On-Demand Webinar: Next Steps for Filling Your Data Lake (Sponsored by Pentaho*)

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With disparate data sources of data often numbering in the hundreds or thousands, hand coding to connect to each source is time-consuming and difficult to manage and maintain. Pentaho simplifies and automates the process of getting your big data into your data. Watch this webinar and learn how Pentaho helps you to: • Simplify and

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Categories: Data Center, Webcasts

Big Data Management Guide Eight Essential Checklists for Managing the Analytic Data Pipeline

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Are you tasked with transforming your data into true business value? Don’t miss our new data management guide: 8 Essential Checklists for Managing the Analytic Data Pipeline. Each step is a critical to ensuring your data is analytics-ready when business users need it. Use the guide to evaluate your vendor options and flag potential pitfalls

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TDWI Checklist Report: Emerging Best Practices for Data Lakes

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Designing a data lake that meets both business and technology goals is critical, but not easy. From the great size and diversity of data within a data lake, to the need to support a wide range of interfaces, platforms, data structures, and processing methods, too often data lakes turn into a messy data swamp, and

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Market Guide for IoT Integration

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IoT project implementers cite integration as a top technical challenge. To help determine which IoT integration offerings best match their IT project requirements, IT leaders must understand that IoT integration requirements differ and that integration capabilities of IoT solutions vary widely.

2016 Dresner Big Data Analytics Market Study (Sponsored by Pentaho*)

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Based on survey methodology, this second Big Data Analytics Market Study from Dresner Advisory focuses upon the combination of analytical solutions within the Hadoop ecosystem, adding some new criteria and exploring changing market dynamics and user perceptions and plans. You’ll also learn why Pentaho ranked among the top three Big Data Analytic vendors in the

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Hadoop Infographic: Hadoop and the Analytic Data Pipeline (*Sponsored by Pentaho)

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Need some inspiration on Hadoop? Pentaho’s step-by-step interactive infographic shows how you can handle common Hadoop challenges at every stage of the analytic data pipeline. Check out the infographic and learn how to: • Develop a flexible and scalable approach to data ingestion and onboarding processes • Scale your data processing and blending efforts, while

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Embedded Analytics Vendor Selection Guide, A Holistic Evaluation Criteria for Your OEM Analytics Project

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This whitepaper covers six guidelines product leaders should explore during their embedded analytics evaluation: 1) Data Access, Integration, and Management, 2) End User Analytics Functionality, 3) Embedding Analytics into the Application User Interface, 4) Deployment and Security, 5) Extensibility, Customization, and Transparency, and 6) Services, Support, and Vendor Experience. Content covers: • Key requirements and

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TDWI Best Practices Report: Improving Data Preparation for Business Analytics (Sponsored by Pentaho*)

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Want to get the data you need faster? If you’re trying to automate and scale your data preparation processes, this TDWI Best Practices Report is a must-read. The TDWI report also examines how self-service data preparation will affect your operations, including how self-service data prep fits with visual analytics, data discovery, BI tools, and Hadoop.

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Buying vs. Building Business Analytics

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Providing analytics functionality to your end users can create a number of benefits – such as higher user satisfaction, competitive advantages for your business, and accelerated overall growth. As a part of this process, almost every development organization is faced with a fundamental question – whether to build the required analytics functionality in-house or to

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TDWI Best Practices Report: Next-Generation Analytics and Platforms

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Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics,

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