operational analytics

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Published By: Melissa Data     Published Date: Jan 18, 2018
Maintaining high quality data is essential for operational efficiency, meaningful analytics and good long-term customer relationships. But, when dealing with multiple sources of data, data quality becomes complex, so you need to know when you should build a custom data quality tools over canned solutions. To answer this question, it is important to understand the difference between rules-based data quality, where internal subject matter expertise is necessary – and active data quality, where different domain expertise and resources are required.
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Melissa Data
Published By: Alteryx     Published Date: May 24, 2017
Spreadsheets are a mainstay in almost every organization. They are a great way to calculate and manipulate numeric data to make decisions. Unfortunately, as organizations grow, so does the data, and relying on spreadsheet-based tools like Excel for heavy data preparation, blending and analysis can be cumbersome and unreliable. Alteryx, Inc. is a leader in self-service data analytics and provides analysts with the ability to easily prep, blend, and analyze all data using a repeatable workflow, then deploy and share analytics at scale for deeper insights in hours, not weeks. This paper highlights how transitioning from a spreadsheet-based environment to an Alteryx workflow approach can help analyst better understand their data, improve consistency, and operationalize analytics through a flexible deployment and consumption environment.
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Alteryx
Published By: Basho     Published Date: Nov 25, 2015
The landscape of Scalable Operational and Analytical Systems is changing and disrupting the norm of using relational databases for all workloads. With the growing need to process and analyze Big Data at Scale, the demand for alternative strategies has grown and has given rise to the emergence of NoSQL databases for scalable processing. Mike Ferguson, Managing Director of Intelligent Business Strategies, is an independent IT Analyst who specializes in Big Data, BI/Analytics, Data Management and Enterprise Business Integration. In this whitepaper he will discuss the movement towards NoSQL databases for scalable operational and analytical systems, what’s driving Big Data analytics from Hadoop to the emergence of Apache Spark, the value of operational analytics and the importance of in-memory processing, and why use Apache Spark as your in-memory analytical platform for operational analytics.
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Basho
Published By: Hewlett Packard Enterprise     Published Date: May 11, 2018
Digital transformation (DX) is a must for midsize firms (those with 100 to 999 employees) to thrive in the digital economy. DX enables firms to increase competitive advantage through initiatives such as automating business processes, creating greater operational efficiencies, building deeper customer relationships, and creating new revenue streams based on technology-enabled products and services. DX is a journey, and it starts with firms embracing an IT-centric vision that guides a data-driven, analytics-first strategy. The outcome of DX initiatives depends on the ability of a firm to efficiently leverage people (talent), process, platforms, and governance to meet the firm’s business objectives.
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Hewlett Packard Enterprise
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: Oracle CX     Published Date: Oct 20, 2017
With the growing size and importance of information stored in today’s databases, accessing and using the right information at the right time has become increasingly critical. Real-time access and analysis of operational data is key to making faster and better business decisions, providing enterprises with unique competitive advantages. Running analytics on operational data has been difficult because operational data is stored in row format, which is best for online transaction processing (OLTP) databases, while storing data in column format is much better for analytics processing. Therefore, companies normally have both an operational database with data in row format and a separate data warehouse with data in column format, which leads to reliance on “stale data” for business decisions. With Oracle’s Database In-Memory and Oracle servers based on the SPARC S7 and SPARC M7 processors companies can now store data in memory in both row and data formats, and run analytics on their operatio
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Oracle CX
Published By: ExtraHop     Published Date: Apr 03, 2013
The ExtraHop Discovery Edition is a free virtual appliance will help you to discover the performance of your applications across the network, web, VDI, database, and storage tiers. Get yours today!
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it operational intelligence, application performance management, application performance monitoring, application monitoring, network performance management, network performance monitoring, network monitoring, infrastructure performance monitoring, network monitoring, infrastructure performance monitoring, infrastructure monitoring, business transaction management, end-user experience monitoring, end-user monitoring, real-user monitoring, operations analytics, cloud performance monitoring, web performance monitoring, database performance monitoring, citrix performance monitoring
    
ExtraHop
Published By: Microsoft     Published Date: Oct 06, 2017
After rapid expansion of vendors and features, players in the operational DBMS market continue converging toward feature parity. Data and analytics leaders will be interested in the lack of Visionaries, competition in the Challengers quadrant and the maturing cloud capabilities among these vendors.
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data management, data system, business development, software integration, resource planning, enterprise management, data collection
    
