On Demand
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
Most business intelligence (BI) systems were initially designed to support managed forms of reporting and simple analytics. Reports in these BI systems needed to be auditable, governable, tested, required high data quality, and so on. Now, however, organizations want to do more with their BI systems than reporting.
Rick van der Lans
Cloud software offerings have exploded in the data management and governance scene in a big way. Longstanding leaders in the data quality tool market are releasing cloud versions of their DQ platforms while upstart cloud-only competitors attempt to gain market share by selling more lightweight toolsets, often directly to business divisions rather than IT. Interesting hybrid architectures are also being tested, sometimes with multiple vendors and sometimes with multiple types of implementations of the same vendors’ tools.
Aaron Fuller
Sponsored by
Trillium Software
Data, data everywhere… Today’s BI and analytics implementation experts are faced with increasing volumes and sources of data – on premises and off – new and innovative technologies, more complex data integration and quality issues, and difficulties in maintaining and enhancing these diverse BI architectures.
Claudia Imhoff, Ph.D.
Sponsored by
Collibra
As the rate of data management innovation accelerates, many data warehouse professionals are beginning to identify where gaps in the conventional data warehouse architecture prevent the organization from getting the best advantage from its information assets. Open source platforms, big data systems, and cloud computing all promise to revolutionize the pervasiveness of business intelligence and analytics across the organization. Consequently, many of these professionals are exploring ways to modernize their business intelligence, reporting, and analytics environments.
David Loshin
Sponsored by
Snowflake
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.
Donald Farmer
The number of options for storing, manipulating and accessing data have exploded over the last decade. Open source “NoSQL” (not-only SQL) have spread like wildfire among organizations with cutting-edge analytics. They, along with Hadoop, have lowered the cost barrier to powerful, flexible and incredibly scalable implementations of systems that access unstructured, semi-structured and flexibly-structured data in addition to relational data. However, the learning- and investment-curves have been prohibitive for many organizations. It is all too common that a company would like to advance its database and analytics capabilities with non-relational data but they don’t have the time, human resources or budgets to dedicate to spinning-up and learning how to use these new technologies.
Aaron Fuller
Sponsored by
IBM