On Demand
The conventional approach to data warehousing may satisfy conventional reporting and straightforward analytical needs. Yet outside of the enterprise data warehouse, the information world has rapidly evolved and changed – there are new data sources, streaming different kinds of data, all coming at faster speeds. While we trust our existing data warehouse platforms to meet existing business needs, how can we integrate new technologies to address new business challenges without disrupting the consumers who rely on the trust and security of the established reporting and analysis platforms and applications?
David Loshin
Sponsored by
TDWI and IBM Content
The Internet of Things (IoT)—a network of physical objects accessed through the Internet—has big implications for both business and consumers. From data center environmental sensors to remote asset tracking, the IoT can help improve business processes and create new value. TDWI research indicates growing excitement around the IoT and machine data.
Fern Halper, Ph.D.
Sponsored by
SAP
The Internet of Things - a network of connected physical objects that can send and receive data over the Internet—is a hot market topic. It’s about connecting devices, sensors, electronics and more. It’s exciting, innovative, and important. The network itself is a big trend, but the analytics that can be performed over this data will be where the value lies.
Fern Halper, Ph.D.
Sponsored by
Dell EMC
There are two technological advances that are influencing significant changes in the way we think about data integration: the increasing consumption of external streaming data and the reliance on cloud computing as an acceptable alternative to on-premises computing. The enlightened perception of using the Internet as a broad platform for distribution of data and computing means that conventional approaches to data exchange and ingestion are yielding to more sophisticated approaches to data integration that, paradoxically, rely on a simplified development architecture.
David Loshin
Sponsored by
Liaison Technologies
Organizations can gain powerful, actionable insights by combining maps, geographical data, and relevant “big data” sources such as customer behavior or sensor data. Leading firms in a variety of industries—including retail, real estate, energy, telecommunications, land management, and law enforcement—are today engaged in projects involving geospatial analytics, and broader interest is growing. TDWI Research, in a recent survey on emerging technologies, found that the number of respondents who stated that they would be using geospatial analytics will double over the next three years.
Fern Halper, Ph.D., David Stodder
Sponsored by
Hewlett Packard Enterprise
Without design principles, swimming in circles in a big data lake can make your arms tired. Fortunately, the data lake concept has evolved sufficiently that best practices have emerged. In an open discussion, these big data experts will shed light on how a data lake changes the data storage, data processing, and analytic workflows in data management architectures.
Wayne Eckerson
Sponsored by
MapR, Teradata
Some emerging technologies (ETs) are so new that they are truly just emerging—for example, technologies for agile BI and analytics, data visualizations, BI on clouds or SaaS, event processing, Hadoop, Apache Spark and Shark, mashups, mobile BI, NoSQL, social media, the Internet of things, solid-state drives, and streaming data. Other ETs have been around for a few years, but are just now seeing appreciable user adoption—for example, appliances, competency centers, collaborative BI, columnar databases, data virtualization, open source, in-database analytics, in-memory databases, MDM, real-time operation, predictive analytics, and unstructured data.
Philip Russom, Ph.D., Fern Halper, Ph.D., David Stodder
Sponsored by
Hewlett Packard Enterprise, MicroStrategy, Qlik®, Snowflake, Trifacta, Voltage Security, Striim