When data mining and handling techniques are not useful and are unable to expose the insights of large data, unstructured data or time-sensitive data, another aspect is used which is new to the realm of software industries.

We at TheWebOrion love to break new technologies through the security gaps and make enterprises more secure by enabling them to fix the vulnerabilities in no time.

If you are a startup or a Fortune 500 enterprise, chances are you rely on Hadoop for its Big Data requirements. In the case if extremely strict security processes are not followed and if developers are not aware of the security vulnerabilities, chances are you might be a highly insecure Big Data instance – waiting for it to be compromised by an attacker.

During our previous engagements, we have identified most of the Big Data Hadoop instances to be highly insecure and vulnerable to easy-to-execute security attacks. This made us launch Hadoop and Big Data Penetration Testing as one of our offerings.

 

Testing of Big Data Applications:

1. Data Staging Validation: The first stage also referred to as a Pre-Hadoop stage which involves the process of big data testing.

2. Map Reduce Validation: the Second stage comprises the verification and validation of Map Reduce. Usually, testers perform tests on business logic on every single node and run them on every different node for validation.

3. Output Validation Phase: This is the third and final stage of big data testing. After successful completion of stage two, the output data files are produced which is then ready to be moved to the location as per the requirement of the business.

 

Challenges in Big Data Testing

 Following are the challenges faced in big data testing:

  • Automation Testing is Essential: Since the big data involves large data sets that need high processing power that takes more time than regular testing, testing it manually is no longer an option. Thus, it requires automated test scripts to detect any flaws in the process. It can only be written by programmers that mean middle-level testers or black box tester needs to scale up their skills to do big data testing.
  • Higher Technical Expertise: Dealing with big data doesn’t include only testers but it involves various technical expertise such as developers and project managers. The team involved in this system should be proficient in using big data framework such as Hadoop.
  • Complexity and Integration Problems: As big data is collected from various sources it is not always compatible, coordinated or may not have similar formats as enterprise applications. For a proper functioning system, the information should be available in the expected time and the input/output data flow should also be free to run.
  • Cost Challenges: For a consistent development, integration and testing of big data require For business’s many big data specialist may cost more. Many businesses use a pay-as-you-use solution in order to come up with a cost-saving solution. Also, don’t forget to inquire about the testing procedure, most of the process should include automation tests otherwise it will be taking weeks of manual testing.

 

Our team will help you:

Reduce risk: Rely on a Fortune 100 company to deliver dependable results

Accelerate time to value: Use our expertise to speed up your Big Data deployment

Maintain control: Trust our advisors to guide you to self-sufficiency