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Can you explain more how Netezza helps predict data warehousing costs , secures collaboration and automates maintenance and operations ?

• Getting real-time Insights . Another pain point is getting realtime insights . When we move from analyzing static data to handling inputs in real-time , a great deal of complexity is added . While

innovations such as fully automated Extract , Transform , and Load ( ETL ) engines make life easier , there is still a long way to go for organizations looking to use real-time insights .

• Siloed Analytics and Competing Results . If one department of an organization has access to certain types of information and other departments don ’ t , then this could provide skewed results across the organisation .

• Lack of Skills to Interpret and Apply Analytics in Business Context . Even if an organization has the required technical staff , the lack of skills to interpret and use analytics among business staff can be another significant barrier to effectively using data and making data-driven decisions .

• Data Governance and Security . Companies source data for decision-making from many internal and external data sources . However , the governance of this data is very much an issue . Another data challenge for organizations is ensuring their security and integrity . Due to the criticality of the data , even a minor incident can result in enormous losses for the organization .

What is the next generation of IBM Netezza Performance Server and what is it doing to make it accessible to everyone across cloud , hybrid and on-premises deployments ?

IBM Netezza Performance Server is the advanced cloud-native data warehouse designed for unified , scalable analytics and insights available anywhere . Built with data lake integration , Netezza Performance Server empowers you to run highly complex queries and machine learning to support critical business decisions across your organization . It provides a secure , and scalable source for your analytics that is simple to use and flexible enough to run demanding analytical workloads across fully managed cloud , hybrid and onpremises environments .

IBM Netezza Performance Server is available on IBM Cloud ®, AWS , Azure and IBM Cloud Pak ® for Data Systems .

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 service-level 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 United States . Regarding advice , whatever technology or architecture works best for you , make sure you have a team capable of supporting your organization throughout the design , build and run process . p

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