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 Business Intelligence and Analytics Principles and Practices: Charting the Course to BI and Analytic Success (Updated)

    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

  • TDWI Predictive Analytics Fundamentals (Updated)

    Predictive analytics is a set of techniques used to gain new knowledge from large amounts of raw data by combining data mining, statistics, and modeling. Predictive analytics goes beyond insight (knowing why things happen) to foresight (knowing what is likely to happen in the future). 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

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

  • Putting Machine Learning to Work in Your Enterprise

    Everyone is talking about machine learning—software that can learn without being explicitly programmed, machine learning (and deep learning) can access, analyze, and find patterns in big data in a way that is beyond human capabilities. The technology is being used in a wide range of industries for use cases including fraud prevention, predicting crop yields, preventing and mitigating natural disasters, predictive maintenance of enterprise assets, and improving supply chain efficiencies. 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

  • 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

Upside

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    Upcoming TDWI Events

    Conferences, Leadership Summits, Seminars, and Bootcamps

    • Conference - UPDATED TDWI Orlando Conference

      December 3-8, 2017
      SUPER EARLY BIRD CLOSES OCT 20

      TDWI Orlando brings the future of data and analytics to life. Our comprehensive agenda covers the most important topics and success factors for high-impact data insights, with expert instructors whose only goal is to get you to the next level. Learn to enable rapid scalability and elasticity, manage users and data security, and democratize your analytics efforts.

    • Leadership Summit TDWI Orlando Leadership Summit

      December 4-5, 2017
      SUPER EARLY BIRD CLOSES OCT 20

      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.