Are you feeling comfortable using big data techniques? Are you able to get benefits in business? Have you received to get the real value of Hadoop to take your business to new heights, if not yet then rethink on this issue because as a big data developer, you must be aware that there are a lot of myths regarding the adaptation and implementation of big data? If your company is implementing big data with misconceptions and if you don’t have clarity regarding the power of Big data then your business will not be able to get real benefits.

Our big data developers have shared views in this post regarding the myths people normally have regarding big data.

1. Hadoop is Batch Only

A myth about Hadoop is that it is useful only for batch processing. Batch processing is used for large quantities of historical data and is normally a slow processor in a way we can say, it doesn’t go with the cloud technologies. But the reality is that it’s a practical, powerful solution for real-time analytics. Hadoop works very well with other real-time big data solutions, including Spark, and is capable of handling immediate processing jobs like online customer transactions where there is no room for errors or latency.

2. Security is No Good with Hadoop

When the Hadoop solutions started initially many security locks were reported which Hadoop has overcome with due course of time. Now it is implementing enterprise level high security. Hadoop ecosystem leaders have built enterprise-grade security into their Hadoop Platforms, including Cloudera in Cloudera Enterprise, Hortonworks in the Hortonworks Data Platform, and MapR in its Converged Data Platform. The level of desired security can be achieved using Hadoop.The ecosystem implemented is in accord with the cloud technologies so we can be assured of data security.

3. There is No Good Way to Achieve Data Governance in Hadoop

The data security issue is resolved in Hadoop and data governance is achieved. However, the myth is still continuing that the Hadoop can’t handle huge data transactions. The Cloudera Navigator, Hortonwork’s integration, and MapR Converged Data platform are used to provide governance in the Hadoop environment.

4. Big Data and Hadoop work well with Unstructured Data

Hadoop was initially adopted widely to provide solutions when it comes to managing and analyzing unstructured data, so naturally, it became widely assumed that Hadoop is developed to handle unstructured data and it is good for that. In fact, the analytics capabilities applicable with unstructured data work well for the structured data sets too. Hadoop as a service has nothing to do with the nature of the data.

5. You Need skilled big data developers to Get Meaningful Answers Out of Big Data & Hadoop

People and companies normally think that big data developers and Hadoop programmers can only handle the applications and data once we start using big data solution. The companies and the persons associated will not be able to work with Hadoop or big data. It is a myth, all the tool required to work in Hadoop or big data solutions are available in the package itself, only the initial training is required.

Conclusion:

Big Data and Hadoop are cloud-based open source software frameworks for storing data and running applications on clusters of data. Hadoop is used for massive storage of data having the advanced processing power and the ability to handle virtually tasks to run complex applications.

Big data development companies are ensuring a smooth implementation of the solutions. Actually, the initial task to prepare data in a consolidated form is tiresome but once this process is completed, big data has exclusive powers to present different views of data along with the predictive analysis which will definitely boost your business, If you are planning to implement big data or Hadoop solutions then you may contact us!