Search: The Big Data Secret That No One's Talking About

Sometimes, when a new technology is introduced, it takes off in unexpected ways. It’s easy to get off track and lose focus of what the real intent and purpose behind the technology is. Such is the case with big data. As organizations seek to find all of the powerful ways that big data and data analytics can be used, a few of the more pertinent use cases go somewhat underutilized. With big data, the potent potential for search just may be a bit overlooked. Are you using search to its full potential?

It’s Not Too Sexy, But It Works

Search has almost fallen out of vogue in the era of Hadoop, Spark, and a growing but often convoluted collection of NoSQL databases. For many practical applications, it isn’t really necessary to delve into HBase, Flink, Splice Machine, or Couchbase. Search is a less sexy, but most definitely a more efficient, way to find working sets in memory.

There are several excellent tools available for search, including some super open source products like Elasticsearch. Solr, and others. It’s important to understand that tools like Spark aren’t the best to use specifically for search. However, from a data analytics standpoint, you can easily tack search onto a Hadoop infrastructure (or a strong machine library) and get more bang for your buck. You can also use search with your Spark operations.

Using Search to Create a Dynamic User Experience

Search is still an efficient and effective way for finding working sets within memory or for discovering I/O problems. It’s also a useful tool for security, and can be used to improve user experience. For example, it’s a great tool for grabbing more information about your users and for delivering an improved user experience by offering them the most relevant information for their purposes.

Use search to capture signals about your users and then create a dynamic user experience based on their behavior and preferences. By using search and indexes, you can take advantage of the front-end streaming analytics and use it to promote a better UX, without really having to get into machine learning before you’re ready for that. Search allows you to choose the right data according to the right criteria, and even personalize a user experience, without all of the data analytics that go behind machine learning.

Bigstep for Big Data

Bigstep’s Data Lake is fully integrated with all of your big data and search tools, including Hadoop, Spark, and almost all the popular NoSQL databases, including Couchbase, Cassandra, Elasticsearch, Solr, R, and more. The Bigstep solution is also compatible with your enterprise data warehouse solution.

What are you waiting for? Dive into the Bigstep Data Lake. The water’s just fine. See our products and find out more about how Bigstep is right for all your big data operations.