The processes and approaches to deliver business value through data and analytics. Includes a strong focus on leadership strategies and organizational management to maximize data management and analytics impact.

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Research & Resources

  • Developing a Bi-Modal Logical Data Warehouse Architecture Using Data Virtualization

    Download this white paper for an explanation of logical data warehouse architecture and why organizations should invest in it. more

  • Use Self-Service Analytics to Build Strong Data Teams white paper cover

    If you want your business to be data-driven, you must first make an important decision about how to tap into your organization’s vast resources of raw data and how to turn this data into actionable business intelligence. more

  • NiFi for Dummies hortonworks white paper cover image

    Apache NiFi is an integrated data logistics and simple event processing platform. It provides an end-to-end platform that can collect, curate, analyze and act on data in real-time, on-premise, or in the cloud with a drag-and-drop visual interface. This book is a must read. more

  • Forrester Reprints: Stretch Your Data Management Capabilities hortonworks white paper cover image

    Firms face an enormous data management challenge: how to act on data and insights to serve increasingly powerful customers and outmaneuver disruptive competitors. Architects once had time to plan methodically, but those days are quickly fading as the pace of business change accelerates. The only answer is a continuous improvement that stretches data capabilities in an “insights-first” strategy. This report provides advice for enterprise and data architects to help them systematically improve their data management capabilities in order to turn data into insights. more

  • Modernizing the Analytic Database with Cloudera Enterprise Cloudera white paper cover

    Learn how Cloudera Enterprise provides a new kind of analytic database designed to tap into the full value of your data. As an adaptive, high-performance, analytic database, it opens up BI and exploratory analytics over more data—using the skills analysts already rely on—to derive instant value. more

  • ESG: Efficiently Offloading and Optimizing BI Workloads to Hadoop with Cloudera Navigator Optimizer Cloudera white paper cover

    This ESG Lab Review documents the recent analysis of Cloudera Navigator Optimizer with a goal of validating its ability to enable organizations to identify and offload SQL workloads from legacy data marts and costly enterprise data warehouses (EDWs) to a modern analytic database built on Hadoop, while optimizing existing workloads already on Hadoop. more

  • Deep Learning: A Guide for Enterprise Architects

    Download this white paper for an introduction to deep learning. Learn how Cloudera’s unified platform for data and machine learning can help your organization move forward with deep learning. more

  • Experian Gets a 360-Degree Customer View Cloudera WP Experian

    Download this white paper to learn how Cloudera solutions are enabling Experian, a credit reporting company, to create a better customer experience. more

  • Deep Learning: The Start of an AI Revolution for Customer Insights Professionals Cloudera WP DL Customer Insights

    Download this white paper to learn how deep learning will help businesses understand their customers. more

  • TDWI Checklist Report | Data Monetization: 7 Steps to Building Consumable Data Solutions Google data monetization checklist report cover image

    Data products are not a new idea; data aggregators have been producing purchasable data sets for decades. However, as organizations have become motivated to be “data driven,” the concept of a “data product” has rapidly morphed into different shapes, including packaged data sets, lightweight API-based services, directly connected end-user visualizations, and full-blown access to hosted reporting and analytics dashboards. more

  • Agile Data Warehousing Using Automation Attunity Compose Agile Data Warehousing revised WP thumb

    Download this white paper to learn how Attunity Compose, a revolutionary agile analytics platform, is enabling businesses around the globe to reduce data warehouse project labor, accelerate time to value, and make more informed business decisions faster. more



  • Accelerating the Path to Value with Business Intelligence and Analytics: A TDWI Best Practices Research Report

    Organizations of all sizes are in competition to realize value from data – and to realize it faster. To do so, they increasingly need flexible and agile business intelligence(BI), analytics, and data infrastructure, not systems that take too long to develop and do not give users the dynamic, iterative, and interactive access to data that they need. Fortunately, technology developments are trending in a positive direction for organizations seeking to accelerate their path to value with BI, analytics, and the critical supporting data infrastructure. These include self-service BI and visual analytics, self-service data preparation, cloud computing and software as a service(SaaS), and new data integration technologies. more

