To achieve greater scalability and tighter integration with their enterprise data lake and cloud computing initiatives, many Netezza users are exploring various growth options. These options fall into two broad categories:
While switching to an IBM solution may seem to be the easiest option, it can create a proprietary vendor dependency that limits your flexibility to take advantage of the open source enterprise data lake or cloud investments you may be making. The flexibility to take advantage of modern data architecture technologies can deliver significant cost savings and near-infinite scalability. Enterprises can capitalize on this opportunity by offloading Netezza workloads to a Hadoop/Spark or cloud-based modern data architecture.
This webinar shows you how to put automation to work to reduce the cost, time, and risk of a large-scale transformation. Experts from Impetus also demonstrated a way to transform Netezza workloads to big data "automagically," using the industry's first automated workload transformation engine. This will be an interactive discussion followed by Q&A.
VP - Modern Data Architecture Practice, Impetus Technologies
Venkat has over 25 years of industry experience in big data analytics, data warehousing, ETL, and business intelligence. He is a trusted leader who collaborates with CIOs of Fortune 500 companies and acts as a global business architect and strategist to help gain new business insights through a better understanding of their data.
Product Manager – Data Warehouse Modernization Solutions, Impetus Technologies
Dhirendra is responsible for analyzing customer’s business challenges and mapping them to provide a secure, scalable, and robust solution leveraging big data technologies. He has extensive experience in big data technologies and advanced analytics such as BI, Hadoop, RDBMS, and machine learning.