18 Free Exploratory Data Analysis Tools For People who don’t code so well

avcontentteam 05 Jul, 2020 • 10 min read


  • A coding background is not mandatory for data analysis and predictive modelling
  • Plenty of open source and proprietary tools exist which automate the steps of predictive modelling like data cleaning, data visualization, etc
  • Some of them are also quite popular like Excel, Tableau, Qlikview, KNIME , Weka and many more



Some of these tools are even better than programming (R, Python, SAS) tools.

All of us are born with special talents. It’s just a matter of time until we discover it and start believing in ourselves. We all have limitations, but should we stop there? No.

When I started coding in R, I struggled. Sometimes a lot more than one can ever think! Because I had never ever coded even <Hello World> in my entire life.  My situation was similar to a guy who didn’t know swimming but was manhandled into deep ocean, who somehow saved himself from drowning but ended up gulping lot of salty water.

Now when I look back, I laugh at myself. Do you know why? Because, I could have chosen one of several non-coding tools available for data analysis, and could’ve avoided the suffering.

Data exploration is an inevitable part of predictive modeling. You can’t make predictions unless you know what happened in the past. The most important skill to master data exploration is ‘curiosity’, which is free of cost yet isn’t owned by everyone.

I have written this article to help you acknowledge various free tools available for exploratory data analysis. Now a days, ample of tools are available in the market which are free & quite interesting to work with. These tools doesn’t require you to code explicitly but simple drag – drop clicks do the job.


List of  Non Programming Tools

1. Excel / SpreadsheetExcel, data analytics

If you are transitioning into data science or have already survived for years, you would know, even after countless years, excel remains an indispensable part of analytics industry. Even today, most of the problems faced in analytics projects are solved using this software. With larger than ever community support, tutorials, free resources, learning this tool has become quite easier.

It supports all the important features like summarizing data, visualizing data, data wrangling etc. which are powerful enough to inspect data from all possible angles. No matter how many tools you know, excel must feature in your armory. Though, Microsoft excel is paid but you can still try various other spreadsheet tools like open office, google docs, which are certainly worth a try!

Free Download: Click Here


2. Trifactatrifacta, data cleaning

Trifacta’s Wrangler tool is challenging the traditional methods of data cleaning and manipulation. Since Excel possess limitations on data size, this tool has no such boundaries and you can securely work on big data sets. This tool has incredible features such as chart recommendations, inbuilt algorithms, analysis insights using which you can generate reports in no time. It’s an intelligent tool focused on solving business problems faster, thereby allowing us to be more productive at data related exercises.

Availability of such open source tools make us feel more confident and supportive, also that there are good people around the world who are working extremely hard to make our lives better.

Free Download: Click Here


3. Rapid Minerrapid miner, machine learning

This tool emerged as a leader in 2016 Gartner Magic Quadrant for Advanced Analytics. Yes, it’s more than a data cleaning tool. It extends its expertise in building machine learning models. Yes, it comprises all the ML algorithms which we use frequently. Not just a GUI, it also extends support to people using Python & R for model building.

It continues to fascinate people around the world with its remarkable capabilities. Above all, it claims to provide analytics experience at lightning fast level. Their product line has several products built for big data, visualizations, model deployment, some of which (enterprise) include a subscription fee. In short, we can say it’s a complete tool for any business which requires performing all tasks from data loading to model deployment.

Free Download: Click Here


4. Rattle GUI rattle, R

If you tried using R, but couldn’t get a knack of what’s going in, Rattle should be your first choice. This GUI is built on R and gets launched by typing install.packages("rattle") followed by library(rattle) then rattle() in R. Therefore, to use Rattle you must install R. It’s also more than just data mining tool. Rattle supports various ML algorithms such as Tree, SVM, Boosting, Neural Net, Survival, Linear models etc.

It’s being widely used these days. According to CRAN, Rattle is being installed 10000 times every month. It provides enough options to explore, transform and model data in just a few clicks. However, it has fewer options than SPSS for statistical analysis. Although, SPSS is a paid tool while Rattle is free of cost.

Free Download: Click Here


5. Qlikviewqlikview, business intelligence

Qlikview is one of the most popular tools in the business intelligence industry around the world. Deriving business insights and presenting it in an awesome manner, is what this tool does. With it’s state of the art visualization capabilities, you’d be amazed by the amount of control you get while working on data. It has an inbuilt recommendation engine to update you from time to time about the best visualization methods while working on data sets.

