operationalizing analytics

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Published By: SAS     Published Date: Jan 17, 2018
This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.
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SAS
Published By: IBM     Published Date: May 17, 2016
Wikibon conducted in-depth interviews with organizations that had achieved Big Data success and high rates of returns. These interviews determined an important generality: that Big Data winners focused on operationalizing and automating their Big Data projects. They used Inline Analytics to drive algorithms that directly connected to and facilitated automatic change in the operational systems-of-record. These algorithms were usually developed and supported by data tables derived using Deep Data Analytics from Big Data Hadoop systems and/or data warehouses. Instead of focusing on enlightening the few with pretty historical graphs, successful players focused on changing the operational systems for everybody and managed the feedback and improvement process from the company as a whole.
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ibm, big data, inline analytics, business analytics, roi
    
IBM
Published By: SAS     Published Date: Jun 27, 2019
The potential for analytics to transform health care – to make it more personalized, intelligent, cost-efficient and effective – is immense. The question is, how will you move your organization forward to exploit the power of analytics? In this paper, explore recommendations and best practices from experts at UnitedHealth Group, Eli Lilly and Company, and Mercy Virtual who are operationalizing SAS analytics across their enterprises and realizing impressive results.
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SAS
Published By: SAS     Published Date: Aug 13, 2018
You may know some data management basics, but are you aware of the transformational results that can result from doing data management right? This paper explains core data management capabilities, then describes how a solid data management foundation can help you get more out of your data. Fraudsters are only becoming smarter. How is your organization keeping pace and staying ahead of fraud schemes and regulatory mandates to monitor for them? In this e-book, learn the basics in how to prevent fraud, achieve compliance and preserve security.
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SAS
Published By: SAS     Published Date: Jan 04, 2019
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment. Newer examples of operational analytics include support for logistics, customer call centers, fraud detection, and recommendation engines to name just a few. Embedding analytics is certainly not new but has been gaining more attention recently as data volumes and the freq
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SAS
Published By: IBM     Published Date: Jan 05, 2015
Ziff Davis recently surveyed over 300 IT professionals on the state of big data and analytics initiatives in their organizations. The results tell a compelling story: while most IT pros understand the value of big data, actually operationalizing their analytics strategies to deliver usable insights to their organizations remains a challenge.
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big data, it professionals, analytics initiatives, analytics strategies, analytic solutions
    
IBM
Published By: SAS     Published Date: Sep 30, 2014
When Information Revolution1 was published in 2006, no Chinese based companies were among the top 10 largest companies by market capitalization. Apple didn’t sell phones. Facebook was something college kids used to connect with their friends. Back then, we talked a lot about the amount of data coming in and faster processing speed. What we believed then remains true today: Data, and the decision-making process, can be moved throughout the organization to equip every decision maker (automated, line worker, analyst, executive) to make the best choices. By operationalizing analytics, organizations can identify and quantify both opportunity and risk. Information Revolution highlighted SAS’ Information Evolution Model, which helps organizations understand how they interact with their information and how to extract more value from it through analytics.
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sas, organizational insights, operationalizing analytics, sas’ information evolution model
    
SAS
Published By: SAS     Published Date: Jun 05, 2017
This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.
Tags : 
    
SAS
Published By: SAS     Published Date: Aug 03, 2016
As the pace of business continues to accelerate, forward-looking organizations are beginning to realize that it is not enough to analyze their data; they must also take action on it. To do this, more businesses are beginning to systematically operationalize their analytics as part of a business process. Operationalizing and embedding analytics is about integrating actionable insights into systems and business processes used to make decisions. These systems might be automated or provide manual, actionable insights. Analytics are currently being embedded into dashboards, applications, devices, systems, and databases. Examples run from simple to complex and organizations are at different stages of operational deployment.
Tags : 
best practices, embedding analytics, technology, data, operational analytics
    
SAS
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