IBM Netezza Performance Server is available on IBM Cloud , AWS , Azure and IBM Cloud Pak for Data Systems .
Can you explain more about how Netezza helps predict data warehousing costs , secures collaboration and automates maintenance and operations ?
Elastic scaling handles both planned and unplanned spikes in data warehouse requests or demand for computing power and helps accommodate these short-term needs while continuing to meet servicelevel agreements ( SLAs ) for downstream applications . Elastic computing also enables elastic pricing – you can scale up and down while only paying for what you use . The Netezza Performance Server is a cloud-based data warehouse that can be brought up and taken down with minimal investment in time and resources . Netezza provides you with the ability to move to the public cloud or augment your on-premises Netezza Performance Server for IBM Cloud Pak for Data System environment with data marts . For example , you can add cloud-based data warehousing resources for those few days each quarter when your regional offices need to run financial analyses .
What is the future of running complex analytics on very large data volumes with speed and simplicity ?
Data warehouses have a long history in decision support and business intelligence applications , though were not suited or were expensive for handling unstructured data , semi-structured data and data with high variety , velocity and volume . Data lakes then emerged to handle raw data in a variety of formats on cheap storage for data science and Machine Learning , though lacked critical features from the world of data warehouses : they do not support transactions , they do not enforce data quality and their lack of consistency / isolation makes it almost impossible to mix appends and reads , and batch and streaming jobs .
A data lakehouse is a new data management architecture that combines the flexibility , cost-efficiency and scale of data lake with the data management and
ACID transactions of data warehouses , enabling Business Intelligence ( BI ) and Machine Learning ( ML ) on all data .
Netezza Performance Server now makes it easy to perform analytics in your data lake using its robust massively parallel execution engine and SQL on Parquet capabilities .
What advice would you give to organisations who want to achieve their data goals while ensuring their warehouse is built for simplicity , sophistication , scale and speed ?
One of the biggest challenges facing organisations is having the expertise to cope with the changing data landscape and demands for more data . This is why we have invested so heavily in our team over the years to a point where we now have the largest certified team of IBM Netezza professionals outside of the US . Regarding advice , whatever technology or architecture works best for you , make sure you have a team capable of supporting your organisation throughout the design , build and run process . �
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