The Importance of Big Data for an Enterprise
Big data comprises of many data sets often called as Hadoop. They are so large that they cannot be easily captured, stored, or searched using tools. There are various areas where the data sets add to the ‘Huge Data’ in the global market, including human genome and the environment. Handling such huge data requires special software working on various servers simultaneously.
With so many uncertainties with the organizations today, the value of huge datasets cannot be overstressed. In the latest trend, it is seen that targeted marketing of a particular item from a US-based retailer utilizes various methods to identify customers requiring that particular product based on the information gathered on purchase pattern. This was accomplished by assigning an ID to the customer and their purchases were tracked. This was done to anticipate buying pattern of the customer to design targeted campaigns for marketing.
In order to achieve market growth, there are a few considerations for data analytics.
- Setting special courses for necessary skills
- Including analytics strategy in Applied Science courses
- Generate awareness through government-drove initiatives
- Enhancing big data initiatives through increase in R&D
Big data can benefit organizations in the below five areas:
- Comprehend market conditions
Big data can help the organization to predict future customer behavior.
- Better know your customers
With the help of big data analysis, you can know the general thought process and feedback from your customers.
- Control Online Reputation
You can make use of big data tools to make sentimental analysis to manage online communication.
- Cost Saving
Big data tools prove to be cost-efficient in the long run. However, there might be an initial cost associated with it.
- Data Availability
You can get relevant data through big data tools in a proper structured format.
With the growing complexity in the IT industry, QA holds the key to assisting business in making perspective and intelligent decisions. The quality of a BI solution is dependent upon the quality of the provided data and the value of findings it delivers. An effective testing can help in ensure data credibility through a comprehensive test strategy that includes test planning, infrastructure and QA teams, developers and business users.