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In their wisdom, the editors of the book decided that I wrote “too much” So, they correctly shortened my contribution by about half in the final published version of my Foreword for the book. I publish this in its original form in order to capture the essence of my point of view on the power of graph analytics.
Multi-channel publishing of data services. What is the cost and ROI of Data Virtualization? The ROI is obtained by savings in the cost of hardware, software, storage, development and maintenance. Prescriptiveanalytics. Real-time information. Agile requirements and fast deployment times.
PrescriptiveAnalytics. Increase in ROI. Features: intuitive visualizations on-premise and cloud report sharing dashboard and report publishing to the web indicators of data patterns integration with third-party services (Salesforce, Google Analytics, Zendesk, Azure, Mailchimp, etc.). SAP Lumira.
It includes predictive and prescriptiveanalytics and is used to gain insight into data and plan for the future using sophisticated features like key influencer analytics, sentiment analysis, embedded business intelligence, assisted predictive modeling, anomaly alerts, natural language processing (NLP) for simple search analytics and other features.
This was for the Chief Data Officer, or head of data and analytics. Gartner also published the same piece of research for other roles, such as Application and Software Engineering. Try this: Tie Your Data and Analytics Initiatives to Stakeholders and Their Business Goals. We have published some case studies.
Return on Investment Now we bring it all together to calculate the ROI on embedded analytics. Costs: The investment in developing and maintaining the solution. “-1”: The formula assures that a positive ROI is achieved only when benefits exceed the costs. Benefits: The combination of strategic benefits (e.g., cost reduction).
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