  • Database Strategies for Modern BI and Analytics

    The data universe has changed. Big data, cloud computing, and open source have dramatically expanded the number of data warehousing offerings available to today’s businesses. An increasing number of companies are implementing self-service business intelligence (BI) and visual analytics tools to access and make sense of all of the new and diverse sources of data their teams are consuming. Data literacy is changing equally fast as an increasing number of “data consumers” want to interact with data on their own rather than through IT. more

  • Rethinking Enterprise BI in a Self-Service World: Balancing User Freedom with Enterprise IT Responsibilities

    Both product and tech leaders have always recognized that business intelligence (BI) is most valuable when it is pervasive, contextual, and actionable. A new generation of solutions -- embedded BI – provides unprecedented power to weave reporting and analytics into the fabric of apps and business processes. 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

  • Big Data Management Best Practices for Data Lakes

    Organizations are pursuing data lakes in a fury. Organizations in many industries are attempting to deploydata lakes for a variety of purposes, including the persistence of raw detailed source data, data landing and staging, continuous ingestion, archiving analytic data, broad exploration of data, data prep, the capture of big data, and the augmentation of data warehouse environments. These general design patterns are being applied to industry and departmental domain specific solutions, namely marketing data lakes, sales performance data lakes, healthcare data lakes, and financial fraud data lakes. more

  • Making Data Preparation Faster, Easier, and Smarter

    Business users, business analysts, and data scientists have diverse data needs and specialties, but they all have one thing in common: they are tired of long, complicated, and tedious data preparation. Unfortunately, data preparation is getting even more difficult as users doing analytics and data discovery reach out to larger volumes of different types of data. 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

  • 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

  • Business, IT, and Self-Service Data Preparation: Can We Talk?

    One of the hottest trends today is self-service data preparation. Following the path of front-end tools for self-service business intelligence (BI) and visual analytics, self-service data preparation is aimed at providing nontechnical business users with the ability to explore data and choose data sets to fit their BI and analytics requirements. The goal is to reduce IT hand-holding—an ambitious one considering that, according to TDWI research, in most organizations IT manages nearly all data preparation steps, which can include data ingestion and collection, data transformation, data quality improvement, and data integration. Self-service data preparation thus represents a significant and potentially destabilizing change for IT and the way that IT and business work together. more

  • Land O’Lakes: How Free-Form Data Lakes Are Complementing Structured Data Warehouses

    As the data warehouse environment (DWE) continues to evolve, one of its strongest trends is the diversification of data platforms. A rigorously structured relational data warehouse is still at the heart of the DWE, but it is being joined more and more by other platform types, including data platforms based on columns, appliances, graph, streaming data, and open source. more

  • Harnessing the Power of Embedded Analytics for Financial Services

    Firms in financial services and many other industries are under pressure to improve efficiency, productivity, and decision-making power. For both daily operational and strategic decisions, organizations need to draw insights quickly from quality data so that they can understand and act on changes in markets, regulations, operations, customer behavior, fraud patterns, and the competitive landscape. Financial services firms need to be smarter and faster to survive in an industry where business models are changing and old ways of managing risk are out of date. more

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    Upcoming TDWI Events

    Conferences, Leadership Summits, Seminars, and Bootcamps

    • Conference TDWI Chicago Conference Chicago

      May 6-11, 2018
      Super Early Bird Ends March 23

      Join us for our annual conference, TDWI Chicago, to discuss the latest developments in enterprise data management, analytics, and business intelligence. Dive into industry best practices with world-renowned speakers and get in-depth training in all things data.

    • Leadership Summit TDWI Chicago Leadership Summit TDWI Leadership Summit

      May 7-8, 2018
      Super Early Bird Ends March 23

      The Chicago Leadership Summit is the best time to network, strategize, and get up-to-speed on new technologies and best practices. Join fellow business analytics and IT leaders in the Windy City learn how you can better enable your data team’s success.