A Complete Guide to Overcoming Executives’ Concerns about Hadoop
CEOs are often critical of adopting new technology, and for good reason. New technology is expensive and all too often fails to come through and offer any real value to the company.
CEOs are often critical of adopting new technology, and for good reason. New technology is expensive and all too often fails to come through and offer any real value to the company. This could present a challenge for IT managers who want to implement Apache Hadoop, the increasingly popular and cost-effective framework for large-scale, data-intensive deployments, into the company’s technology infrastructure. Here are some common concerns regarding Hadoop as well as additional information to help executives make an informed decision.
Open source products are not enterprise-friendly.
For a Hadoop platform to be truly enterprise-friendly, it needs to offer businesses enterprise-grade features. MapR provides all of these features, including high availability, disaster recovery, security, and full data protection. Our advanced platform also allows Hadoop to be accessed easily as traditional network-attached storage with read-write capabilities.
We already have a data warehouse in place.
Most businesses only keep samples of their data because it is too costly to keep all of it in a relational database. This means that the when business needs change or new questions arise which require larger or different data sets, the raw data is no longer available for analysis. Hadoop, on the other hand, can be used as a complete and accessible data hub that can store all of a company’s data – structured, semi-structured, and unstructured – and let companies access it at anytime as business needs change.
Hadoop does not offer real-time analytical tools.
One of the main reasons to use Hadoop is to be able to access Big Data and garner valuable business insights from that data. Many vendors sell enterprise-ready analytical tools, and one distribution in particular allows customers to perform predictive analytics, full search and discovery, and conduct advanced database operations. This integrated search capability provides real-time analytics and discovery for Big Data.
Switching to Hadoop will be too expensive.
Every piece of technology comes with an upfront cost, but Hadoop is much more cost effective for storing large volumes of data. Data that used to be considered too expensive to store can now be made available for analysis at a much lower cost on a per-terabyte basis. In addition, Hadoop doesn’t require expensive hardware or high-end processors. Any type of commodity server can hook into a Hadoop network and work just fine. As companies explore more use cases with Hadoop, they will discover that Hadoop is usually a more cost-effective and faster solution than standard SQL databases.
We don’t have the expertise in this area.
Hadoop has a forum to go to for support, and several Hadoop vendors also offer full technical support and professional services to help you get the most out of your Hadoop investment. In addition, several vendors offer enterprise-ready Hadoop distribution packages that make Hadoop easy to install, configure and run, eliminating the need for bringing data scientists on board.
I don’t trust data to make business decisions.
This may be one of the most difficult objections to overcome, but the truth is Hadoop offers access to volume and types of data that were not easily accessible before. With Hadoop, data can now be made available to improve business insights, and these new insights have the potential to impact operations, marketing, product innovation and security, as well as many other aspects of one’s business. In the end, leveraging big data will have a significantly positive impact on ROI.
Were there any concerns that I missed? How have you convinced your business leaders to move forward with a Hadoop solution?
To learn more download The Executive’s Guide to Big Data & Apache Hadoop for free here.
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