Getting the Most Value From Your Hadoop Ecosystem
For some companies, many big data projects are left unfinished due to inaccurate scope, technical roadblocks, and data silos. Misconceptions, mistakes, and poor planning can negatively impact deployments by wasting time and resources, hindering performance, and delaying return on investment.
So what can you do to avoid common mistakes and keep your Hadoop initiative on the right track? To begin with, you will need to account for common mistakes that sometimes occur. For organizations that have seen the benefits of big data, integrating Apache Hadoop® into their data management strategy means struggling with new developer tools, new user interfaces, and a need for new skills in a completely new environment.
Just finding experienced and knowledgeable talent to tackle your Hadoop applications may be quite challenging. The Wall Street Journal reports that Hadoop programmers and data scientists can earn as much as $300,000 per year.
To that end, how do you use Hadoop in a way that will give you the greatest ROI? Implementing effective information management is a good start. Your ability to exploit big data for competitive advantage depends on its consistency and accuracy. Data quality and master data management technologies will ensure the information in your Hadoop environment is fit for purpose at all times.
Another avenue to go down in getting more value is learning about how to prevent mistakes and follow best practices. You can start by downloading our white paper, “6 Issues That Can Derail Your Big Data Initiative: How to Get Hadoop Data Management on the Right Track”. Then put your big data projects on the path to success.
One more method to get the maximum benefit from your big data analytic repositories is to check out iWay Big Data Integrator from Information Builders. Our technologies work seamlessly in any Hadoop distribution, ensuring the quality, consistency, completeness, and availability of even the largest volumes of data.
Get value for your company by utilizing the resources above and any others you may find. I’ll be writing about more big data topics in the coming months, so look for me online, and feel free to leave a comment below.