However, it is not a statistical software. Qlikview is incredible at exploring data, trends, insights but it can’t prove anything statistically. In that case, you might want to look at other softwares.

Free Download: Click Here


6. Weka weka, machine learning

An advantage of using Weka is that it is easy to learn. Being a machine learning tool, its interface is intuitive enough for you to get the job done quickly. It provides options for data preprocessing, classification, regression, clustering, association rules and visualization. Most of the steps you think of while model building can be achieved using Weka. It is built on Java.

Initially, it was designed for research purposes at University of Wakaito, but later it got accepted by more and more people around the world. However, over time I haven’t seen an enthusiastic Weka community like that of R and Python. The tutorial listed below should help you more.

Free Tutorial: Click Here


7. KNIME knime, machine learning, data visualization

Similar to RapidMiner, KNIME offers an open source analytics platform for analyzing data, which can later be deployed, scaled using other supportive KNIME products. This tool has an abundance of features on data blending and visualization, and advanced machine learning algorithms. Yes, using this tool you can build models as well. Although, there hasn’t been enough talk about this tool, but considering its state of the art design, I think it will soon come under much needed limelight.

Moreover, quick training lessons are available on their website to get you started with this tool right now.

Free Download: Click Here


8. Orange orange, machine learning, data cleaning

As cool as its sounds, this tool is designed to produce interactive data visualizations and data mining tasks. There are enough youtube tutorials to learn this tool. It has an extensive library of data mining tasks which includes all classification, regression, clustering methods. Along with this, the versatile visualizations which get formed during data analysis allow us to understand the data more closely.

To build any model, you’ll be required  to create a flowchart. This is interesting as it would help us further understand the exact procedure of data mining tasks.

Free Download: Click Here


9. Tableau Publictableau, data visualization

Tableau is a data visualization software. We can say, tableau and qlikview are the most powerful sharks in the business intelligence ocean. The comparison of superiority is never ending. It’s a fast visualization software which let’s you explore data, every observation using various possible charts. It’s intelligent algorithms figure out by self about the type of data, best method available etc.

If you want to understand data in real time, tableau can get the job done. In a way, tableau imparts a colorful life to data and let’s us share our work with others.

Free Download: Click Here


10. Data Wrapper datawrapper, business intelligence, data visualization

It’s a lightning fast visualization software. Next time, when someone in your team gets assigned BI work, and he/she has no clue what to do, this software is a considerable option. It’s visualization bucket comprises of line chart, bar chart, column chart, pie chart, stacked bar chart and maps. So, it’s a basic software and can’t be compared with giants like tableau and qlikview. This tool is browser enabled and doesn’t require any software installation.


11. Data Science Studio (DSS)

ikuIt is a powerful tool designed to connect technology, business and data. It is available in two segments: Coding & Non-Coding. It’s a complete package for any organization which aims to develop, build, deploy and scale models on network. DSS is also powerful enough to create smart data applications to solve real world problems. It comprises of features which facilitates team integration on projects. Among all features, the most interesting part is, you can reproduce your work in DSS as every action in the system is versioned through an integrated GIT repository.

Free Download: Click Here


12. OpenRefinerefine

It started as Google Refine but looks like google plummeted this project due to reasons unclear. However, this tool is still available renamed as Open Refine. Among the generous list of open source tools, openrefine specializes in messy data; cleaning, transforming and shaping it for predictive modeling purposes. As an interesting fact, during model building, 80% time of an analyst is spent in data cleaning. Sounds unpleasant, but it’s a fact. Using openrefine, analysts can not only save their time, but put it to use for productive work.

Free Download: Click Here


13. Talendtalend

Decision making these days is largely driven by data. Managers & professionals no longer take gut-based decisions. They require a tool which can help them quickly. Talend can help them to explore data and support their decision making. Precisely, it’s a data collaboration tool capable of clean, transform and visualize data.

Moreover, it also offers an interesting automation feature where you can save and redo your previous task on a new data set. This feature is unique and haven’t been found in many tools. Also, it makes auto discovery, provides smart suggestion to the user for enhanced data analysis.