Microsoft
Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 2017
"With the introduction of Oracle Database In-Memory and servers with the SPARC S7 and SPARC M7 processors Oracle delivers an architecture where analytics are run on live operational databases and not on data subsets in data warehouses. Decision-making is much faster and more accurate because the data is not a stale subset. And for those moving enterprise applications to the cloud, Real-time analytics of the SPARC S7 and SPARC M7 processors are available both in a private cloud on SPARC servers or in Oracle’s Public cloud in the SPARC cloud compute service. Moving to the Oracle Public Cloud does not compromise the benefits of SPARC solutions. Some examples of utilizing real time data for business decisions include: analysis of supply chain data for order fulfillment and supply optimization, analysis of customer purchase history for real time recommendations to customers using online purchasing systems, etc. "
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Oracle PaaS/IaaS/Hardware
Published By: CA Technologies     Published Date: Jul 20, 2017
e-book which lays out the case for machine learning and artificial intelligence for mainframe operational analytics. The mainframe is now part of a highly complex connected ecosystem driving trillions of mobile and web transactions critical to the functioning of the application economy. The emergence of new workloads and apps on the mainframe means that the status quo isn’t enough when it comes to Mainframe management. IT professionals alone – whether mainframe skilled or not – simply can’t keep up with the onslaught of performance alerts, false alarms. Machine learning deliver mainframe intelligence a more proactive and automated approach to handle this challenge.
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CA Technologies
Published By: Splunk     Published Date: Aug 17, 2018
IT organizations are now responsible for delivering seamless customer experiences while preventing outages and managing an increasing number of systems. With growing responsibility placed on IT, there is an opportunity to drive strategy for company-wide business processes and operations. Companies using machine data powered platforms like Splunk collect disparate data types to quickly troubleshoot and monitor systems. By adding predictive capabilities, IT can glean critical insights for the business and develop strategic initiatives on issues that matter. Download the white paper “Embracing the Strategic Opportunity of IT” to learn how to: Enable a business aware IT organization Unlock operational efficiencies Solve problems with predictive analytics
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it event management, it event management tool, event logs, aiops platform, what is aiops, aiops vendor, market guide for aiops platforms, guide for aiops platforms, monitor end to end, itoa, aiops, predictive analysis, machine learning, event correlation, event management, it operations analytics, it analytics, ibm watson, hp monitoring, hp operations manager
    
Splunk
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, business intelligence
    
IBM
Published By: IBM     Published Date: Feb 02, 2016
Energy firms should build and nurture a customer-centric culture delighting clients while maximizing operational and financial results. In doing so, we’ll highlight the crucial role analytics plays in helping energy firms ensure operational efficiency and customer satisfaction.
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ibm, energy, analytics, utility, customer experience, data, customer satisfaction, analytical applications
    
IBM
Published By: IBM     Published Date: Apr 11, 2016
This paper explores why your business needs the latest operational decision management (ODM) solutions to help turn data insights into action. Discover how IBM Operational Decision Manager software and the IBM Business Process Manager platform work together to: *Recognize patterns that suggest opportunity or risk *Create and shape business events by automating decisions *Bring more dimension and precision to decision making by applying analytics to big data *Help you implement the right business processes by understanding data in context.
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ibm, smarter process, operational decision management, odm, knowledge management, enterprise applications, business technology
    
IBM
Published By: IBM     Published Date: Apr 20, 2016
Energy firms should build and nurture a customer-centric culture delighting clients while maximizing operational and financial results. In doing so, we’ll highlight the crucial role analytics plays in helping energy firms ensure operational efficiency and customer satisfaction.
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ibm, customer experience management, cem, energy, utilities, energy sector, aberdeen group
    
IBM
Published By: Teradata     Published Date: May 12, 2015
We evaluate vendors that provide applications that integrate executional, operational and analytical marketing processes. Companies seeking a solution that integrates campaign management, marketing resource management and analytics should review this research.
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Teradata
Published By: Visier     Published Date: Nov 04, 2014
With workforce analytics, HR professionals can play a more pivotal role in their organizations to help direct senior management and hiring managers in connecting the dots between their company’s overall performance and their investment in their workforce. Workforce analytics empower HR professionals to shift from being an operational function to becoming more of a strategic role within their organization. Workforce analytics uncovers deep insights into workforce data by drilling down into the data and highlighting both patterns of success to be repeated and patterns of failure that could lead to risk and impact. Go from intuition- to fact-based workforce decision-making with this comprehensive guide to workforce analytics. This eBook includes advice on how to get started, tips to ensure successful implementation, and key recommendations for finding the right solution
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visier, workforce analytics, hr metrics, planning
    
