Big Data Analysis Tools
Rudra Makwana | 4th year B.Tech Integrated (Computer Engineering),
NMIMS’s MPSTME.
Abstract
Big Data Analytics is a very broad area and attracts interests from both academia and industry. A lot of information, knowledge and patterns can be extracted from big data. Big data is a new trend and many companies are working on the same. Companies are analyzing this large amount of data with help of various tools. They also offer for software with easy and simple user interface to analyze data. This paper contains a short abstract on big data and various analyses tools of the same.
Introduction
Big Data is defined as a collection of large amounts of organized and randomized data. The data may be structured, non-structured of semi-structured and is about a company or product. It has five characteristics also known as 5Vs of Big Data: Volume, Variety, Velocity, Veracity and Value.
Big Data Analysis is the process of examining or analyzing large amount of big data to extract information like hidden patterns, correlations, market trends and customer preferences. Big Data Analyses plays an important role in industry, banking and health care.
Types of Big Data Analyzing Tools
There are a large variety of tools available to improve various factors in analyzing the data. These tools may be available as open-source tools or closed-source tools. The tools have five main approaches to analyze data and gather analysis report:
· Discovery Tools:
Discovery tools are useful throughout the information lifecycle for frequently, intuitive exploration and analysis of information form any combination of structured, unstructured and semi — structured source. These tools are used along with Business Intelligence Tools.
· Business Intelligence (BI) Tools:
BI tools are used for analyzing, reporting and performance management with data from data warehouse or information systems.
· In-Database Analytics:
They are techniques allow data processing directly in the database.
· High-Availability Distributed Object-Oriented Platform (HADOOP):
Hadoop is an open-source platform for pre-processing of data to identify macro trends or chunk of values. It is used as a basic form of analysis.
· Decision Management:
It consists of self-learning and predictive modelling and allows distinct recommendations across multiple channels.
Tools for Big Data Analytics
A. Google Big-Query:
It is a revolutionary tool which can run SQL queries over unstructured data. It can execute statements against huge datasets and billions of data rows within a few seconds. Some of features are:
· It analyses large datasets in short amount of time.
· It can be accessed by a number of methods: through Big Query Browser Tool, Google Spreadsheet, etc.
· The data can be loaded easily by direct uploading or by Cloud storage.
· It has a transparent and simple pricing structure and offers some free amount of data.
B. Datameer Big Data Analytics:
It is a robust application tool which offers data integration, analytics and data visualization. The key features of this application are:
· It has good data integration and allows gathering and integrating data from various resources.
· It has its own API which can be used by external applications to access it.
· It has good data analytic process, ensuring instant data visualization of data.
C. Pentaho Big Data Analytics:
It offers a complete solution to analyze and blend big data into insights within a single integrated platform. The unique features of Pentaho are:
· It lets the users to blend all types of data. Data can be processed from a number of sources like Hadoop, No SQL Databases, etc. Powerful algorithms, built-in components and sophisticated data processing tools enable the users to uncover valuable insights that usually remain hidden on leveraging traditional data analysis.
· It lets user draw interactive visualization by leveraging wide variety of built-in visualization tools.
D. Alteryx Designer:
It is a data analytical tool used across the industry. It can process all sorts of sophisticated data. It is very easy to use. Key features of Alteryx Designer are:
· It can integrate data from multiple sources in a single workflow which ensures improved decision making.
· It has multi-threading capabilities and is deeply associated with R language.
Closure
Big Data analytical tools are used to analyze data and generate analysis data or reports. They provide effective ways to analyze huge amount of data with more efficiency. All big data analysis tools provide similar functionalities like data analyses, integration and visualization and the tools differs on some parameters.
References
· Empirical Investigation of Big Data Analytical Tools: Comparative Analysis
https://ieeexplore.ieee.org/abstract/document/8862739
· Google Big Query
https://www.slideshare.net/AndreasRaible/google-bigquery-features-benefits
· Alteryx
https://www.alteryx.com/products/alteryx-platform/alteryx-designer
· Pentaho