Free Download: Click Here


14. Data Preparator data preparator, data cleaning

This tool is built on Java to assist us in data exploration, cleaning and analysis. It includes various inbuilt packages for discretization, numeration, scaling, attribute selection, missing values, outliers, statistics, visualization, balancing, sampling, row selection, and several other tasks. It’s GUI is intuitive and simple to understand. Once you start working on it, I’m sure you wouldn’t take lot of time to figure out how to work.

A unique advantage of this tool is, the data set used for analysis doesn’t get stored in computer memory. This means you can work on large data sets without having any speed or memory troubles.

Free Download: Click Here


15. DataCracker  datacracker, messy data, survey data

It’s a data analysis software which specializes on survey data. Many companies do survey but they struggle to analyze it statistically. Survey data are never clean. It comprises of multiple missing & inappropriate values. This tool reduces our agony and enhances our experience of working on messy data. This tool is designed such that it can load data from all major internet survey programs like surveymonkey, survey gizmo etc. There are several interactive features which helps to understand data better.

Free Download: Click Here


16. Data Applied data_applied, data visualization, data mining

This powerful interactive tool is designed to build, share, design data analysis reports. Creating visualization on large data sets can sometimes be troublesome. But this tool is robust in visualizing large amounts of data using tree maps. Like all other tools above, it has feature for data transformation, statistical analysis, detecting anomalies etc. All in all, it’s a multi usage data mining tool capable of of automatically extracting valuable knowledge (signal) from the raw data. You’d be amazed to see that such non-programming tools are no less than R or Python for data analysis.

Free Download: Click Here


17.  Tanagra Project tanagra

You might not like it because of its old fashioned UI, but this free data mining software is designed to build machine learning models. Tanagra project started as a free software for academic and research purposes. Being an open source project, it provides you enough space to devise your own algorithm and contribute.

Along with supervised learning algorithms, it is enabled with paradigms such as clustering, factorial analysis, parametric and nonparametric statistics, association rule, feature selection and construction algorithms etc. Some of its limitations include  unavailability of wide set of data sources, direct access to datawarehouses and databases, data cleansing, interactive utilization etc.

Free Download: Click Here


18. H2oh2o, machine learning

H2o is one of the most popular software in analytics industry today. In few years, this organization has succeeded in evangelizing the analytics community around the world. With this open source software, they bring lighting fast analytics experience, which is further extended using API for programming languages. Not just data analysis, but you can build advanced machine learning models in no time. The community support is great, hence learning this tool isn’t a worry. If you live in US, chances are they would be organizing a meetup nearby you. Do drop by!

Free Download: Click Here


Bonus Additions:

In addition to the awesome tools above, I also found some more tools which I thought you might be interested to look at. However, these tools aren’t free but you can still avail them for trial:

  1. Data Kleenr
  2. Data Ladder
  3. Data Cleaner
  4. WinPure


End Notes

Once you start working on these tools (your choice), you’d understand that knowing programming for predictive modeling isn’t much advantageous. You can accomplish the same thing with these open source tools. Therefore, until now, if you were get disappointed at your lack of coding prowess, now is the time you channelize your enthusiasm on these tools. You may be interested to check 19 Data Science Tools for Non Coders.

The only limitation I see with these tools (some of them) is, lack of community support. Except few tools, several of them don’t have a community to seek help and suggestions. Still, it’s worth a try!

Did you like reading this article? Have you worked on any of the tools listed above? Which one do you think is the most versatile? Drop your suggestions / opinions in the comments below.

Got expertise in Business Intelligence  / Machine Learning / Big Data / Data Science? Showcase your knowledge and help Analytics Vidhya community by posting your blog.

avcontentteam 05 Jul 2020

Frequently Asked Questions

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Responses From Readers


Sabrina 23 Sep, 2016

Manish, I enjoy your articles a lot, comprehensive list and it would make life so much easier for non coders? Great job!

Shantala 23 Sep, 2016

Very Informative. I will try Rattle GUI in R. Thanks for the information. Keep posting....

Sunil Kappal
Sunil Kappal 23 Sep, 2016

Great article, I believe BGML is another one to lookout for as it is picking up pretty good pace with analysts and data scientists. The awesome thing about this tool is that it lets you download the algorithm as a code which can be used directly for predictions.Just thought of sharing it !!!

