A further look at the Total Value of Ownership for Enterprise Data Warehouses
Myriad obstacles confront the enterprise data warehouse (EDW) environment, including exponentially greater data volume, the challenges of maintaining data quality and acquiring cloud-savvy expertise. Our first of three blogs in this series explored types of data warehouses suitable for the enterprise Journey to AI.
With these challenges in mind, a recent analysis from Cabot Partners compared five data warehouse solutions, including a total value of ownership (TVO) framework to determine how well these offerings met a variety of EDW needs.
The first two components of TVO – total cost of ownership and productivity improvements – discussed previously, highlighted Netezza® Performance Server on IBM® Cloud Pak® for Data a clear leader. This blog explores the second set of these components, revenue/profits and risk mitigation.
Boosting revenue/profits with smart solutions
Revenue and profits determine the speed solution improvements can be made, the time available for value-added activities – rather than effort spent on routine maintenance – and the additional capabilities that can be integrated into a unified solution.
Containerized EDW solutions help businesses launch solutions more quickly and begin producing ROI as soon as possible because they eliminate the need for an appliance deployment. And businesses upgrading to NPS from previous Netezza models like Mako, Twinfin, and Striper will realize a simpler transition. Most can migrate with a single command: “nz_migrate”. The shorter the migration time, the sooner the return on investment of updated features and functionality.
Another vital capability that helps ensure users spend their time on adding value rather than maintenance is the automation of tuning and administration within the EDW. Data scientists can deliver actionable insights rather than spend time prepping and cleaning data. For example, NPS Snippet Processing Units (SPU) are managed by OpenShift; once workloads are built and tested, OpenShift can easily deploy to new environments. No rework is required, even on a new cloud platform. And ease of scale – up to petabyte capacity – ensures users need never worry about running out of room.
The tools data scientists use to distill useful information from the EDW can boost revenue and profits directly. These include Jupyter notebook, RStudio, popular coding languages, and a variety of AI and analytics tools like Streams flow editor, SPSS modeler, AutoAI. A platform with native tools and capabilities helps deliver more power thorough integration.
Using data governance to mitigate risk
Data governance poses one of the most significant challenges for the modern EDW. Businesses must balance quick access for authorized users with the challenges of correct cataloguing, tracking and identity masking. And they must be able to apply AI with as few complications as possible in a governed environment. A platform with automated data discovery and classification empowers data scientists to spend less time on prep and more time on science; and for stewards to ensure better usage of data across the organization, the same capabilities provide simplified oversight of sensitive data masking and better control over data zone and life cycle management. Powered by Watson, IBM Watson Knowledge Catalog provides added data discovery and locates relevant curated data via intelligent recommendations and user reviews. And IBM Watson OpenScale tracks and measures outcomes from AI and ML models across their life cycles.
Risk-mitigating capabilities work best as native elements or extensions in an integrated platform. Cobbling together solutions from diverse – or even the same – vendors can introduce integration problems that may increase, rather than mitigate, risk. And Netezza Performance Server on IBM Cloud Pak for Data proves superior to its competitors across TCO, productivity, revenue/profits and risk mitigation.
“NPS which includes IBM Cloud Pak for Data System is outperforming competitors and fast-tracking the delivery of client value in their advanced analytics and AI journey.” – Cabot Partners
Explore total value of ownership in greater depth
Please read Cabot Partner’s complete evaluation for the full story. And watch for our comparison of Netezza Performance Server to its competitors across five different architectural layers of a modern EDW: modernization, infrastructure, enterprise-readiness, data management, and analytics.