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 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 BI and Analytics Executive Briefing

    Business Intelligence and Analytics are at the heart of business management today. Everyone from executives to knowledge workers depends on information to maximize business effectiveness and efficiency. more

  • 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

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

  • Top Ten Cloud Trends for 2017 Tableau Cloud Trends WP cover

    Download this white paper to understand how enterprises are slowly but steadily moving to the cloud by prioritizing hosted computing and cloud data storage, building technical expertise, and recruiting employees with cloud experience. more

  • Cloud Data Warehousing for Dummies Snowflake WP cover Cloud Data

    Download this e-book to discover how your organization can tap the power of massive amounts of data conveniently and affordably to enhance efficiency and transform raw data into valuable business intel. more

  • Modernize Your Supply Chain with Smart, Connected Analytics Birst white paper cover

    Download this white paper to learn how modern supply chain analytics will facilitate collaboration beyond the four walls of your business and across the entire ecosystem of partners and suppliers. more

  • Architecting a Platform for Big Data Analytics (2nd ed.)

    Download this white paper to learn about IBM's cloud and on-premises big data analytics offerings, such as IBM BigInsights for Apache Hadoop; IBM integration with Apache Spark; and Big SQL and Fluid Query, which simplify access to traditional data warehouses and Hadoop. more

  • Why Cloud Is the Future of Data Warehousing IBM WP Why Cloud Is the Future thumbnail

    Download this white paper to learn how IBM dashDB transforms the traditional data warehouse with a hybrid architecture that provides all the flexibility and scalability of the cloud while ensuring security. more

  • Maximizing Your Data Lake with a Cloud or Hybrid Approach IBM white paper Maximizing Your Data Lake thumb

    Download this white paper to learn how your organization can benefit from a data lake maintained in a cloud or hybrid infrastructure. more

  • Just the Facts: Four Critical Concepts for Planning the Logical Data Warehouse

    If your first-generation warehouse is constraining your business, it may be time to consider a logical data warehouse solution. This white paper describes the four key facts you need to know to help you evaluate and choose the right solution. more

  • Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics

    The market for data warehouse and data management solutions for analytics is demanding broad solutions. Download this Gartner Magic Quadrant report to find the right vendor for your needs. more

  • Expert Tips for Accelerating Big Data Analytics and Better Business Insights Attunity white paper Acclerating Big Data Analytics cover image

    Download this white paper to learn the drivers and challenges for enabling real-time big data delivery in heterogeneous environments using analytics. more

  • Why Firms Struggle to Analyze More Data

    Today, data is the lifeblood of every enterprise. In order to succeed in this customer-centric era, data insights must inform every function of the business, including customer experience, operations, marketing, sales, service, and finance. This white paper describes how organizations that understand how data is used can prioritize their analytics efforts to find the most valuable and actionable insights on a regular basis. 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

Webinar

  • 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

  • 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

Upcoming Event

Upside

Filter by:
You must choose at least one filter.

    Upcoming TDWI Events

    Conferences, Executive Summits, Seminars, and Bootcamps

    • Accelerate TDWI Boston Accelerate TDWI Accelerate Boston

      April 3-5, 2017
      EARLY BIRD CLOSES MAR 3

      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
      SUPER EARLY BIRD ENDS MAR 17

      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.