Gianni 23 Sep, 2016

Thank you Manish ! Good job.

Herman 23 Sep, 2016

Brilliant article. Thank you.

Mehul Shah
Mehul Shah 23 Sep, 2016

Thank you Manish for the nice and informative article for individuals like me who are not from coding background.

Pratima Joshi
Pratima Joshi 23 Sep, 2016

Hello Manish, More than any of the above mentioned tools, I found Microsoft Azure ML studio very useful, user-friendly and easy to learn. It is free, cloud based and has support for R and Python.

Yvette 23 Sep, 2016

Thank you for the article, Manish. I have Tableau Desktop, but I am always keeping my eye on what tools are available. I enjoyed the article.

RRD 23 Sep, 2016

The section on DataWrapper is missing a link. Thanks for this excellent article.

Anshul solanki
Anshul solanki 23 Sep, 2016

I was wondering if we have similar kind of tools to do exploration of data in text format, specifically for NLP related problems.

Omesaad 24 Sep, 2016

Thanks Manish I wonder what about Nvivo and spss ? Are they involved?

Hari Galla
Hari Galla 28 Sep, 2016

Thank you Manish! Lot of information about tools available

Ramdas 30 Sep, 2016

Thank you manish, very informative article as always, will check out the trifacta tool.Ramdas

Edmund Laugasson
Edmund Laugasson 04 Oct, 2016

Apache OpenOffice is not developed actively but LibreOffice is a good reincarnation and contains already several data analysis tools - https://help.libreoffice.org/Calc/Data_Statistics_in_Calc

joshua bryant
joshua bryant 16 Dec, 2016

hi i think this is a great website

Stewart 28 May, 2017

Thanks a lot. Love it.

David 02 Jun, 2017

Nice list, but the lack of Power BI here is surprising, They are leaders in self service BI according to Gartner - ahead of Qlik, Tableau and the rest, and the free version is not a time limited trial but genuinely free.

Ravi 28 Jun, 2017

There are few updation required in this article. SAS has also launched few tools which did not require any coding. Also You did not mention about tablaue.

Jeffery 10 Jul, 2017

Skype has established its online-centered customer beta for the entire world, following establishing it generally inside the U.S. and You.K. before this 30 days. Skype for Web also now supports Linux and Chromebook for instant online messaging conversation (no video and voice but, those call for a connect-in installing).The expansion of the beta adds support for a longer list of spoken languages to aid bolster that global usability

Amit Jain
Amit Jain 10 Jul, 2017

I am working on image classification problems. Is there any tool which can generate visualisation in 3d or 2d, showing spread of images, Annotating their predicted class. Each image being spatially distance from each other on the basis of confidence factor.

Thomas 13 Jul, 2017

This is a great list. For non analitics experts there is JetPackData.com which is very fast and flexible.

Kanohi 21 Jul, 2017

We suggest to include the curios.IT data exploration software for iPad and Windows 10 in this list (Disclaimer: we are the authors of this app)

Shiju 26 Jul, 2017

Thanks team, this is really helpful. Trying out Tableau

Anil K. Gupta
Anil K. Gupta 23 Aug, 2017


Tha Masta
Tha Masta 19 Sep, 2017

Yoyoyo this article was sizzling yu fel me, could've dun with a shot of grammarly tho, peace bigtoebigmonayy out

qasim 27 Sep, 2017

any recommended tool for analysing non ethical data for the data set??

Laura Wyss
Laura Wyss 01 Nov, 2017

Hey,Nice write up!!! But it would be great if you add one more tool in this list! Windsor.ai . Windsor is a very useful business intelligence tool that enable an organisation to visually analyse its data to make profitable business related decisions. It helped me a lot in making my organisation's data more informative and valuable.

Vishwajeet Singh
Vishwajeet Singh 08 Nov, 2017

Bro can you tell some tool as add on for SAS programming. Please help me with this

James Lucas
James Lucas 18 May, 2018

Great list. There is one I would like to add that I used pursuing my MS in Predictive Analytics. That tool is "Exploratory". It uses R. Just do a google search on "Exploratory R" and you should get a hit. There are videos to help you learn and in some spots, you can see the code it generates in dplyr.Good Coding!j-

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