Leveraging Big Data to accelerate your Digital Transformation...

Leveraging Big Data to accelerate your Digital Transformation, Reduce Cost and Latency to Insight.

Today’s firms are inundated with data, but starving for insights. Visionary firms are not just looking to store and protect data. They are looking to extract insights providing them opportunities to:

• Innovate
• Mitigate Risk
• Reduce Operational Costs
• Enhance customer experience + loyalty
• Create new markets with digital-based assets
• Drive Revenue

The primary issue is that we have developed a series of fragmented analytic solutions where data scientists and business analysts spend more time moving and transforming data than building new models and extracting insights. #BigData breaks traditional architectures. A new approach is needed.

Numerous studies have demonstrated that the number one issue for NextGen analytic technologies (Spark, Hadoop, ELK stack, Splunk, HPC, etc.) is more of a data ingest issue than a compute issue.

Now firms are exploring artificial intelligence. A new workflow is needed. IBM has a solution that will allow you:
• Improve the degree of confidence in modeling
• Reduce the cost per simulation
• Increase the efficiency and utilization of existing analytic stacks
• Reduce CapEx + Opex
• Provide transparency to allow you to sent workloads to a true hybrid multi-cloud environment.

Our Speaker, Bob Gaines, is on the IBM Unstructured Data and big data analytic team for North America. His specialty is the Big Data; high-performance data analytics and heterogeneous computing environments; and helping customer evolve their big data analytic silos into an integrated and automated data pipeline with an open software-defined architecture.

Bob has a deep history in storage from the (StorageTek -> Sun Microsystems -> Oracle) where is managed the state, local, end education storage team for the US. He was regional VP for DDN Storage; Financial Services Managing Director for Seagate and Cray before being VP of sales for a technology spinoff of a capital markets trading firm.

He has spent the last 9 years helping financial firms build smarter algorithmic trading models and leveraged the apache analytic stack for anomaly detection for risk and compliance. He has an MBA from Loyola and data science continuing education certificate from MIT- School of Engineering.

He is a six sigma in TQM and leverages this requirements-based approach and detailed understanding of the customers' quantitative workflows to crafts solutions the reduce latency to insight; improve the degree of confidence in modeling; at a lower cost per simulation, driving improved data-driven business decisions and financial results.

He has been a speaker at many industry events:
• Chief Data Officer Conference
• Strat Big Data Conference
• STAC- Securities Technology Analysis Center
• HPC for WallStreet.
• SuperComputing Conference

We will have plenty of time for discussion and networking with your peers!