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TDWI Predictive Analytics Fundamentals

Extend your analytics program from gaining insight to providing foresight with this great introduction to predictive analytics skills.

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Research & Resources

  • 7 Tips to Succeed with Big Data Tableau white paper 7 Tips to Succeed with Big Data thumb

    Download this white paper to learn seven new ways to achieve success with big data. more

  • 3 Shifts in the Modern Data Environment (And What It Means for IT Leaders) Tableau white paper 3 Shifts in the Modern Data Environment thumb

    Download this white paper to understand the three shifts within the modern data environment that are critical to becoming a data-driven organization. more

  • Benchmark Your BI Environment for Continuous Improvement Birst white paper Benchmark Your BI Environment thumb

    Download this white paper to measure and assess the efficiency and effectiveness of your organization's business intelligence environment. more

  • Five Common Hadoopable Problems Cloudera white paper Five Common Hadoopable thumb

    Download this white paper to learn how organizations are harnessing the power of Apache Hadoop. more

  • TDWI Best Practices Report | Master Data Management: Consensus-Driven Data Definitions for Cross-Application Consistency

    Although MDM has long been done in a few isolated silo applications, companies now practice it in more silos and with more connections among silos. Forward-looking companies even practice enterprise MDM, with a broad scope across many applications and businesses. As with many data management practices, the general trend in MDM is toward broader and better integrated enterprise scope. more

  • TDWI Best Practices Report | Predictive Analytics: Extending the Value of Your Data Warehousing Investment TDWI Best Practices Report Q1 2007

    This report is designed for the business or technical manager who oversees a business intelligence (BI) environment and wishes to learn the best practices and pitfalls of implementing a predictive analytics capability. The report defines predictive analytics as a form of BI that uncovers relationships and patterns, within large volumes of data, that can be used to predict future behavior and events. Unlike other BI technologies, predictive analytics is forward-looking, using past events to anticipate the future. more

  • TDWI Best Practices Report | BI Search and Text Analytics: New Additions to the BI Technology Stack TDWI Best Practices Report Q2 2007

    This report details how the expansion of the technology stack for business intelligence (BI) and data warehousing (DW) accommodates two relatively new additions, namely BI search and text analytics. Although each stands ably on its own, the two are related in that they tend to operate on unstructured data. Unstructured data is playing a larger role in BI and DW over time, and that role is today supported largely by tools and techniques for BI search and text analytics. more

  • TDWI Best Practices Report | Best Practices in Operational BI: Converging Analytical and Operational Processes TDWI Best Practices Report Q3 2007

    Operational business intelligence (BI) represents a turning point in the evolution of BI. Traditionally, BI has been the province of technically savvy business analysts who spend many hours with sophisticated tools analyzing trends and patterns in large volumes of historical data to improve the effectiveness of strategic and tactical decisions. But operational BI changes this equation: it moves BI out of the back room and embeds it into the fabric of the business, intertwining it with operational processes and applications that drive thousands of daily decisions. This report describes the promise of operational BI and provides suggestions about how to surmount the challenges involved in converging operational and analytical processes. more

  • TDWI Best Practices Report | Business Intelligence Solutions for SAP TDWI Best Practices Report Q4 2007

    Providing business intelligence (BI) solutions for a business that uses SAP software continues to confound many users because of the long list of available options and the inherent complexity of such an undertaking. Yet, organizations need to clear these hurdles so they can benefit from a BI solution that provides visibility into business processes supported by applications from SAP and other vendors. This isn’t a new issue, but SAP customers need to revisit their BI solutions for SAP now, because many are old and need updating. In addition, new products and releases—from SAP and other vendors—have introduced more BI tool options. more

  • TDWI Best Practices Report | Strategies for Managing Spreadmarts: Migrating to a Managed BI Environment TDWI Best Practices Report Q1 2008

    In organizations all over the world, business people bypass their IT groups to get data from spreadmarts. Spreadmarts are data shadow systems in which individuals collect and massage data on an ongoing basis to support their information requirements or those of their immediate workgroup. These shadow systems, which are usually built on spreadsheets, exist outside of approved, IT-managed corporate data repositories, such as data warehouses, data marts, or ERP systems, and contain data and logic that often conflict with corporate data. Once created, these systems spread throughout an organization like pernicious vines, strangling any chance for information consistency and reliability. You’ll find them in all industries, supporting all business functions. According to TDWI Research, more than 90% of all organizations have spreadmarts. more

