DATA MANAGEMENT

The technologies, architectures, and practices needed to manage data as a critical enterprise asset. It is a broad field, within which there are specialized disciplines.

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Research & Resources

  • TDWI Pulse Report | Reducing Inefficiency and Increasing the Value of Analytics and Business Intelligence Data watch Pulse Report cover image

    This first in a new series of reports offers focused research and analysis of trending analytics, business intelligence, and data management issues facing organizations. TDWI Pulse Reports are designed to educate technical and business professionals and aid them in developing strategies for improvement. 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

  • The Past, Present, and Future of Data Warehousing White paper cover

    You need a powerful, simple, and affordable data warehouse built for the cloud to store and analyze all your data in one location. In this e-book, we’ll detail key insights you can use to champion modern data warehouse technology within your organization, helping it become a data-driven enterprise. more

  • How and Why to Automate Your SaaS Data Pipeline Bedrock white paper cover image

    Small to medium-sized businesses use, on average, fifteen SaaS applications to boost productivity and open new engagement channels with customers. Download this white paper to see how data pipeline automation can give these companies a huge competitive advantage. more

  • Dynamic Data Marketplace: Fast Data for Fast Business Denodo White Paper cover

    With data services presented through a “storefront” interface where users can shop for best-fit data to meet their needs, we can make the shift from the enterprise data warehouse (EDW) to the enterprise data marketplace (EDM). more

  • TDWI Checklist Report | Data Architecture for IoT Communications and Analytics Checklist cover

    The foundation of a successful IoT implementation is a technical architecture that blends network connectivity with an information architecture for streaming, ingesting, filtering, and capturing data. This checklist explores some fundamental aspects of the data architecture necessary for IoT success. more

  • TDWI Checklist Report | Seven Best Practices for Machine Learning on a Data Lake Checklist Report cover

    As organizations collect and analyze increasing amounts of data, they are turning to the data lake as the platform to perform more advanced analytics such as machine learning. This TDWI Checklist Report presents best practices for advanced analytics on a data lake. more

  • TDWI Checklist Report | Six Strategies for Balancing Compliance with Data Value TDWI Checklist Report cover

    Businesses can only seize new data-driven opportunities if they recognize sensitive data and handle it responsibly. This report focuses on how targeted improvements to specific data management best practices and technology can contribute significantly to your success with GDPR compliance, as well as data governance and data-driven programs in general. more

  • Magic of Data Integration for the Enterprise - eGuide Attunity white paper cover image

    Read this fun eGuide to discover how the simple and automated Attunity data integration platform benefits users with its drag-and-drop GUI design that enables very high-volume universal data replication and ingestion as well as real-time, continuous data integration and loading. more

  • TDWI Checklist Report | Data Management for Data Lakes in the Cloud Informatica DM checklist cover image

    A lake or cloud can breathe new life into established enterprise data architectures (data warehouses, marketing channel data, digital supply chains) or create new and different ones (analytics labs and sandboxes, ecosystems of cloud-based operational applications). This report discusses the leading data management (DM) best practices you need for data lakes to be successful when deployed in the cloud. more

  • Sector Roadmap: Cloud Analytic Databases 2017 White paper cover

    Some relational databases have undergone significant cloud-related development in their latest releases. Those will be the focus of this Sector Roadmap, along with the databases built native for the cloud. more

Upside

Webinar

  • The Automation and Optimization of Advanced Analytics based on Machine Learning

    However, embracing machine learning successfully is challenged by ML’s serious data requirements. In development, designing an analytic model depends on very large volumes of diverse data. In production, an analytic model created via machine learning again needs voluminous data, so it can learn and improve over time. In turn, managing big data for machine learning demands a substantial data management infrastructure and tool portfolio. more

  • Six Strategies for Balancing Risk with Data Value

    Managing data for value is a business-oriented focus on the potential of data. It complements the all-too-common obsession with data’s technical requirements. Data value recognizes that data is a valuable business asset and should be leveraged accordingly. If you are managing data for value, your asset portfolio of data should be protected, grown, and governed. more

