The Top 5 Debunked Myths About Big Data and Hadoop
What is Hadoop and Big Data? While most business leaders and decision makers have at least heard about these technologies, they also have misconceptions or myths about whether these technologies can work for their business.
This article discusses the top 5 myths about Big Data Hadoop, which have been debunked:
Myth 1: Only big companies require Big Data analytics
Big Data analytics is a technology that is required by both large Fortune 500 companies and by small-to-medium business (SMB) enterprises. Most industry leaders believe that SMBs are not equipped to generate and handle Big Data, which is not true. As compared to large corporations, SMBs have both the speed and flexibility to leverage on structured data.
Myth 2: Only experienced data scientists can make sense of Big Data
Another common myth is that only data scientists with a doctorate in Mathematics and computer science experience can work with Big Data. While data scientist are few and harder to recruit, the fact is that Computer Science professionals with a decent understanding of Mathematics can equally perform the job.
Myth 3: Myths about Hadoop
This includes assumptions about what is Hadoop technology, what is Hadoop used for, or the common Hadoop is only good for batch processing. Hadoop-based solutions are good for real time analytics and can work with other Big Data solutions such as Spark. Regarding myths about implementing security with Hadoop, recent developments have made it easier to achieve enterprise-level security using Hadoop.
Myth 4: My company does not have Big Data.
Most companies do generate big data. The only challenge is on how to generate good or useful data that draw insights about customers. Without a proper infrastructure, companies waste time and money collecting the wrong data. Companies need to address questions about the type of business data they want to analyze and the use case, before capturing the relevant data.
Myth 5: Big Data required big investment.
This is not true in all cases. The budget requirement usually depends on the type of data analytics to be performed. Use of public cloud-based platforms can reduce the costs and complexities associated with Big Data. For more details on bigdata & in depth, enroll for the big data and Hadoop training with Acadgild and become a successful Hadoop Developer.