Big data is no longer optional for business. Forbes reported that 79 percent of executives think that companies that don’t pursue big data will face tough challenges, possibly even being driven out of business.

Companies that don’t want to meet that fate need to figure out how to tackle the many challenges of working with that data. While finding talent and developing useful analytics programs is obviously key, there are also many challenges related to storing that data.

  1. Where do you store big data? The cloud has been an answer to many companies’ demand for big data storage. But big data storage isn’t just about expanding to provide the needed capacity. Big data storage needs to meet high performance requirements to enable large-scale analytics programs to reveal usable insights in a timely manner.
  1. How do you manage big data? Traditional SQL databases aren’t necessarily well suited to big data, which includes many unstructured data sources as well as conventional ones. While most companies have developed expertise in relational database management, they lack equivalent skills in NoSQL databases that are designed for object storage. This makes it difficult to make smart decisions about the best tools to use for big data storage and management.
  1. How do you keep big data consistent? With data coming from so many sources and used to support high-level decision-making, ensuring that data is consistent is both necessary and extremely complicated. Data models need to be aligned and synchronization processes implemented to make sure the data fed into applications yields valid insights.
  1. What’s the big data lifecycle? Deciding how long to keep your data has a big impact on how much storage you need. Some would say data should never be discarded because you can’t tell what will be valuable later on, but you’ll likely at least want to put older data in cold storage. You need a process that will handle data as it ages.
  1. How will you keep your big data secure? Security issues scale in parallel with the data. Because big data is often used in exploratory projects, it’s difficult to control access based on need. There’s also a lot of personally identifiable information in these data sets, and it needs to be protected. Even the insights big data generates may require sensitive handling to avoid situations like when Target revealed a teenage girl’s pregnancy to her family.

Once you understand the challenges of managing big data, you can start exploring the technical solutions that enable you to collect, control, and use it. Your options include hyperconverged infrastructure in your data center and cloud. Either solution can be cost effective as long as your team fully understands how to support and manage the infrastructure.

dcVAST’s expert team can help you analyze your big data storage requirements and work with you to develop and implement a solution. We provide managed Nutanix and managed Amazon Web Services to ensure your chosen strategy is optimized and efficient. Contact us to start figuring out the answers to your big data storage questions.