Let’s just say that it’s time for us to be “out in the open with analytics” — pertaining to open source data. The new age explores the potential of combining the SAS software and its benefits with its open analytics. With this, there will be a clear exploration of how businesses can open their analytics program to all types of programming languages at all levels for users. This will ensure consistency in levelling which will automatically reflect in actions no matter where you start in the company.
SAS is now put up with today’s analytics technologies in conversation about open analytics and commercial analytics to be dramatically changed pertaining to the data conditions. To fully understand this, we first need to think about the entire analytics cycle which includes data preparation and deployment, data performance, data scalability and governance including algorithms.
within that cycle, there is an equally important role for both open source and commercial analytics. With Machine learning algorithms developing through SAS or Python there is a clear deployment in real-time data streams within SAS Event Stream Processing with an integration with open systems through Java and C APIs, RESTful web services, Apache Kafka, HDFS. Data scientists are branched from all sorts of backgrounds, having access to a variety of analytics system to govern and deploy models with access to more options for solving complex problems, in general.it also allows to explores topics like switching from open source technology to enterprise software and the benefits of using both parallelly.
With reports also covering topics like open source is gaining momentum in the new world of analytics, and learn from Navistar’s experience according to Gyasi Dapaa Director of Data Science Navistar also discusses the co-existence of both open source and enterprise software in today’s data-based world.