MicroStrategy version 10 enables big data engine support

With this new release MicroStrategy continues to expand their integrated software suite covering all styles of information access including

• data discovery with a new data wrangling capability
• data visualisation now with D3 library visualisation integration
• advanced analytics using a comprehensive library of predictive algorithms
• interactive dashboards with a new easy to use HTML5 interface
• mobile BI and enterprise reporting

No data left behind

MicroStrategy now ships with a new and growing list of native connectors. These include Hadoop in all its various flavours, Facebook, Twitter and Google Analytics. This new access to big data and cloud-based data sources anticipates growing demand from organisations embarking on big data projects.

MicroStrategy 10 now offers direct connectivity to the Hadoop Distributed File System (HDFS) via the MicroStrategy developed Big Data Engine. This is useful for organisations that are deploying data lakes using Hadoop. This software runs as an Apache Hadoop Yarn application and can provide direct access to the Hadoop HDFS. This is a much faster interface than the Hive ODBC connection and it can consume both structured and unstructured data from Hadoop.

‍

The data lake

According to the 2014 Gartner Hadoop usage survey results the number one deployment for big data solutions is the data lake -  a centralised repository that can ingest and store unstructured, semi-structured and structured data for the enterprise to access and analyse. Gartner shows the data lake is being used according to the following distribution:

• 53 percent are doing interactive SQL
• 18 percent are running database management systems
• 14 percent are doing stream processing
• 9 percent are running search
• 6 percent are running graph applications e.g. GraphX

‍

More than half of all respondents use SQL to access data from their Hadoop solution.

The data lake is now recognised as an essential component of any modern information management environment and it complements the existing enterprise data warehouse and data integration processing. Typically a data lake with non-relational data will contain raw internal and external data that can be accessed directly for data exploration, search, prototyping and visualisation. In contrast the enterprise data warehouse will contain high quality relational data that has been loaded, quality checked and structured to support dashboards and enterprise reporting. There may be data in the EDW sourced from the data lake using data warehouse extract, transform load (ETL) tools.

MicroStrategy 10 offers a great solution for organisations embarking on the big data journey.