Top 20 Big Data Tools: Big Data and Types of Big Data Jobs

By Indeed Editorial Team

Published 19 January 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

Big data is an information technology term that refers to the process of mining and using massive amounts of data from multiple primary and secondary sources. Technical experts use big data tools and technologies to extract the data and organise, store and update it in databases so that it is easy to retrieve and reference for analytical reports. By understanding big data tools and their role in data analysis, you can decide if you want a career in this field. In this article, we explain more about big data, including big data tools and corresponding software, and share some jobs in big data.

What is big data and its tools?

The term big data was coined in 2005 by O'Reilly Media's Director of Market Research, Roger Mougalas. Big data comprises large and complex data sets that contain a great variety of data from different sources. The data can be in various forms, such as text, images, video and audio, and may come from:

  • news reports

  • documents

  • emails

  • social media data feeds

  • web page clickstreams

  • web applications

  • customer databases

  • medical records

  • historical records

  • transaction processing systems

  • smart devices

  • interconnected sensor equipment

  • industrial equipment

  • scientific research

  • financial market data

  • network and server log files

  • geographic information

  • traffic information

  • weather information

Since it is difficult for traditional data processing software to handle the rapidly accumulating and voluminous bulk of data sets, it is necessary to use advanced big data tools and technologies to process them. These tools allow technical experts to sift and sort through vast amounts of data and organise it so that it is possible to derive meaning from it and identify trends and patterns. They can analyse them and use their findings to create insightful analytical reports that predict behaviours and make informed assumptions to address problems and find solutions in various fields.

What are the most popular big data tools?

The most popular big data tools are the ones that enable technical experts to do the following:

Undertake data integration

With the tools used in big data, technical experts can rapidly gather and process high volumes of raw, unstructured and partially structured data from different sources. They can transform the data into an easy-to-understand format. With large data integration, processes can become quicker.

Manage and store data

As the data sets can scale up to terabyte, petabyte and even exabyte levels, they must have adequate storage solutions. With big data tools, companies can store massive amounts of data in clusters on-premises, in the cloud or by using both options. It is possible to store the data in any format to meet processing requirements, update it regularly and access it whenever needed.

Analyse and align data

With big data tools, it is possible to analyse varied data sets, make important discoveries and align the findings to specific goals. For example, by using the data related to customer behaviour, product sales and market trends, companies can determine how well their business is doing in the marketplace currently and predict how it might fare in the future. They can make decisions to improve their business model, develop newer products, expand to other markets and increase their profits.

Related: 50 Data Science Interview Questions (With Example Answers)

Which software is used for big data?

The list of big data tools that companies commonly use includes the following top 20 tools:

  1. Apache Hadoop

  2. Storm

  3. MapReduce

  4. Google Search Operators

  5. Google Fusion Tables

  6. Splice Machine

  7. Microsoft HDInsight

  8. RapidMiner

  9. OpenRefine

  10. NodeXL

  11. HPCC

  12. Atlas.ti

  13. Qubole

  14. Statwing

  15. Pentaho

  16. Cassandra

  17. Cloudera

  18. Hive

  19. Tableau

  20. Zoho Analytics

What are big data analytics tools?

Big data analytics tools are those tools used in big data operations by information technology experts to process, analyse and interpret the large set of data in their databases. Since it can be extremely arduous to manually process and analyse the copious amounts of complex data in the databases, it becomes necessary to use big data tools and technologies to manage it.

With the help of these big data technologies and tools, the IT experts can find out about current market trends, industry competitors, target customers, customer preferences and other vital business information. They can then report their findings to management and assist them in making crucial business decisions to benefit the company.

What are big data jobs?

Big data jobs are those jobs that are concerned with gathering, organising, processing and analysing extensive amounts of data for various business purposes. Most companies require different kinds of information to function and stay competitive in their industry. So, they hire skilled employees with technical expertise to use big data technology and tools to extract data from multiple sources and store it in databases.

The big data experts then organise and process this data so that it is easily accessible and readable. They analyse it to derive meaning from it and write detailed reports on their data interpretations. The company management uses the insights and information from these data analysis reports to improve the efficiency of their current operations, enhance their customer service, identify new business opportunities and make smarter and more profitable business decisions.

Where to find big data jobs

You may be able to find big data jobs in different companies in almost all industries. The ones that typically hire professionals with big data skills are IT companies, health care companies, insurance companies and online retailers. Their advertisements for big data job openings may appear on the company's website, online job sites, professional networking sites and social media platforms. Some jobs may be available only through industry contacts.

Types of big data jobs

Big data jobs are available across different industries as a growing number of companies are beginning to understand the value of data analysis for advancing their businesses. Here are some big data jobs that you can take up:

1. Technical recruiter

National average salary: ₹23,306 per month

Primary duties: The principal role of a technical recruiter is to find qualified IT professionals to fill the available positions in a company. They post the job descriptions on the company website, online job sites, professional networking sites and social media platforms. After that, they screen the applications they receive, shortlist candidates, invite them and conduct the interviews. They inform the candidates of their selection, discuss salary and benefits and assist with onboarding.

2. Data analyst

National average salary: ₹31,953 per month

Primary duties: A data analyst works independently or with a team to design, develop and maintain databases and data systems. They also extract raw data from primary and secondary sources. After this, they reorganise the data into a readable format, analyse it and write informative reports. Companies use these data analysis reports to make crucial business decisions.

Related: Frequently Asked Questions: What Is a Data Analyst?

3. Database manager

National average salary: ₹37,363 per month

Primary duties: Database managers set up databases and data handling systems, monitor their efficiency, develop data processing protocols and oversee project management tasks. They train and supervise the data teams and manage budgets. Additionally, they write data reports to help the management team make correct business decisions.

4. Database administrator

National average salary: ₹6,60,629 per year

Primary duties: A database administrator helps to develop databases and oversees their daily management. They keep them updated, organise data, manage access and ensure data security. They are also responsible for database modification and maintenance work.

Related: 13 Data Mining Techniques: A Complete Guide

5. Network security engineer

National average salary: ₹7,79,271 per year

Primary duties: A network security engineer installs, tests and updates security software and sets up firewalls. They also monitor computer networks and take action to prevent intrusions and other security breaches. Additionally, a network security engineer may offer technical support to users and make recommendations to the management for improving network security.

6. Business intelligence analyst

National average salary: ₹8,25,539 per year

Primary duties: The main responsibility of a business intelligence analyst is to source, review and analyse data from databases. They can then use the information to compile finance and market-related reports. These reports can guide companies in making decisions that affect their business operations and goals.

7. Data scientist

National average salary: ₹8,50,809 per year

Primary duties: A data scientist extracts data from different sources, processes it and analyses it. They write conclusive reports on the trends and patterns they find. They also create automated data modelling processes and use these to build machine-learning algorithms and predictive models.

Related: What Does a Data Scientist Do? And How To Become One

8. Big data engineer

National average salary: ₹10,51,807 per year

Primary duties: A big data engineer processes, evaluates and manages massive amounts of raw data. They create data processing systems to make the data usable and easily accessible. They provide reports to companies and help them improve their business performances.

Please note that none of the companies mentioned in this article are affiliated with Indeed.

Salary figures reflect data listed on Indeed Salaries at time of writing. Salaries may vary depending on the hiring organisation and a candidate's experience, academic background and location.

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