Big Data science
Making better sense of Big Data
“Big Data” does not have to imply “Big Hardware”
Our SAx platform has been meticulously optimized to achieve massive data processing and analysis capabilities with minimal hardware.
SAx is designed to process many billions of events per day with a small handful of servers. Unlike traditional Hadoop systems that require large numbers of servers for even introductory analytics capabilities, SAx does more with much less than a Hadoop-based infrastructure.
Store the needle, not the haystack
As data management systems continue to mature, more and more individual interactions and events are being captured. The result is ever-increasing volumes of data to analyze.
Storing all of this content in raw form becomes very cost ineffective and unmanageable. SAx is designed to analyze these massive streams of raw data, extract the content that is of value, enrich that content, and discard the content that has no business value or significance.
This process results in data flows that are drastically reduced in volume, yielding data sets that are both manageable and rich in value. We are domain experts. We rely on our countless years of experience working in the telecommunication industry analyzing data to know what to keep and what to discard. This is core to the SAx DNA.
Get answers now, not later
Speed of data analytics is core to the SAx foundation. Speed is critical on both the data ingest side as well as the data output side. SAx uses cutting edge technologies and proprietary methodologies to drink from the proverbial fire hose.
Our solution is capable of ingesting and enriching data flows at mind-blowing rates, in the order of 100k records per second per server. Our data modeling advancements allow us to structure vast volumes of data for immediate results. Leveraging Big Data to answer business questions is only of business value if the answers are achievable in reasonable amounts of time.
SAx has been designed to answer those important business questions in seconds, as opposed to the minutes or hours you might wait on getting similar answers from Hadoop-based systems.