Big Data is improvising the way companies and businesses operate and compete. It is recognized as a large set of data gathered from myriad sources that are useful for extracting vital data. This is the core reason why every single enterprise is concentrating on executing the right techniques for the storage, collection, evaluation, and testing of Big Data. In short, big data allows organizations to enhance operational efficiencies, assess their internal processes, and lower costs.
Implementing this cutting-edge solution even allow data experts to recognize the latest trends, such as discovering financial implications, financial bench-marking against industry standards and determining financial growth prospects. Big Data and Analytics also bring incredible impact to all kinds of enterprises. It allows enterprises to drive their different sales and marketing campaigns, and make informed decisions to drive the desired outcome.
Big Data Predictions and Stats
According to a current study and research report mentioned by MarketsandMarkets, the big data market size to rise worth $ 229.4 billion in 2020 from $ 138.9 billion by 2025 globally, at a CAGR (Compound Annual Growth Rate) of 10.6 percent during the forecast and analysis period.
Image source- Marketsandmarkets forecast and analysis for Big Data
A Forrester research and study also found that 44% of B2C marketers or enterprises are using big data and analytics to enhance response rate and to gain greater insights to prepare or develop effective relationship-driven strategies.
As per Accenture study, 79 percent of executives in the enterprise is of the same opinion that organizations that don’t embrace Big Data and Analytics will drop their competitive point & could face loss. Plus, 83% have pursued projects on Big Data to gain a competitive edge.
Around 59 percent of executives stated that Big Data at their organization would be improved through AI usage as per PwC.
On a current McKinsey Analytics survey, 50% of participants confirm that Big Data and analytics have tremendously gain insight by boosting business practices chiefly in marketing and sales roles.
As mentioned by Statista, global Big Data market output for software & services can hit to USD 103B in 2027 from USD 42B in 2018, increasing a CAGR by 10.48%.
Image Source- Statista 2020- Big data market size revenue forecast worldwide from 2011 to 2027
Also Read: Why You Should Invest In Big Data Testing?
Applicability of Big Data Testing for Enterprises
Big Data majorly focuses to achieve quality data that help companies to make appropriate decisions and help improve bottom and top line. Due to higher testing efforts on data validation, the actual system tests often take a back gear. To beat these glitches and to obtain the massive benefits of Big Data, there are varied ways for processing big data:
Frame Better Testing Strategy: Craft a better test strategy that automates the process concerning the collection and scrutiny of valid data. It ensures that the test automation scheme is in line with the stated business objectives.
Performance Testing: Performance tests are done mainly to determine the Stability, Speed, Scalability, under the series of data counting Structured, Semi-structured, and Unstructured. This type of test can easily process big data in minimal time. It helps to completely discover issues and erase the blockers that may affect the overall performance.
Functional Testing: This type of testing is essential across 5 Vs (Value, Volume, Velocity, Veracity, and Variety) of Big Data. It helps to verify and validate the results at every stage thus wipe out defects and aid to meet client expectations.
Hence, leveraging Big Data and analytics is crucial for the benefit of the organization. We, at KiwiQA, provide high-end Big Data & Analytics Solution to optimize data processes in various scenarios and outline data-driven solutions in shortened timelines.
Most Popular Tools For Testing Big Data
HDFS (Hadoop Distributed File System) Tool: It critically replicates the data across diverse servers or systems. Assists in processing data on other replicated servers if in case one server is completely down.
MapReduce Tool: Handle and optimize and gargantuan quantity of data that could be semi-structured, data, structured, or unstructured.
PIG Tool: This is the top-level language that is critical to scrutinize a large bundle of data, signifying them as data flows. You can also use it with the Hadoop tool and aids to carry out all the Hadoop’s data manipulation functions.
KiwiQA’a open-source testing tools help assess the reporting app for end-users adaptability and constantly re-examine the observations with dev and user groups, as a part of our DevOps and agile testing. We have a team of qualified QA testers who works with devotion and steadfastness to deliver maximum results in the shortest time period.
Core Advantages of Big Data Testing
Listed below are some of the crucial benefits of big data testing:
1. Big Data Helps Enhance Data Accuracy
Every single organization is seeking for proper information that can aid them for business forecasting and decision-making. Such data needs to be authenticated for its accurateness in any big data software app. This can be critically done by ensuring that the data insertion procedure is error-free, correct data is feeding to the big data framework and the data output in the data access tools is correct as per the need.
2. Big Data Manage Confidentiality & Improve Data Security
It is critical for the enterprises involved with client apps to manage data confidentiality and maintain the level of confidence. In case of any breach in data, the brand name might fall in the danger zone. Hence, it is recommended to conduct big data tests at every single level to avert the chances of the data security breakdown.
Also Read: Big Data Testing For Enterprises
3. Businesses Leverage Insights to Make Better Decisions
Appropriate data is significant for critical business decisions and success. By using high-tech big data technologies and platforms, analyzing the bulk of data to leverage insights becomes easy. When the right information and data goes in the hands of the right people, it becomes a positive trait. It helps to scrutinize all sorts of threats in the decision-making process, which ultimately becomes a great help to make better decisions.
4. Big Data Enabled New Concept in Customer Insights
Big data has enabled a new concept in customer analytics and insight by not only making assumptions about their crucial desires but indeed by monitoring what the customer truly wants. Leveraging such beneficial data, businesses can use their ability to create insights around customer’s activities what they take on their journey, along with their intention.
Also Read: Top 5 Big Data Testing Challenges
5. High Profits and ROI
For any enterprise, in order to get ahead of the competitive market, it is crucial to crafting effective strategies for Big Data Analytics. The adding up of data testing just before any processing or analysis guarantees and authenticates that enterprise dealing with the appropriate data. This, in turn, results in a hike in revenue for your business and helps cut down costs.
If you have any Big Data project in your head, then reach out to KiwiQA for a consultation. We have a pool of dedicated QA professionals with great experience in big data testing.