1. Best Big Data Analytics Tools

We will learn about Best Data Analytic Tools. Also, will study these Data Analysis Tools: Tableau Public, OpenRefine, KNIME, RapidMiner, Google Fusion Tables, NodeXL, Wolfram Alpha, Google Search Operators, Solver, Dataiku DSS with their uses, limitations, and description.

2. List of Big Data Analytics Tools

Data Analytics is the process of analysing datasets to draw results, on the basis of information they get. It is popular in commercial industries, scientists and researchers to make a more informed business decision and to verify theories, models and hypothesis.

These are the 10 Best Big Data Analytic Tools with their uses and limitations, which can help you to analyse the data. Let’s discuss them one by one:

Tableau Public

OpenRefine

KNIME

RapidMiner

Google Fusion Tables

NodeXL

Wolfram Alpha

Google Search Operators

Solver

Dataiku DSS

a. Tableau Public

i. What is Tableau Public – Big Data Analytics Tools

It is a simple and intuitive tool. As it offers intriguing insights through data visualization. Tableau Public’s million-row limit. As it’s easy to use fares better than most of the other players in the data analytics market.

With Tableau’s visuals, you can investigate a hypothesis. Also, explore the data, and cross-check your insights.

ii. Uses of Tableau Public

You can publish interactive data visualizations to the web for free.

No programming skills required.

Visualizations published to Tableau Public can be embedded into blogs. Also, web pages and be shared through email or social media. The shared content can be made available s for downloads. This makes it the best Big Data Analytics tools.

iii. Limitations of Tableau Public

All data is public and offers very little scope for restricted access

Data size limitation

Cannot be connected to R.

The only way to read is via OData sources, is Excel or txt.

b. OpenRefine

i. What is OpenRefine – Data Analytic Tools

Formerly known as GoogleRefine, the data cleaning software. As it helps you clean up data for analysis. It operates on a row of data. Also, have cells under columns, quite similar to relational database tables.

ii. Uses of OpenRefine

Cleaning messy data

Transformation of data

Parsing data from websites

Adding data to the dataset by fetching it from web services. For instance, OpenRefine could be used for geocoding addresses to geographic coordinates.

iii. Limitations of OpenRefine

Open Refine is unsuitable for large datasets.

Refine does not work very well with big data

c. KNIME

i. What is KNIME – Data Analysis Tools

KNIME helps you to manipulate, analyze, and model data through visual programming. It is used to integrate various components for data mining and machine learning.

ii. Uses of KNIME

Don’t write blocks of code. Rather, you have to drop and drag connection points between activities.

This data analysis tool supports programming languages.

In fact, analysis tools like these can be extended to run chemistry data, text mining, python, and R.

iii. Limitation of KNIME

Poor data visualization

d. RapidMiner

i. What is RapidMiner – Data Analytic Tools

RapidMiner provides machine learning procedures. And data mining including data visualization, processing, statistical modeling and predictive analytics.

RapidMiner written in Java is fast gaining acceptance as a Big data analytics tool.

ii. Uses of RapidMiner

It provides an integrated environment for business analytics, predictive analysis.

Along with commercial and business applications, it is also used for application development.

iii. Limitations of RapidMiner

RapidMiner has size constraints with respect to the number of rows.

For RapidMiner, you need more hardware resources than ODM and SAS.

e. Google Fusion Tables

i. What is Google Fusion Tables

When comes to data tools, we have a cooler, larger version of Google Spreadsheets. An incredible tool for data analysis, mapping, and large dataset visualization. Also, Google Fusion Tables can be added to business analytics tools list. This is also one of the best Big Data Analytics tools.

ii. Uses of Google Fusion Tables

Visualize bigger table data online.

Filter and summarize across hundreds of thousands of rows.

Combine tables with other data on the web

You can merge two or three tables to generate a single visualization that includes sets of data. You can create a map in minutes!



iii. Limitations of Google Fusion Tables

Only the first 100,000 rows of data in a table are included in query results or mapped.

The total size of the data sent in one API call cannot be more than 1MB.

f. NodeXL

i. What is NodeXL

It is a visualization and analysis software of relationships and networks. NodeXL provides exact calculations. It is a free (not the pro one) and open-source network analysis and visualization software. NodeXL is one of the best statistical tools for data analysis. In which includes advanced network metrics. Also, access to social media network data importers, and automation.

ii. Uses of NodeXL

This is one of the data analysis tools in Excel that helps in the following areas:

Data Import

Graph Visualization

Graph Analysis

Data Representation

This software integrates into Microsoft Excel 2007, 2010, 2013, and 2016. It opens as a workbook with a variety of worksheets containing the elements of a graph structure. That is like nodes and edges.

This software can import various graph formats. Such adjacency matrices, Pajek .net, UCINet .dl, GraphML, and edge lists.

iii. Limitations of NodeXL

You need to use multiple seeding terms for a particular problem.

Running the data extractions at slightly different times.

g. Wolfram Alpha

i. What is Wolfram Alpha

It is a computational knowledge engine or answering engine founded by Stephen Wolfram.

ii. Uses of Wolfram Alpha

Is an add-on for Apple’s Siri

Provides detailed responses to technical searches and solves calculus problems.

Helps business users with information charts and graphs. And helps in creating topic overviews, commodity information, and high-level pricing history.

iii. Limitations of Wolfram Alpha

Wolfram Alpha can only deal with a publicly known number and facts, not with viewpoints.

It limits the computation time for each query.

Any doubt in these Statistical tools for Data Analysis? Please Comment.

h. Google Search Operators

i. What is Google Search Operators

It is a powerful resource which helps you filter Google results. That instantly to get most relevant and useful information.

ii. Uses of Google Search Operators

Faster filtering of Google search results

Google’s powerful data analysis tool can help discover new information.

i. Solver

i. What is Excel Solver

The Solver Add-in is a Microsoft Office Excel add-in program. Also, it is available when you install Microsoft Excel or Office. It is a linear programming and optimization tool in excel.

This allows you to set constraints. It is an advanced optimization tool that helps in quick problem-solving.

ii. Uses of Solver

the final values found by Solver are a solution to interrelation and decision.

It uses a variety of methods, from nonlinear optimization. And also linear programming to evolutionary and genetic algorithms, to find solutions.

iii. Limitations of Solver

Poor scaling is one of the areas where Excel Solver lacks.

It can affect solution time and quality.

Solver affects the intrinsic solvability of your model.

j. Dataiku DSS

i. What is Dataiku DSS

This is a collaborative data science software platform. Also, it helps a team build, prototype, explore. Although, it deliver their own data products more efficiently.

ii. Uses of Dataiku DSS

Dataiku DSS– Data analytic tools provide an interactive visual interface. As in this they can build, click, and point or use languages like SQL.

iii. Limitation of Dataiku DSS

Limited visualization capabilities

UI hurdles: Reloading of code/datasets

Inability to easily compile entire code into a single document/notebook

Still, need to integrate with SPARK

These were the top data analytics tools and this is all on Best Big Data Analytics tools.