Visier
Published By: IBM     Published Date: Oct 19, 2017
The Smarter Process platform is IBM’s solution for reinventing business operations in a way that infuses every process with intelligence and expertise to deliver greater customer centricity, which in turn fuels top-line growth. It incorporates Business Process Management, Case Management, Operational Decision Management and Process Analytics, along with Process Discovery and Design with an objective of ensuring that customers find it easy to do business and that every interaction includes positive touch points. Within the context of this new imperative, accessing cloud efficiencies, leveraging mobile for greater engagement, mining big data for insights, and enhancing customer relationships via social media, are proving to be critical and interrelated strategies.
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customer engagement, mobile, social, bpm, case management
    
IBM
Published By: Datastax     Published Date: May 14, 2018
The data management practices of old will no longer work. If you’re still trying to use a centralized approach, you are probably finding it difficult to keep up with the real-time demands of the Right-Now Economy. This special Gartner report describes the main drivers for modernizing data management — operational efficiency and analytics — and explains why balancing connecting data with collecting data will be a fundamental requirement for modern data management moving forward.
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Datastax
Published By: Alteryx, Inc.     Published Date: Apr 21, 2017
As a financial services provider, you have probably invested hundreds of thousands, if not millions of dollars, in building an analytic infrastructure. But, do your line-of-business analysts and managers have access to the data and insights they need, when they need them? Three ways Alteryx can help you improve customer experience, manage risk and increase operational efficiency Case studies on how your peer financial services companies are using self-service data analytics for a competitive edge
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Alteryx, Inc.
Published By: IBM     Published Date: Apr 16, 2018
In this on-demand webinar from the Institute of Management Accountants (IMA), Sherri Liao of The Hackett Group and Jim Collins of IBM discuss the steps your organization can take to link financial planning to operational decision making more effectively. You’ll hear about: Simplifying and amplifying reporting Optimizing decision-making: Predictive vs. historical analytics Aligning finance and operations Reporting beyond finance to include cross-functional measures of performance The path to building a World-Class finance organization
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operational planning, financial planning, planning analytics
    
IBM
Published By: IBM     Published Date: May 23, 2018
IBM Planning Analytics is the fast, flexible, planning solution that helps you align financial plans with corporate objectives linked to operational tactics and market events. In this quick, 10- minute guided demo, you’ll get hands-on experience with IBM Planning Analytics by building a book for revenue planning. You’ll play the role of a financial planner and learn how to: • Create a book for revenue planning in Planning Analytics Workspace • Adjust the plan by increasing sales through an online channel by 20% • Review the impact of your changes on net profit
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ibm planning analytics, revenue planning, income statement
    
IBM
Published By: IBM     Published Date: Jul 02, 2018
Digital transformation is not a buzzword. IT has moved from the back office to the front office in nearly every aspect of business operations, driven by what IDC calls the 3rd Platform of compute with mobile, social business, cloud, and big data analytics as the pillars. In this new environment, business leaders are facing the challenge of lifting their organization to new levels of competitive capability, that of digital transformation — leveraging digital technologies together with organizational, operational, and business model innovation to develop new growth strategies. One such challenge is helping the business efficiently reap value from big data and avoid being taken out by a competitor or disruptor that figures out new opportunities from big data analytics before the business does. From an IT perspective, there is a fairly straightforward sequence of applications that businesses can adopt over time that will help put direction into this journey. IDC outlines this sequence to e
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IBM
Published By: IBM     Published Date: Jul 16, 2018
IBM Planning Analytics, powered by IBM TM1, is the fast, flexible, planning solution that helps you align financial plans with corporate objectives linked to operational tactics and market events. In this quick, 10- minute guided demo, you’ll get hands-on experience with IBM Planning Analytics by building a revenue plan. You’ll play the role of a financial planner and learn how to: • Create a revenue plan in IBM Planning Analytics Workspace • Adjust the plan by increasing sales by 20% through an online channel • Review the impact of your changes on net profit
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IBM
Published By: Avi Networks     Published Date: Mar 07, 2018
"Maximizing Operational Efficiency and Application Performance in VMware-Based Data Center Some of the most common challenges in VMware-based virtual data center environments include: - Lack of visibility into applications and end-user experience - Complex and error-prone operations - High capital and operational costs Review our solution brief to learn how the Avi Controller, the industry’s first solution that integrates application delivery with real-time analytics, is able to solve these challenges."
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Avi Networks
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