Self-service analytics lets business users intuitively perform ad hoc reporting and analysis on data and has been part of mainstream BI for years. However, traditional BI tools simply don’t work well against the new breed of big data platforms such as Hadoop and NoSQL databases.
Here are questions to ask when looking for easy, self-service analytics for big data platforms.
Do you have more than one big data store?
Big data analytics tools must be capable of self-service analytics against not just a single big data platform like Hadoop but also multiple big data platforms. Over time, most organizations will support multiple big data stores.
Do you want to use the same tool for big data stores and traditional relational data stores?
Big data analytics tools must support both traditional, relational data stores and big data. Otherwise, data must be loaded from traditional stores into the big data stores. For example, moving data from a low-latency relational database into high-latency but highly scalable Hadoop.
Do you have hours to access your big data?
Traditional BI tools take the lowest common denominator approach to integrating with big data platforms, for example using Hive with Hadoop. “Batch oriented” interfaces make it impossible to perform speed-of-thought analysis.
For self-service big data analytics, Pentaho offers Instaview for instant and interactive analysis of all the most popular big data platforms and more traditional stores with excellent performance. Instaview is part of the Pentaho Business Analytics platform that includes additional big data capabilities ranging from reporting to predictive analytics.