DEVELOPMENT, DEPLOYMENT & DELIVERY

Languages and software environments for analytics development as well as analytics deployment and delivery models to help organizations achieve their goals.

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  • 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

  • Ask the Expert: Demystifying Semantics and Ontologies
    TDWI Members Only

    We hear more and more about semantics these days, but what does it mean? What is an ontology and how does it relate to a data model? Do semantics and ontologies have a role to play in data architecture and data modeling? 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

  • Ask the Expert about the Role of Data Visualization on Data Validation
    TDWI Members Only

    Data visualization has become a standard part of the business intelligence fair. It is now expected that a business intelligence team include a rich set of graphics in the tooling used across the business. In the real-time world, we are faced with the challenge of handling data streams directly from operational tools. This real-time data when presented visually tend to immediately skew to highlight outliers and exceptions in the data. more

  • Modern Data Warehouse Integration: Bringing Data Together in the Cloud

    As more organizations leverage hosted data warehouse environments and cloud-based reporting and analytics services, the challenges of data integration become more acute. In the past, data integration was straightforward: most of the data that flowed into the data warehouse originated well within the corporate firewall. Today, however, there is an increasingly varying mix of data sources, including on-premises data systems, cloud-based databases, externally-produced third-party data, as well as data sourced from software-as-a-service (SaaS) environments. The diversity of these sources contributes to growing complexity in bringing the data together; different data refresh rates, streaming cadences, and timing differences confound conventional staging and bulk load processes, leading to increased operational efforts at best, and inconsistent results at worst. 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

  • Ask the Expert on The UX Guide to Analytics
    TDWI Members Only

    Enterprise analytics spans a wide array of categories but they all have one thing in common, they require human interaction to realize value. However, much of that value is often left on the table. Factors such as user interviews, persona design, stakeholder buy in, wireframing, iteration, adoption and feedback are underutilized and greatly increase the risk of user disengagement and stakeholder frustration. Analytics managers and dashboard creators can miss the opportunity to leverage user motivations to drive success. more

  • Up to the Minute: The Need for Rapid Adoption of Streaming Data

    As Internet of Things (IoT) technologies become more common and web data grows in volume, there is growing evidence that the ability to analyze continuous data is not only valuable but necessary. In fact, those with the ability to capture and analyze massive numbers of independent continuous data streams will have a powerful capability that will help them to power operational intelligence and predictive analytics. A growing number of applications increasingly rely on fast analysis, but tomorrow’s world will be even more dependent on up-to-the-minute consumption of data streams. more

  • Ask the Expert on the Roles and Construct of a Thriving Analytic Team
    TDWI Members Only

    Most organizations believe they will achieve better analytic results if they populate a deeper bench of experienced data scientists and machine learning practitioners. But this is akin to building a home exclusively with highly skilled framers, brick layers and cabinet makers. You’ll end up with a solid structure and great workmanship, but not a true functional home. 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

  • Ask the Expert on Determining the Economic Value of Data (EvD)
    TDWI Members Only

    Most organizations lack a road map for leveraging data and analytics to optimize key business processes, uncover new business opportunities or deliver a differentiated customer experience. They do not understand what’s possible with respect to integrating data and analytics into the business model. And the Internet of Things only exacerbates the volume and variety of data that organizations could be capturing. 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.