ANALYTICS, DATA SCIENCE & BUSINESS INTELLIGENCE

The technologies, techniques, and algorithms for analyzing all kinds of data to derive insights and take action for better decision making and enterprise success.

Explore Analytics, Data Science & Business Intelligence Content

Onsite Education

  • TDWI Big Data Fundamentals: Creating Value from Non-Traditional Data Sets

    Big data is a hot topic in BI and analytics. Yet it is a complex topic that is still in the early stages of evolution. Successful big data projects that deliver real business value are challenged by multiple definitions and rapidly shifting technologies. more

  • TDWI Analytics Fundamentals

    Analytics is a hot topic, but also a complex topic. This continuously growing field now includes descriptive, diagnostic, predictive, and prescriptive analytics. Applied analytics including optimization, simulation, and automation expand the scope. more

  • TDWI Business Intelligence Principles and Practices: Charting the Course to BI Success

    The BI life cycle spans a continuum that begins with large amounts of disparate data and stretches to encompass people, technology, information, analysis, and decision making. The benefits of BI are substantial: new business capabilities for insight, forecasting, planning, agility, and strategy execution. more

Online Learning

  • TDWI Data Science Bootcamp

    Get in-demand skills for the hottest job in analytics: Data Scientist. A 4-module intensive course covers everything from sourcing and prepping data to communicating business insights. more

Research & Resources

Webinar

  • End Your Data Struggle: How to Seamlessly Analyze Disparate Data

    Many organizations today are struggling to get value from their data and advanced analytics initiatives. The struggle begins with data diversity, as organizations are trying to support new apps, customer channels, sensors, and social media outlets. Each source may have its own data structure, quality, and container (in the form of files, documents, messages). The struggle is exacerbated by the exploding volume of data that must be captured, processed, stored, and delivered to the right users in a state that is fit for their own individual needs. 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

  • Big Data and Data Science: Enterprise Paths to Success

    Big data and data science can provide a significant path to value for organizations. These technologies, methodologies, and skills can help organizations gain additional insight about customers and operations; they can help make organizations more efficient, be a new source of revenue, and make organizations more competitive. more

  • Data-centric Security- Seven Best Practices for Protecting Your Most Sensitive Data

    As organizations incorporate newer data strategies, they also need to consider data-centric security. Data-centric security focuses security controls on the data, rather than perimeter servers or other infrastructure or the network. The goal is to protect sensitive data where it is stored and where it moves. This is becoming increasingly important as organizations start to deal with big data and newer data management platforms and hybrid architectures that include Hadoop and the cloud. Yet, TDWI research suggests that organizations still seem to focus on perimeter security and on application centric security for sensitive data. They think they are focused on protecting their data, but the reality is that many organizations don’t classify their data or know where their sensitive data lives, much less how to protect it. 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

  • Seven Strategies for Achieving Big Data Analytics Maturity

    Big data analytics is full of potential – but also fraught with pitfalls, obstacles, and a fog of hype surrounding the technologies. To be successful, organizations need to know where to begin with big data analytics and how to sustain progress so that they can achieve objectives. With key strategic initiatives hinging on success with big data analytics – including developing competitive innovations in customer intelligence and engagement, fraud detection, security, and product development – organizations need a roadmap for how to move ahead. 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

  • Discover 5 Keys to IoT Success: TDWI’s New IoT Readiness Assessment

    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

  • 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

  • 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

Upside

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    Upcoming TDWI Events

    Conferences, Leadership Summits, Seminars, and Bootcamps

    • Accelerate TDWI Boston Accelerate TDWI Accelerate Boston

      April 3-5, 2017
      REGISTRATION CLOSES MAR 31

      ACCELERATE brings together the brightest minds in data to share their expertise and insight on the future of data science and analytics. From sessions on core data science skills, to learning how to use new big data tools such as R, Python, and Spark, to talks on the latest trends in machine learning, predictive analytics and artificial intelligence, attendees will learn from industry experts, receive valuable training, and network and share ideas with their data peers in an exciting and collaborative environment.

    • Conference TDWI Chicago Conference

      May 7-12, 2017
      EARLY BIRD DEADLINE APR 7

      TDWI Chicago addresses our greatest data challenges head-on: Data streaming, enriching your data lake with new information sources, and connecting to spectrum of IoT. You will leave TDWI Chicago’s 6-day in-depth conference with the skills and insights to design, build and analyze your organization’s data.