  • TDWI Best Practices Report | Data Governance Strategies: Helping your Organization Comply, Transform, and Integrate TDWI Best Practices Report Q2 2008

    Any time data crosses an organizational boundary, it should be governed, whether you’re sharing data among business units internally or publishing data to customers, partners, auditors, and regulatory bodies externally. Organizations are under renewed pressure to ensure that compliance and accountability requirements are met as the scope of data integration broadens. In response to this situation, many organizations are turning to data governance, which establishes policies and procedures for sharing data, as well as improving data’s quality, structure, and auditability. more

Upside

Webinar

  • Enabling Self-Service Analytics with Intelligent Data Integration

    One of the strongest trends in information technology (IT) today is self service, which puts the power of creating data-driven solutions in the hands of the business user. This way, IT organizations are offloaded; they needn’t create unique datasets, reports, and analyses per user, which frees up IT’s time for other tasks. Furthermore, a broad range of end-users – mostly mildly technical business people – needn’t wait for help from IT, thereby giving them greater agility and creativity, while reducing the time to value and allowing them to apply their business expertise to a well-targeted solution. Therefore, self service is a win-win situation – but only if key pieces of technology are in place. more

  • Governing Big Data and Hadoop

    Big data presents significant business opportunities, when leveraged properly. And yet, big data also presents significant business and technology risks, when it is poorly governed or managed. more

  • BI, Analytics, and the Cloud: Strategies for Business Agility

    Cloud computing is a major trend that offers advantages in terms of flexibility, dynamic scalability, and agility. Even so, there’s been a lot of marketing hype. The reality is that, until recently, cloud has been slow to take off for business intelligence (BI) and analytics. Organizations have been concerned about security, performance, functionality, and other critical issues. TDWI Research is now seeing a significant shift as more organizations show willingness to experiment with BI and analytics in the cloud and are moving into deployment. more

  • Combat Rising Integration Complexity with dPaaS

    Today's integration complexities are supersized. Businesses must contend with unprecedented volumes and varieties of data at a time of growing IT resource scarcity and aging integration software. Throw into the mix the high demands—and even higher expectations—placed on analytics as a way of driving business performance, and it's easy to see why many integration environments are overwhelmed and underperforming. more

  • The What, Why, When, and How of Data Warehouse Modernization

    Despite their ongoing evolution, data warehouses (DWs) are more relevant than ever as they support operationalized analytics and wring business value from machine data and other new forms of big data. In the age of big data analytics, it’s important to modernize a DW environment to keep it competitive and aligned with business goals. more

  • Moving Forward with IoT: Introducing TDWI's New IoT Readiness Assessment Tool

    The Internet of Things (IoT) is hot and getting hotter. Consumers use it for health monitoring and “smart” home devices, such as thermostats and appliances. On the business front, a piece of equipment—or any business asset, really—can be tagged, monitored, and analyzed. This might include a sensor-enabled pressure valve on a piece of drilling equipment, a tagged piece of construction material, food moving to market, or a chip placed in an employee badge, not to mention smart cities, smart power grids, and more. more

  • Dynamic Metadata: Enabling Modern BI Architecture

    In a highly competitive market, today’s forward-looking organizations are seeking to optimize and modernize their IT investments, specifically in enterprise business intelligence (BI). There’s a strong push to capitalize on newer features such as self-service BI, advanced analytics, and customized visualizations—all of which relinquish the centralized data governance necessary for corporate and regulatory compliance. more

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Upcoming TDWI Events

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  • ConferenceTDWI Austin 2016 Austin, TX

    December 4-9, 2016

    TDWI Austin focuses on state-of-the-art technologies and practices for storing, analyzing, and harnessing enterprise data to drive customer-centric innovation. TDWI Austin isn’t like other events—instead of one-hour sessions, vendor pitches, and marketing fluff, industry experts share their knowledge and experiences in half- and full-day sessions organized around the skills you need in your job today.

  • Executive SummtExecutive Summit Austin 2016

    Data-Driven Emerging Technologies

    Austin, Texas
    December 5-6, 2016

    An interactive summit for business, IT, and analytics leaders who select and implement emerging technologies to solve new challenges and align with new business opportunities. Register and participate in intimate sessions, network with your peers and learn best practices from the leaders of the data revolution.

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