It is quite a well-known fact that the Hadoop database is accompanied by inherent issues and challenges. Data integration, business needs, budget, and specialized skills are only some of the things that would be factoring into both planning and its effective implementation. With the aim of assisting companies in gaining business value and success through the use of Hadoop, we are identifying a few commonly made Hadoop mistakes that are made by IT teams and executives as they are going through the entire planning and execution process. Let us find out effective ways of avoiding all these Hadoop mistakes.
Mistake: Migrating Everything Even Before Chalking Out a Plan
You must have just realized that your present architecture is not adequately equipped for processing big data efficiently, your management is willing to adopt Hadoop instead, and you are pretty thrilled to get going. But be patient and do not be in a hurry to dive into a Hadoop project without enough thought and proper planning. Migrating before having a clear-cut strategy could be culminating in long-term problems and costly ongoing maintenance.
Understand a specific project’s potential value and know the precise business reason. When you are using Hadoop the very first time, it is going to be a really steep learning curve and be prepared to get a tremendous amount of error messages. Dysfunction is supposed to be the Hadoop environment natural byproduct unless you are availing the proficiency and expertise of RemoteDBA.com for perfect database solutions. Successful implementation would be possible by identifying precisely a particular business use case. You must take into account every stage of the process and you must very vividly determine the method of how Big Data and Hadoop would be generating value for your organization or business. You must consider taking a comprehensive view of your data pipeline before the implementation of the Hadoop database. This would be boosting product success and fortifying IT collaboration and interaction with the business.
Mistake: No Special Treatment for Hadoop
A major mistake would be if you are handling Hadoop just in the same manner as other standard regular databases. Hadoop seems to be quite powerful but it is definitely not structured in the same manner as the Oracle or Teradata database, or HP Vertica etc. In the same way, Hadoop was certainly not designed for storing anything that could be kept normally on your Google Drive or Dropbox. Another effective rule of thumb in this context, if it could be fittings on your laptop or desktop, chances are it did not belong to Hadoop.
Solution: Avoid Data Swamp
As your company would be scaling up there could be data onboarding from only a few sources that would be going into Hadoop and then to a hundred others. Resources and IT time could be monopolized, generating numerous hard-coded data movement processes. Moreover, the process could be error-prone or highly manual. You must consider taking effective measures upfront so that you could understand and identify the best ways to utilize the Hadoop ecosystem for deriving business value. Or else, you would land up with a data swamp or data lake. That implies lots of data would be there but you would not succeed in deriving any kind of value from it.
Mistake: Assuming that the Same Skill Sets Required For Managing a Conventional RDBMS Could Be Transferable to Hadoop
Assuming that you could carry on doing everything with Hadoop practically, the same way, you have been doing with the conventional RDBMS is a glaring mistake made by several business people implementing Hadoop the very first time. However, you simply cannot rely on the same old skill set.
Solution: New Developers and New Skills Would Be Required
As Hadoop is not used to functioning in the same manner as any relational database, you simply cannot hope to migrate all data to Hadoop and then rely on managing it in a similar way. Moreover, you simply cannot hope to transfer or interchange skill sets between the two. You could be ensuring a seamless transition to Hadoop simply be devoting adequate time to understanding how it could be serving your organization proficiently and how it could be impacting your business. At this point in time, you need to obtain new technology skills or even new developers. You must consider figuring out effective ways of integrating Hadoop into existing operational systems and even the data warehouses.
Mistake: Security Not Given Preference
For most organizations, it is of top priority to protect sensitive business data particularly, with increasing cases of data breaches taking place in the high-profile circuits. Remember you would be involved in processing extremely sensitive business data of your business partners and even important clients and customers. You must understand not only the long-term importance of securing sensitive data but you must give security top priority before deploying the Hadoop database.
Solution: Address all security solutions before deployment
You must have total control over who could be accessing clusters and exactly what they could be allowed to do with your data. You must have total control over the actions that users will be taking when they are actually in a cluster. You must remember tracking and logging all actions taken by each and every user. Use exclusively industry standard and compliant data encryption methods. Use predictive analysis for almost real-time behavioral analytics. Consider automating and sending alerts depending on diverse data in Hadoop.
The actual business value of the Hadoop database could be evaluated by the actual nature of any data issue. When a specific data problem is established your best objective would be to find out if your present data architecture would be assisting you in achieving all your goals. You have employed the services of super-talented people so you must follow their advice as they have sound knowledge and the know-how. Once you have identified the business requirement, find out who would actually be benefited from this investment, the way it would be impacting your infrastructure and effective ways of justifying spending. Moreover, it is best to avoid Science projects as they are merely technical exercise having restricted business value.