  • Extending Your Data Warehouse Environment with Hadoop: Bringing Enterprise and External Data Together

    Surveys run by TDWI show that roughly a fifth of mature data warehouse environments now include Hadoop in production. Hadoop is becoming entrenched in warehousing because it can improve many components of the data warehouse architecture—from data ingestion to analytics processing to archiving—all at scale with a reasonable price. more

  • What It Takes to Be Data-Driven: Technologies and Practices for Becoming a Smarter Organization

    Gut instinct alone is not enough to enable decisions that will drive success. Most businesses today believe in the power of BI and analytics to help drive insight and value. TDWI research indicates that the vast majority of organizations are using technology such as visual analytics and BI dashboards to help them gain insight. However, gaining insight and using that insight to make decisions are often two different things. more

  • Building a Successful Data Lake in the Cloud

    Data lakes on Hadoop have come on strong in recent years because they help many types of user organizations – from Internet firms to mainstream industries – capture big data at scale and analyze or otherwise process it for business value. more

  • Location Analytics for Your Data Lake: Driving New Business Insights and Outcomes

    Location information has been a growth area in recent years in data management, as user organizations of many sizes and industries have realized how location information can inspire new business insights, practices, and outcomes. In response, many users have reworked older enterprise data environments to enrich the data with more location information. At the same time they have begun capturing data from new sources that include location information, especially from sensors, machines, devices, vehicles, and the Internet of Things (IoT). Much of this new data is being managed in data lakes, which in turn are usually deployed atop Hadoop. more

  • Location Analytics for Your Data Lake: Driving New Business Insights and Outcomes

    Location information has been a growth area in recent years in data management, as user organizations of many sizes and industries have realized how location information can inspire new business insights, practices, and outcomes. In response, many users have reworked older enterprise data environments to enrich the data with more location information. At the same time they have begun capturing data from new sources that include location information, especially from sensors, machines, devices, vehicles, and the Internet of Things (IoT). Much of this new data is being managed in data lakes, which in turn are usually deployed atop Hadoop. more

  • Ask the Expert on Data Literacy
    TDWI Members Only

    Businesses of all types and sizes are becoming more and more defined by their data. As this happens, it is equally important to improve the ability of managers, staff and even the general public, to make decisions which are well-informed by an understanding of the data behind their choices. Data literacy is the ability to understand the nature of the data we work with, and the ways in which we can interpret and communicate through our use of this important resource. more

  • IoT’s Impact on Data Warehousing: Defining IoT in Terms of Its Data Requirements

    The Internet of Things (IoT) is a computing paradigm where a widening range of physical devices—including smartphones, vehicles, shipping pallets, kitchen appliances, manufacturing robots, and anything fitted with a sensor—can transmit data about their location, state, activity, and surroundings. Depending on the device type, some may also receive data and instructions that control device behavior. more

  • Ask the Expert: Data Science
    TDWI Members Only

    It’s hard to find a topic out there hotter than Data Science right now; and can be equally hard to find one more confusing. Data Science techniques have revolutionized nearly any industry you can imagine, and in some cases created whole new ones from thin air. Despite this, much of Data Science remains couched in mystery--a magic black box that is supposed to solve all of our problems. more

  • Making Multiplatform Data Architectures Work for You: Common Use Cases and Reference Architectures

    To leverage the new wave of advanced data sources available, users and architects are turning to a multiplatform data architecture (MDA), where numerous diverse data platforms and tools are integrated in a multiplatform, distributed architecture. An MDA is typified by an extreme diversity of platform types that may include multiple brands of relational databases, NoSQL platforms, in-memory functions, and tools for data integration, analytics, and stream processing. Any of these may be on premises, in the cloud, or in hybrid combinations of the two. more

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    Upcoming TDWI Events

    Conferences, Leadership Summits, Seminars, and Bootcamps

    • Conference TDWI Chicago Conference Chicago

      May 6-11, 2018
      Registration Ends May 5

      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
      Registration Ends May 5

      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.