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        Analyst Perspectives

        The need for businesses to process and analyze data has grown in intensity along with the volumes of data they are amassing. Our benchmark research consistently shows that preparing data is the most widespread impediment to analytic and operational efficiency. In our recent research on data and analytics in the cloud, more than half (55%) of organizations said that preparing data for analysis is a major impediment, followed by other preparatory tasks: reviewing data for quality and consistency...

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        Topics: Big Data, Sales Performance, Supply Chain Performance, Human Capital, Marketing, Monarch, Operational Performance Management (OPM), Customer Performance, Business Analytics, Business Intelligence, Business Performance, Data Preparation, Financial Performance, Governance, Risk & Compliance (GRC), Information Management, Uncategorized, Business Performance Management (BPM), Datawatch, Information Optimization, Risk & Compliance (GRC)

        PentahoWorld 2015, Pentaho’s second annual user conference, held in mid-October, centered on the general availability of release 6.0 of its data integration and analytics platform and its acquisition by Hitachi Data Systems (HDS) earlier this year. Company spokespeople detailed the development of the product in relation to the roadmap laid out in 2014 and outlined plans for its integration with those of HDS and its parent Hitachi. They also discussed Pentaho’s and HDS’s shared intentions...

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        Topics: Big Data, Pentaho, Mobile Technology, Wearable Computing, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, IOT, Operational Intelligence, Uncategorized, Information Optimization, Risk & Compliance (GRC)

        The importance of product information management (PIM) has become clear in recent years and especially as it relates to master data management. As I recently wrote handling this business process effectively and using capable software should be priorities for any organization in marketing and selling its products and services but also interconnecting the distributed supply chain. Our research on product information management can help organizations save time and resources in efforts to ensure...

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        Topics: Big Data, Master Data Management, Sales Performance, Supply Chain Performance, Enterworks, Marketing, Operational Performance Management (OPM), Stibo Systems, Webon, Business Performance, CIO, Financial Performance, IBM, Informatica, Information Management, Oracle, Information Optimization, Product Information Management, Riversand

        Ventana Research defines product information management (PIM) as the practice of using information, applications and other technology to effectively support product-related processes across the customer, commerce and supply chain. As organizations increase the number and diversity of products and services they offer to customers and partners, they increasingly need to address limitations in the ways they manage and distribute product information, including related attributes and content that...

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        Topics: Big Data, Master Data Management, Supply Chain Performance, Governance, Marketing, Operational Performance Management (OPM), CIO, Information Management, Business Performance Management (BPM), Financial Performance Management (FPM), Information Optimization, Product Information Management, Sales Performance Management (SPM)

        Splunk’s annual gathering, this year called .conf 2015, in late September hosted almost 4,000 Splunk customers, partners and employees. It is one of the fastest-growing user conferences in the technology industry. The area dedicated to Splunk partners has grown from a handful of booths a few years ago to a vast showroom floor many times larger. While the conference’s main announcement was the release of Splunk Enterprise 6.3, its flagship platform, the progress the company is making in the...

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        Topics: Big Data, Predictive Analytics, Machine Learning, IT Analytics & Performance, Operational Performance, Plunk, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Management, Internet of Things, Operational Intelligence, Data, Information Optimization

        The concept and implementation of what is called big data are no longer new, and many organizations, especially larger ones, view it as a way to manage and understand the flood of data they receive. Our benchmark research on big data analytics shows that business intelligence (BI) is the most common type of system to which organizations deliver big data. However, BI systems aren’t a good fit for analyzing big data. They were built to provide interactive analysis of structured data sources using...

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        Topics: Big Data, Predictive Analytics, Software as a Service, IT Analytics & Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Management, Operational Intelligence, Data, Information Optimization

        As I discussed in the state of data and analytics in the cloud recently, usability is a top evaluation criterion for organizations in selecting cloud-based analytics software. Data access of cloud and on-premises systems are essential antecedents of usability. They can help business people perform analytic tasks themselves without having to rely on IT. Some tools allow data integration by business users on an ad hoc basis, but to provide an enterprise integration process and a governed...

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        Topics: Big Data, Sales Performance, Software as a Service, Mobile Technology, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Information Management, Operational Intelligence, Data

        Optimization is the application of algorithms to sets of data to guide executives and managers in making the best decisions. It’s a trending topic because using optimization technologies and techniques to better manage a variety of day-to-day business issues is becoming easier. I expect optimization, once the preserve of data scientists and operations research specialists will become mainstream in general purpose business analytics over the next five years.

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        Topics: Big Data, Performance Management, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Performance, Financial Performance, Information Management, Price Optimization

        Ventana Research recently completed the most comprehensive evaluation of analytics and business intelligence products and vendors available anywhere. As I discussed recently, such research is necessary and timely as analytics and business intelligence is now a fast-changing market. Our Value Index for Analytics and Business Intelligence in 2015 scrutinizes 15 top vendors and their product offerings in seven key categories: Usability, Manageability, Reliability, Capability, Adaptability, Vendor...

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        Topics: Big Data, Data Quality, Predictive Analytics, Gartner, Governance, Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Applications, Information Management, Operational Intelligence, Value Index, Strata+Hadoop

        Just a few years ago, the prevailing view in the software industry was that the category of business intelligence (BI) was mature and without room for innovation. Vendors competed in terms of feature parity and incremental advancements of their platforms. But since then business intelligence has grown to include analytics, data discovery tools and big data capabilities to process huge volumes and new types of data much faster. As is often the case with change, though, this one has created...

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        Topics: Big Data, Data Quality, Predictive Analytics, Gartner, Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Applications, Information Management, Value Index, Strata+Hadoop
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        Our Analyst Perspective Policy

        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

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