use GUI, data preparation, and an event-modeling console.

7. RapidMiner

RapidMiner is a very popular data science platform used by over 40,000 organizations. It allows users to improve productivity through automated machine learning. It doesn’t require users to write code manually and provides built-in security controls. It also facilitates team collaboration and includes a visual workflow designer for Spark and Hadoop. It offers over 1500 algorithms and data functions, support for third-party machine learning libraries, integration with Python or R, and advanced analytics.

8. OpenRefine

If you’re looking for a free data cleaning and transformation tool, you can’t go wrong with OpenRefine. Formerly known as Google Refine, this open-source data analysis tool is highly secure. Once the data is cleaned, data analysts can extend the dataset to external web services. This software supports numerous file formats for importing and exporting purposes. You can import CSV, TSV, XML, RDF, JSON, Google Spreadsheets, and Google Fusion Tables, then export the data in TSV, CSV, HTML table — and Microsoft Excel.

If you’re searching through the top data analytics tools, check this out. OpenRefine is available in multiple languages and can be used easily by companies of all sizes.

9. Talend

ETL (short for extract, transform, load) is a popular data integration process, and Talend provides an excellent entry data analytics tool. This Java-based tool is used to collect and transform data through preparation, integration, and cloud pipeline design. Talend can efficiently process millions of data records and handle any size project. It features data preparation, big data integration, cloud pipeline designer, and Stitch Data Loader, covering an assortment of data management requirements for any sized organization.

10. NodeXL

Referred to as the “MSPaint of Networks,” this tool comes in two versions: NodeXL Basic and NodeXL Pro. The Basic version is a free, open-source tool that enables data scientists to visualize and analyze network graphs in Microsoft Excel. The Pro version offers additional features that extend to social media network data and AI-powered text and sentiment analysis capabilities. NodeXL is a good choice if you’re looking for data representation, data import, graph analysis, and graph visualization. It’s compatible with Microsoft Excel 2007, 2010, 2013, and 2016.

While this list is hardly exhaustive, it’s a good starting point. You may actually need to use a combination of different data analytics tools and techniques in some cases. One thing is clear, however: data science and data analysis are already essential practices for any business that wants to thrive in the modern world.