Software testing is a process, to evaluate the functionality of a software application with an implication to find whether the developed software met the specified requirements or not and to identify the defects to ensure that the product is defect free in order to produce the quality product.
Limitations of the current Software Testing technique:
- Software testing approaches are driven by data (like skewness in data, datasets size mismatch etc.) rather than the testing scenarios.
- Standard data matching tools don’t work with large volumes of data. This becomes a limitation to the software testing engineer’s skill sets.
The testing process is understandably the most important aspect of any software. The Testing Engineer role extends to different domains when the organization chooses to adapt itself to improve the technology.
At that time It clearly shows that the growth rate of Hadoop related jobs is much higher than that of software testing jobs.
Why Big Data?
In the past Decade, technology platforms were built to address either unstructured or structured data. The value and means of unifying, integrating these data types had yet to be realized, and the computing environments to efficiently process high volumes of disparate data were not yet commercially available.
According to the Study of “Accenture Big Data ” in 2014, Data initiatives are rated as “extremely important” or “important” to 93% of companies over $250M.
Large contents repositories house unstructured data such as documents, and companies often store a great deal of structured information corporate systems like Oracle, SAP and NetSuite and others. Today’s organizations, however, are utilizing, sharing and storing more information in varying formats, including:
- e-mail and Instant Messaging
- Collaborative Intranets and Extranets
- Public websites, wikis, and blogs
- Social media channels
- Video and audio files
The opportunity to amass and capitalize on Big Data is available to any organization, large or small. Leveraging a Big Data analytics solution can help you unlock the strategic value of this information by allowing you to:
- Understand where, when and why your customers buy
- Protect your client base with improved loyalty programs Seize cross-selling and upselling opportunities
- Provide targeted promotional information to your prospects and existing clients
- Optimize Workforce planning and operations
- Improve inefficiencies in your supply chain
- Predict market trends and future needs
- Become more innovative and competitive
- Discover new sources of revenue
The Big Data Challenge and Opportunity
Big Data analytics provides organizations with an opportunity for disruptive change and growth. In most cases, however, the data sets are too large, move too fast or are too complex for the traditional computing environment, which creates a significant challenge. The technologies are available; however, an investment of time, money and resources will be necessary to fully implement a Big Data solution. Is it worth it? The options are limited—invest in the platform, technologies, and expertise to leverage your data, or continue along the path of the status quo. Enterprise content and data specialists, such as General Networks, can help you to define and quantify your Big Data goals and objectives.
Software Testing Engineer learn Big Data and Hadoop
A good Software Testing Engineer possess sharp analytical skills, strong technical skill, great attitude, detail oriented and willingness to learn. These are the exact traits required for anyone to switch over to Hadoop. It is irrefutable that Testing is undergoing transformation but it is not going to be the end of it. But with the changing times, it is prudent to sail the high wave – Hadoop, considering all its features and flexibility.
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