Is your Enterprise Big Data Tested?

Is your Enterprise Big Data Tested?

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The Startup buzz is gaining grounds and it has transformed the way enterprises strategize and operate. Startups are known to leverage various technologies that boost cost effectiveness, efficiency and time to market. For instance, thanks to the Open source platforms, today Startups have access to the best Big Data infrastructure and testing tools at ‘zero’ cost. They run a mile further in optimizing the Cloud to reap the most from their Big Data investments.

Big Data implementation for enterprises can work wonders. What you need is a robust application that is rigorously twisted and tested to fit your organization’s requirements and objectives.

IDC (a market research firm) estimates 50% increase in revenues from the sale of Big Data and business analytics software, hardware, and services between 2015 and 2019. Big Data and Analytics Sales are expected to reach $187 Billion by 2019.

How does Big Data Empower Businesses?

Big Data has proved to be a game changer for American retail stores, as they have been able to further analyze and effectively segment the customer database and market. This has enabled to create customized marketing campaigns and offer relevant deals. Further, they have been equipped with information to schedule their deals and offers as per the data drawn by the application.

It is further predicted that government organizations across the globe will leverage Big Data to radically reduce government expenditure. High profile statisticians and officials will be replaced with Data Scientists to derive the required numbers.

After the super successful and intense Climate Change talks in Paris, there is going to be a whole lot of difference in the way Climate Change is perceived. It will not be alleged as a matter of threat, but an enabler for Market Capitalization purely on the basis of Big Data technologies. For instance, Big Data will analyze climate change views and expert comments across Social Media and Internet, which will help determine the impact rather than just depend on the conventional Meteorological reports.

Big Data implementations have brought remarkable results for enterprises who knew and kept their conviction towards the business objectives. However, it can be a major disappointment for organizations that miss out on the underlying purpose of Big Data implementation.

If the data is managed methodologically, it can empower an organization to make informed choices while venturing in the market place.

What does Big Data Testing Entail?

Big Data testing involves authenticating various data processes and not just the features. Performance and Functional testing work effectively for Big Data applications. While testing their applications, QA engineers process three types of data – Batch, Real time, and Interaction.

Collaborating with an experienced testing partner is absolutely key, as it is important to devise a high level test strategy. Moreover, before the testing starts, it is important to check the data quality and confirm related factors like data accuracy, duplication, and validate whether the existing data is all-inclusive.

In this article, we would like to highlight some prominent benefits of Big Data testing, assuring desired results that can enable informed decision making and ensure higher ROI.

Eases Downtime

The emerging concept of Bring-Your-Own-Device (BYOD) and implementation of Cloud services facilitates anytime, anywhere access to enterprise applications. Due to this there is a rising dependency on the organization’s data to run these applications. This sometimes affects the performance of the application. So, it is important to test the Big Data applications that are expected to be available for employees 24*7. It will avoid bugs, enhance data quality, and ensure seamless functioning of the application. In summary, reduce any expected downtime.

Eases Operating with Large Data sets

With Big Data Applications, development begins with implementation of small data set and then moves on to the larges data sets. As expected, the glitches occurring with small data sets are way lesser than with larger ones as the development process matures. With a view to avoid breakdown of enterprise level applications, it is crucial to test the application’s lifecycle and ensure flawless performance irrespective of changes in data sets.

Maintains Data Quality

Integrity and quality of data is immensely vital for an organization’s growth and attaining overall business objectives. Big Data is increasingly getting popular today, as it empowers enterprises and top management folks to take informed decisions based on historical as well as contemporary data points. Testing these business critical applications helps you avoid duplicity and redundancy with the data sources.

Strengthens Credibility & Performance of Data

The effectiveness and performance of Big Data applications depends on the accuracy and authenticity of the existing data available within an enterprise. Big Data testing involves verification of these data layers, data sets, algorithms, and logic. This efficiently ensures performance of business critical Big Data applications.

Authenticates Real-time data

As mentioned earlier, real-time sourcing of data defines the effectiveness of Big Data application for enterprises. Performance testing of the required data is important to confirm its operational efficiency in real-time. Time is the key word and testing is the only mechanism to determine the ‘time’ factor.

Digitizing data

Organizations across the world have data stored in hard copies, which needs to be cleaned and digitized. Testing helps to scrupulously assess and ensure that no data is not corrupted or lost. The data is converted into various digital formats as per the organization’s requirements. This further ensures availability of essential data in real-time and optimize the processes.

Checks Consistency

When data is digitized, it gets converts into various formats. With Big Data applications and predictive analysis, there are chances of inconsistency over a period of time. Testing brings down these disparities, thus reducing uncertainty.

A comprehensive Big Data and Predictive Analytics strategy enables enterprises to be more analytical in their approach, ensuring higher ROI. Today, enterprises are rapidly seeking Big Data and Analytics solutions. It is predicted by market research firms that the utilities, healthcare and BFSI sectors will bring fastest revenue growth in Big Data and Business Analytics.

Collaborating with the right partner is the need of the hour. Cigniti has worked with global enterprises to devise a resourceful Big Data Testing strategy. Connect with our experts and understand the various facets of Big data testing.

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