On Demand
Design Thinking methods can help organizations overcome the limitations of traditional BI and analytics development. Design Thinking has enabled retail, banking, and other types of firms to revolutionize how they develop products and services to deliver exceptional customer experiences. These methods offer similar potential for unleashing your organization’s creativity in developing applications and services that delight internal users. With organizations under pressure to deliver higher ROI from data—and frustrated by BI and analytics applications and services that don’t meet users’ requirements or realize value from all the data that they have—now is the time to consider new approaches such as Design Thinking.
David Stodder
Sponsored By
Teradata
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.
Philip Russom, Ph.D.
Sponsored By
Pitney Bowes Software Solutions
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.
Philip Russom, Ph.D.
Sponsored By
Pitney Bowes Software Solutions
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.
Bill Schmarzo
Big data is becoming the norm for many organizations, which is a good thing because it can provide a great deal of insight. Big data includes large volumes of disparate data types: structured data as well as “newer” data such as text, images, geospatial and streaming data. Analyzing newer kinds of data is becoming mainstream.
Fern Halper, Ph.D.
Sponsored By
SAP
One of the most effective ways to spread the value and accelerate the adoption of business intelligence (BI) and analytics is to embed it into operational applications. End users and customers value the ability to model, monitor, ask, and answer questions throughout the workflow of familiar business applications. In this webinar, you will learn three ways BI and analytics are typically embedded into operational applications, new embedded use cases, and what to consider in your embedded analytics evaluation.
David Stodder
Sponsored By
Qlik
There is a lot of excitement in the market about machine learning, natural language processing, and AI. Although many of these technologies have been available for decades, new advancements in compute along with some new algorithmic developments are making these technologies more attractive. More organizations are embracing these advanced technologies for a number of reasons, including improving operational efficiencies, better understanding behaviors, and to gain competitive advantage.
Fern Halper, Ph.D.
Sponsored By
SAS, ThoughtSpot, Vertica